The novel coronavirus disease 19 (COVID-19) has resulted in an estimated 20 million excess deaths and the recent resurgence of COVID-19 in China is predicted to result in up to 1 million deaths over the next few months. With vaccines unable to halt transmission it is important to continue our quest for safe, effective, affordable drugs that will be available to all countries. Drug repurposing is one of the strategies being explored in this context. Recently, out of 7,817 approved drugs, 214 candidates were systematically down-selected using a combination of 11 filters including approval status, assay data against SARS-CoV-2, pharmacokinetic, pharmacodynamic and toxicity profiles. These drugs were subjected in this study to virtual screening against various targets of SARS-CoV-2 followed by molecular dynamic studies of the best scoring ligands against each target. The chosen molecular targets were Spike receptor binding domain, Nucleocapsid protein RNA binding domain, and key non-structural proteins 3, 5, 12, 13 and 14. Four drugs approved for other indications — alendronate, cromolyn, natamycin and treprostinil — look sufficiently promising from our in silicostudies to warrant further in vitro and in vivo investigations as appropriate to ascertain their extent of anti-viral activities.

Molecular Dynamics (MD) simulations model motion of molecules in atomistic detail and aid in drug design. While simulations on large systems may require several days to complete, analysis of terabytes of data generated in the process could also be time consuming. Recent studies captured exciting and dramatic drug-receptor interactions under cell-like complex conditions. Such advances make simulations of biomolecular interactions more realistic, insightful, and informative and have potential to make drug design more realistic. However, currently available resources and techniques do not provide, in reasonable time, a comprehensive understanding of events seen in simulations. We demonstrate that big data approach results in significant speedups, and provides rapid insights into simulations performed. Advancing this improvement, we propose a scalable, self-tuning, and responsive framework based on Cloud-infrastructure to accomplish the best possible MD studies with given priorities and within available resources.

G protein-coupled receptors (GPCRs) are critical drug targets. GPCRs convey signals from the extracellular to the intracellular environment through G proteins. There is evidence that some ligands that bind to the GPCRs activate different downstream signaling pathways. G protein activation or -arrestin biased signaling involves ligands binding to receptors and stabilizing conformations that trigger a specific pathway. Molecular dynamics (MD) simulations are especially valuable for obtaining detailed mechanistic information, including identification of allosteric sites and understanding modulators' interactions between receptors and ligands. Here, we highlight recent simulation studies and methods used to study biased G protein-coupled receptor signaling and their conformational dynamics. We also highlight applications of MD simulations to drug discovery.

Aurora kinase A (AURKA) is a normal cell proliferation-inducing enzyme encoded by AURKA gene, with over-expression observed in different types of malignancies. Hence, the goal is to find potential inhibitors against AURKA. In this study, molecular docking, Standard Precision and Extra Precision methods were employed. After the docking study, the ligands showed an extremely low binding score which suggested very high binding affinity of the ligands. Furthermore, Quantum polarized ligand docking (QPLD) was performed to predict the binding status of the molecules. Based on the binding affinity, the top four compounds were chosen for further analysis. The docked complexes were further analyzed in explicit water conditions using 100 ns molecular dynamics simulations and binding free energy calculation. Then, density functional theory (DFT) calculation was used to calculate the molecular properties of the molecules. Finally, systems biology experiments validated the molecular docking and molecular dynamics simulation studies and indicated that quercetin, kaempferol, luteolin and rutin could inhibit the AURKA. The results show that, these four molecules have high binding affinity to the AURKA and significant interactions (LEU139, GLU211and ALA213) were also identified with the hinge region of Aurora kinase A. Thus, LEU139, GLU211, and ALA213 were identified as the crucial protein mechanisms.

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and become a new target for anticancer drugs. In recent years, the small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamides LSD1 inhibitors using molecular docking, three dimensional quantitative structure-activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q²=0.783, r²=0.944, r²_pred=0.851) and Comparative molecular similarity indices analysis (CoMSIA q²=0.728, r²=0.982, r²_pred=0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, the ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

The current outbreak of coronavirus disease (COVID-19) caused by SARS-CoV-2 in Wuhan, China has killed more than 2600 people since December 2019. Currently there is no effective treatment for this epidemic. Drug for anti SARS-CoV-2 are urgently needed. In this study we evaluated two compound libraries containing launched drugs and compounds from 300 kinds of Traditional Chinese Medicine in order to find anti SARS-CoV-2 drugs. Docking and then calculating binding free energy were performed as workflow against four key anti-SARS-CoV-2 drug targets, 3CLpro, PLpro and RdRp from SARSCoV-2, and AAK1 from human as well. As a result, drugs launched with potential for antiviral usage were selected in the hope of providing some knowledge for future drug discovery.

Flavonoids are widely recognized as natural polydrugs, given their anti-inflammatory, antioxidant, sedative and antineoplastic activities. Recently, different studies have shown that flavonoid have the potential to inhibit BET bromodomains. Previous reports suggest that flavonoids are putative inhibitors of the ZA channel due to their orientation and interactions with P86, V87, L92, L94 and N140. Herein, a comprehensive characterization of the binding mode of the biflavonoid amentoflavone and fisetin is discussed. To this end, both compounds were docked with BRD4 using four docking programs. Results were post-processed with protein-ligand interaction fingerprints. To gain further insights into the binding mode of the two natural products, docking results were further analyzed with molecular dynamics. Results showed that amentoflavone makes numerous contacts in the ZA channel, as previously described for flavonoids and kinase inhibitors. It was also found that amentoflavone can potentially make contacts with non-canonical residues for BET inhibition. Most of these contacts were not observed with fisetin. Based on these results, amentoflavone was tested for BRD4 inhibition, showing activity in the micromolar range. This work may serve as basis for scaffold optimization and further characterization of flavonoids as BET inhibitors.

The details of antigen-antibody interactions and the identification of epitopes are critical for the development of monoclonal antibody drugs. Ab42 is a native human-derived anti-CFH monoclonal antibody. In this study, the interaction between antigen pCFH and antibody (Ab42) was theoretically demonstrated by molecular docking and MD simulation, combined with free energy calculation and computational alanine scanning (CAS), and key amino acids and epitopes were identified. Experimental alanine scanning (EAS) was then carried out to verify the results of the calculation, and our results indicated that Ab42 antibody forms hydrogen bonds and interacts hydrophobically with pCFH through the Tyr315, Ser100, Gly33, and Tyr53 residues on its CDR, while the main pCFH epitopes are located at the six sites of Pro441, Ile442, Asp443, Asn444, Ile447, and Thr448. In conclusion, this study has explored the mechanism of antigen-antibody interaction from both theoretical and experimental aspects, and our results have important theoretical significance for the design and development of relevant antibody drugs.

Glioblastoma multiforme (GBM) is a highly heterogeneous brain tumor with limited treatment options and a poor prognosis. Cancer stem cells (CSCs) have emerged as a critical factor in GBM resistance and management, contributing to tumor growth, heterogeneity, and immunosuppression. The transcription factor FOXM1 has been identified as a key player in the progression, spread, and therapy resistance of various cancers, including GBM. In this study, researchers conducted structure-based in silico screening to identify natural compounds that could target the DNA-binding domain (DBD) of the FOXM1 protein. Through molecular docking analyses, identified Silybin B as a potential inhibitor of FOXM1, exhibiting strong interaction with the protein. MD simulations were performed to validate the binding stability of the FOXM1-Silybin B complex. The study provides valuable insights into the potential of Silybin B as a FOXM1 inhibitor and its ability to induce senescence in GBM stem cells. These findings contribute to the development of structure-based design strategies for FOXM1 inhibitors and innovative therapeutic approaches for the treatment of Glioblastoma.

Polo-like kinase 1 (PLK1) plays a pivotal role in cell division regulation and emerges as a promising therapeutic target for cancer treatment. Consequently, the development of small-molecule inhibitors targeting PLK1 has become a focal point in contemporary research. The adenosine triphosphate (ATP)-binding site and the polo-box domain in PLK1 present crucial interaction sites for these inhibitors, aiming to disrupt the protein's function. However, designing potent and selective small-molecule inhibitors can be challenging, requiring a deep understanding of protein-ligand interaction mechanisms at these binding sites. In this context, our study leverages the fragment molecular orbital (FMO) method to explore these site-specific interactions in-depth. Through the FMO approach, we used the FMO method to elucidate the molecular mechanisms of small-molecule drug binding to these sites to design PLK1 inhibitors that are both potent and selective. Our investigation further entailed a comparative analysis of various PLK1 inhibitors, each characterized by distinct structural attributes. This comparison enhanced our understanding of the structure-activity relationships of these inhibitors, underscoring the efficacy of the FMO method in identifying critical binding features and predicting binding modes for small-molecule ligands. Furthermore, Our research spotlighted "hot spot" residues instrumental for selective and robust PLK1 binding. Our findings offer profound insights, priming the rational design of innovative potential PLK1 inhibitors with significant implications for developing anticancer therapeutics.

Polymers' controlled pyrolysis is an economical and environmentally friendly solution to prepare activated carbon. However, due to the experimental difficulty in measuring the dependence between tissues and pyrolysis parameters at high temperatures, the unknown pyrolysis mechanism hinders access to the target products with desirable morphologies and performances. In this study, we investigate the pyrolysis process of polystyrene under different heating rates and temperatures employing reactive molecular dynamics (ReaxFF-MD) simulations. A clear profile of the generation of pyrolysis products determined by the temperature and heating rate is constructed. It is found that the heating rate affects the type and amount of pyrolysis intermediates and their timing, and low-rate heating helps yield more diverse pyrolysis intermediates. While the temperature affects the pyrolytic tissues of the final equilibrium products, either too low or too high a target temperature is detrimental to generating large areas of graphitized tissue. The established theoretical evolution process matches experiments well, thus contributing to preparing target activated carbons by referring to the regulatory mechanism of pyrolytic tissues.

Eukaryotic cells contain membranes with various curvatures, from the near-plane plasma membrane to the highly curved membranes of organelles, vesicles, and membrane protrusions. These curvatures are generated and sustained by curvature-inducing proteins, peptides, and lipids, and describing these mechanisms is an important scientific challenge. In addition to that, some molecules can sense membrane curvature and a thereby be trafficked to specific locations. The description of curvature-sensing is another fundamental challenge. Curved lipid membranes and their interplay with membrane-associated proteins can be investigated with molecular dynamics (MD) simulations, given the right tools. Various methods for simulating curved membranes with MD are discussed here, including tools for setting up simulation of vesicles, and methods for sustaining membrane curvature. The latter are divided into methods that exploit scaffolding virtual beads, methods that use curvature-inducing molecules, and methods applying virtual forces. The variety of simulation tools allow the researcher to closely match the conditions of experimental studies of membrane curvatures.

The World Health Organization (WHO) documents malaria as one of the leading causes of high morbidity and mortality worldwide. The disease affects millions and kills thousands of people annually. Efforts to reduce the global burden of malaria have prompted WHO to recommend prevention strategies like using anti-malarial drugs. However, these strategies have been ineffective because of anti-malarial drug resistance. The only efficacious malaria treatment is Artemisinin-based Combination Therapy (ACT). However, the extended ACTs clearance times, linked to the emergence of artemisinin monotherapy resistance recorded most recently in Africa and the Great Mekong region, pose a danger to its efficacy. Therefore, better efficacious malaria drugs are required. Since P. falciparum heat shock protein 90 (PfHsp90) is a well-characterized malaria drugs target, this study uses it to discover more efficacious malaria drugs. An in-silico approach was used to discover PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria using molecular dynamics simulation (MDS) and hierarchical virtual screening. Geldanamycin (GDM), a well-known anti-PfHsp90 compound, was used to identify PfHsp90 inhibitors with pharmacological properties against Plasmodium malaria by screening it against the ZINC database via the ZINCPHARMER web server. This virtual screening process resulted in 17 hits. These ZINCPHARMER hits were subjected to drug-likeness and pharmacokinetics properties analysis in the SwissADME web server, and 9 of them satisfied the requirements. The 9 ZINC compounds were docked with PfHsp90 using the PyRx software to understand their interactions. From the molecular docking results, ZINC09060002 (-8.2 kcal/mol), ZINC72133064 (-7.8 kcal/mol), ZINC72163401 (-7.7 kcal/mol), ZINC72358537 (-8.1 kcal/mol), and ZINC72358557 (-7.6 kcal/mol) had better binding affinities to PfHsp90 than GDM (-7.5 kcal/mol). The stability of these molecularly docked protein-inhibitor complexes was assessed through MDS using GROMACS 2022. ZINC72163401, ZINC72358537, and ZINC72358557 formed stable complexes with PfHsp90. The lead compounds were subjected to in vitro validation for their inhibitory capability. They showed promising inhibition of parasite growth with IC50 values ranging between 200 – 400 ng/ml. In this regard, the three PfHsp90 inhibitors can be used as anti-malarial drugs. However, further structural optimization studies and clinical (in vivo) tests are necessary to ascertain the antimalarial activity of these compounds in humans.

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder. One of the important therapeutic approaches of AD is the inhibition of β‐site APP cleaving enzyme‐1 (BACE1). This enzyme plays a central role in the synthesis of the pathogenic β-amyloid peptides (Aβ) in Alzheimer's disease. A group of potent BACE1 inhibitors with known x-ray structures (PDB ID 5i3X, 5i3Y, 5iE1, 5i3V, 5i3W, 4LC7, 3TPP) were studied by molecular dynamics simulation and binding energy calculation employing MM_GB(PB)SA. The calculated binding energies gave Kd values 0.139 µM, 1.39 nM, 4.39 mM, 24.3 nM, 1.39 mM, 29.13 mM and 193.07 nM, respectively. These inhibitors showed potent inhibitory activities in enzymatic and cell assays. The Kd values were compared with experimental values, the structures were discussed in view of the energy contributions to binding. Drug likeness of these inhibitors is also discussed. Accommodation of ligands in the catalytic site of BACE1 is discussed depending on the type of fragment involved in each structure. Molecular dynamics (MD) simulations and energy studies were used to explore the recognition of the selected BACE1 inhibitors by Asp 32, Asp228 and the hydrophobic flap. The results show that selective BACE1 inhibition may be due to the formation of strong electrostatic interactions with Asp32 and Asp228 and a large number of hydrogen bonds, π-π and Van der Waals interactions with the amino acid residues located inside the catalytic cavity. Interactions with the ligands show a similar binding mode with BACE1. These results help to rationalize the design of selective BACE1 inhibitors.

Systems Chemistry has been a key component of origin of life research, invoking models of life’s inception based on evolving molecular networks. One such model is the Graded Autocatalysis Replication Domain (GARD) formalism embodied in a Lipid World scenario, which offers rigorous computer simulation based on defined chemical kinetics equations. GARD suggests that the first pre-RNA life-like entities could have been homeostatically-growing assemblies of amphiphiles, undergoing compositional replication and mutations, as well as rudimentary selection and evolution. Recent progress in Molecular Dynamics has provided an experimental tool to study complex biological phenomena such as protein folding, ligand-receptor interactions and micellar formation, growth and fission. The detailed molecular definition of GARD and its inter-molecular catalytic interactions make it highly compatible with Molecular Dynamics analyses. We present a roadmap for simulating GARD’s kinetic and thermodynamic behavior using various Molecular Dynamics methodologies. We review different approaches for testing the validity of the GARD model, by following micellar accretion and fission events and examining compositional changes over time. Near future computational advances could provide empirical delineation for further system complexification, from simple compositional non-covalent assemblies towards more life-like protocellular entities with covalent chemistry that underlies metabolism and genetic encoding.

Zirconium nitride (Zr-N) is a candidate material for inert matric fuel elements in breeder reactors. They have shown exceptional resistance to radiative corrosive environments. They have shown excellent resistance to radiation stability at operational conditions in current generation reactors. But being a candidate nuclear fuel material in generation reactors, their radiation stability at higher temperature conditions observed has not been reported. We have employed molecular dynamics simulations to study the damage cascades and radiation stability of ZrN at 600K. The process of primary damage evolution by considering varying overlapping cascades with 10, 20 keV incident PKA’s reported here. The defects interface interaction and diffusion mechanism at the interface are reported.

In this paper, we introduce a simple yet powerful and working version of the molecular dynamics code using the Python 3.9 language. The code contents are published in the link given in the appendix 1. The structure and components of the program is given in detail using flowcharts and code snippets. The program consists of major features like velocity verlet integrator, thermostats, COM removal, input and output modules, virial, pressure, and other thermodynamic quantities estimation etc. The author believes that this program will be helpful to graduate students who perform research in molecular dynamics simulations who intend to write their own code instead of the sophisticated open source packages.

The main regulatory factors during the adaptation of cancer cells to hypoxic stress are the hypoxia-inducible factors (HIFs), which are being increasingly recognized as an interesting and challenging target for the design of new chemotherapeutic molecules. HIF2A was found to have an large internal hydrophilic cavity within its PAS-B domain, unique to this sub-unit and is suggested to be a possible ligand-binding site. Regulation of HIF2A by cellular molecules is still greatly unknown. In This paper we have employed in-silico techniques, such as molecular docking and dynamic simulation, to design new direct inhibitors against HIF-2A subunit via targeting one of its critical domains and the final top screened molecules have been tested on hypoxic cancer cells for further validation of their inhibitory potential. we targeted the hydrophilic cavity inside the PAS-B domain of the HIF2A to identify novel molecules with a high binding capacity. Virtual Screening methodology was used for molecular docking of NSC library against the target domain inside the HIF2A PAS-B domain with the top 5% compounds with significant MolDock and Re-rank scores were selected for further analysis. The NSC 106416, NSC 217021, NSC 217026, and NSC 215639 compounds were selected based on their docking scores. NSC 215639 had the minimum polar solvation energy and also had a relative strong binding energy. NSC 217026 had the strongest binding energy among other compounds.

In this work, a tool for estimating the contact angle from the molecular dynamics simulations is developed and presented. The tool (Achilles) can detect water droplet on hydrophobic and hydrophilic surfaces. The tool can reconstruct the droplets broken across the periodic boundaries. Further a neighbor density based accurate filter is used to find the droplet liquid vapor interface and a circle is fitted using it after removing the dense layers of water next to solid surface. This fitted circle is solved for contact angle and results are outputted in the form of graphical images and text. The entire content of the internal computations of the tool is broken down into 4 phases and users can monitor the outcomes at every phase through output images. The tool is tested using sample molecular dynamics results of water droplet on hydrophobic and hydrophilic surfaces. We believe this tool can be a good addition to the molecular dynamics simulation community who work on the interfacial physics, droplet evaporation, super hydrophobic surfaces, and wettability etc.

The effect of graphene (GR) on Ni surface relaxation and reconstruction in three different substrate orientations: {111}, {001}, {011}, at two different temperatures: 300K and 400K was studied using Molecular Dynamics simulation. The change of the interplanar distances of the substrate and redistribution of Ni and C atoms in direction perpendicular to the surface were compared with the equilibrium state of GR and bulk Ni, in the absence of the counterpart. The surface reconstruction for GR/Ni system was analyzed base on the calculated radial pair distribution function of Ni and C atoms. The surface roughness was visualized using 2D atomic distribution maps. For the studied substrate orientations and temperatures, it was found that the most densely packed orientation of the Ni base {111} provides minimal changes of the structural parameters of both counterparts at 400 K.

Li₂MnO₃ is critical component in the well-studied Li-excess cathode materials xLi₂MnO₃•(1- x)LiMO₂ for achieving high lithium storage capacity. In this article, the diffusion of Li ions in Li₂MnO₃ is studied using molecular dynamics (MD) simulation with well-behaved empirical force fields obtained by fitting against the crystal structure from experiment and phonons calculated using Density Function Theory (DFT). We have found two possible tetrahedral hopping channels, 0-TM and 1-TM(Mn⁴⁺) channel, which are differentiated by the face sharing octahedral cations. Simulation results show that the 0-TM channel is active for Li hopping, while 1-TM(Mn4+) channel is inactive. During the delithiation process, the Li ions in the TM layered are firstly removed, then those in the Li layer. However, the Li ions will be trapped in the tetrahedral 0-TM channels as long as the four face sharing octahedral sites are cleared. Up to x=1.0 for Li₂-xMnO₃, almost all the Li ions are located at the tetrahedral sites, forming a regular array along a axis. The de-intercalation of tetrahedral Li ions requires a high voltage (>5.2 V vs. Li/Li+), limiting the practical capacities measured in lab. The diffusion of Mn ions into the Li layers is observed in a deeper delithiated structure (x=1.2 for Li₂-xMnO₃), indicating an initial phase transformation to a spinel-like structure. However, the Mn ions are mainly trapped in the tetrahedral sites in the Li layer, instead of the octahedral sites fin spinel-like structure. A few of Mn ions diffusing into the octahedral sites in Li layers have no face sharing tetrahedral Li ions, revealing a further Li de-intercalation is imperative for the complete phase transformation. Our model is not stable for x≥1.4 in Li₂-xMnO₃. Other charge compensation mechanism should be considered in this high delithiation stage, eg. oxygen release.

Plasmodium species that cause malaria, a disease responsible for about half a million deaths per annum despite concerted efforts to combat it. The causative agent depends on type III beta phosphatidylinositol 4-kinase (PPI4K) during the development of merozoite. PPI4K is the only clinically validated Plasmodium kinase so far and its inhibitors are effective both in vitro and in vivo. In this work, a small library of ~22 000 fragments was virtually screened using PPI4K homology model to discover potential ligands of the enzyme. 16 virtual hits were selected based on ≤ -9.0 kcal/mol binding energy cut off and were subjected to similarity and substructure searching after they had passed PAINS screening. The derivatives obtained showed improved binding energies, which ranged from -10.00 to -13.80 kcal/mol. Moreover, the topmost ranking compound 31, with interesting drug-like quality was stable within the protein’s binding cavity during the 10 ns molecular dynamics simulation period. In addition, analysis of its binding pose revealed some unique binding interactions with PPI4K active site residues as the basis for the observed improved binding affinity. Overall, compound 31 appears to be a viable starting point for the development of PPI4K inhibitors with antimalarial activity.

Fibroin-chitosan composites, especially those containing nanohydroxyapatite, show potential for bone tissue regeneration. The physicochemical properties of these biocomposites depend on the compatibility between their components. In this study, the intermolecular interactions of fibroin and chitosan were analyzed using a molecular dynamics approach. Two types of systems were investigated: one containing acetic acid and the other containing calcium (Ca²⁺) and hydrogen phosphate (HPO₄²⁻) ions mimicking hydroxyapatite conditions. After obtaining the optimal equilibrium structures, the distributions of several types of interactions including hydrogen bonds, ionic contacts, and hydrophobic contacts along with the structural and energetical features were examined. The calculated binding energy values for the fibroin-chitosan complexes confirm their remarkable stability. The high affinity of fibroin for chitosan can be explained by the formation of a dense network of interactions between considered biopolymers. These interactions were found to be primarily hydrogen bonds and ionic contacts involving ALA, ARG, ASN, ASP, GLN, GLU, GLY, LEU, PRO, SER, THR, TYR, and VAL residues. As it was established, the complexation of fibroin with chitosan maintains the β-sheet conformation of the peptide. β-Sheet fragments in fibroin are involved in the formation of significant amount of hydrogen bonds and ionic contacts with chitosan.

The construction of molecular robotic-like objects that imitate living things is an important challenge for current chemists. Such molecular devices are expected to perform their duties robustly to carry out mechanical motion, process information, and make independent decisions. Dissipative self-organization plays an essential role in meeting these purposes. To produce a micro-robot that can perform the above tasks autonomously as a single entity, a function generator is required. Although many elegant review articles featuring chemical devices that mimic biological mechanical functions have been published recently, the dissipative structure, which is the minimum requirement, has not been sufficiently discussed. This article aims to show clearly that dissipative self-organization is a phenomenon involving autonomy, robustness, mechanical functions, and energy transformation. Moreover, the author details the recent experimental results of an autonomous light-driven molecular device that achieves all of these features. In addition, a chemical model of cell-amplification is also discussed to focus on the generation of hierarchical movement by dissipative self-organization. By reviewing this research, it may be perceived that mainstream approaches to synthetic chemistry have not always been appropriate. In summary, the author proposes that the integration of catalytic functions is a key issue for the creation of autonomous microarchitecture.

The use of carbon nanotubes to improve the mechanical properties of polymers is one of the promising directions in materials science. The addition of single-walled carbon nanotubes (SWCNT) to a polymer results in significant improvement of mechanical, electrical, optical, and structural properties. However, the addition of SWCNTs does not always improve the polymer properties. Also, when a certain content of SWCNTs is exceeded, the mechanical properties of the nanocomposite are getting worse. This article reports the results of computer simulations for predicting the mechanical properties of polymer/single-walled carbon nanotube nanocomposites. The efficiency of reinforcing polymer composites is considered depending on the concentration of carbon nanotubes in the polymer matrix, their size and structure. The elastic moduli of the nanocomposites were predicted using computer simulations for unit cell tension (0.1%). General trends in the mechanical properties of composites with polypropylene, poly (ethyl methacrylate), polystyrene matrices and SWCNTs are shown.

Micro-pollutants such as 17β-Estradiol (E2) have been detected in different water resources and their negative effects on the environment and organisms have been observed. Aptamers are established as a possible detection tool, but the underlying ligand binding is largely unexplored. In this study, a previously described 35-mer E2-specific aptamer was used to analyse the binding characteristics between E2 and the aptamer with a MD simulation in an aqueous medium. Because there is no 3D structure information available for this aptamer, it was modeled using coarse-grained modeling method. The E2 ligand was positioned inside a potential binding area of the predicted aptamer structure, the complex was used for an 25 ns MD simulation, and the interactions were examined for each time step. We identified E2-specific bases within the interior loop of the aptamer and also demonstrated the influence of frequently underestimated water-mediated hydrogen bonds. The study contributes to the understanding of the behavior of ligands binding with aptamer structure in an aqueous solution. The developed workflow allows generating and examining further appealing ligand-aptamer complexes.

When liquids are confined into nanometer-scale slit, the induced layering-like film structure allows the liquid to sustain non-isotropic stresses and thus being load-bearing. Such anisotropic characteristics of liquid under confinement arise naturally from the liquids’ wave number dependent compressibility that does not need solidification to take place as a prerequisite. In other words, liquids under confinement can still remain fluidity with molecules being (sub-)diffusive. However, the extensively prolonged structural relaxation time can cause hysteresis of stress relaxation of confined molecules in response to the motions of confining walls and thereby yield the quasi-static stress tensor history-dependent. In this work, by means of molecule dynamics, the discrepancy of stress tensor of a highly confined key base-oil component, i.e. 1-decene trimer, is captured after its relaxation from being compressed and decompressed. The results indicate that among the effects (e.g. confinement, molecular structure, and film density) that can potentially affect confined stress tensor, the ordering status of the confined molecules plays a predominant role.

Our work uses Iterative Boltzmann Inversion (IBI) to study the coarse-grained interaction between 20 amino acids and the representative carbon nanotube CNT55L3. IBI is a multi-scale simulation method that has attracted the attention of many researchers in recent years. It can effectively modify the coarse-grained model derived from the Potential of Mean Force (PMF). IBI is based on the distribution result obtained by All-Atom molecular dynamics simulation, that is, the target distribution function, the PMF potential energy is extracted, and then the initial potential energy extracted by the PMF is used to perform simulation iterations using IBI. Our research results have gone through more than 100 iterations, and finally, the distribution obtained by coarse-grained molecular simulation (CGMD) can effectively overlap with the results of all-atom molecular dynamics simulation (AAMD). In addition, our work lays the foundation for the study of force fields for the simulation of the coarse-graining of super-large proteins and other important nanoparticles.

A large amount of steel slag (SS) and CO2 are generated in the steelmaking process. The indirect CO2 capture using SS is a promising way for co-treatment of the wastes. Ammonium salt solution is widely used to extract Ca2+ from the SS since it is recyclable. Several works have focus on improving the carbonation rate by adjusting various parameters (e.g., temperature and pH). However, there is little detail information about the associating behaviors and interaction strength between the various ions in the ammonia solution during the carbonation process. In this work, the Ca2+–CO32-–NH4+–Cl-–H2O system was established by using Material studio software. The effects of temperature and concentration of CO32- on CaCO3 growth were explored at the atomic scale by calculating the binding energy, mean square displacement, and diffusion coefficient between particles. Furthermore, the microstructure, bonding characteristics, and occurrence behavior of each particle were studied though molecular dynamics simulation methods. The results showed that with the increase of temperature (20–80 ℃), the binding ability and diffusion coefficients of Ca2+ and CO32- increase in the system, which is beneficial to the formation of CaCO3 clusters. With the increase of the concentration of CO32- (15–25 vol.%), the binding ability and diffusion coefficient of Ca2+ and CO32- in the system are enhanced, which is beneficial to the formation of CaCO3 clusters.

By manipulating the various physico-chemical properties of amino acids, design of peptides with specific self-assembling properties has been emerging since more than a decade. In this context, short peptides possessing detergent properties (so-called “peptergents”) have been developed to self-assemble into well-ordered nanostructures that can stabilize membrane proteins for crystallization. In this study, the peptide with “peptergency” properties, called ADA8 extensively described by Zhang et al., is studied by molecular dynamics for its self-assembling properties in different conditions. In water, it spontaneously forms beta sheets with a β barrel-like structure. We next simulated the interaction of this peptide with a membrane protein, the bacteriorhodopsin, in the presence or absence of a micelle of dodecylphosphocholine. According to the literature, the peptergent ADA8 is thought to generate a belt of β structures around the hydrophobic helical domain that could help stabilize purified membrane proteins. Molecular dynamics is here used to challenge this view and to provide further molecular details for the replacement of detergent molecules around the protein. To our best knowledge, this is the first molecular mechanism proposed for ''peptergency''. In addition, our calculation approach should serve as a predicting tool for the design of beta peptergent with diverse amphipathic properties.

The past two decades have witnessed the introduction of and then a steady increase in the use of computational techniques in the study and development of molecularly imprinted polymers (MIPs). Molecular dynamics (MD) based studies have had a significant role in this development as they can provide insights concerning the mechanisms governing the molecular level events underlying MIP synthesis and MIP-ligand interactions and can be used for the identification of preferred monomer compositions and for the prediction of MIP properties. We here review the role that MD has played in the development of molecular imprinting and examine the different types of MD strategies that have been used, including their advantages and challenges. Recent trends in the application of MD to the study of MIPs are presented, along with a perspective on the future importance of MD-based studies for the development of molecular imprinting science and technology.

An important parameter in the development of a new drug is the drug's affinity to the identified target (protein/enzyme). Predicting the ligand binding to the target (protein/enzyme) by molecular simulation would allow the synthesis to be restricted to the most promising compounds.A restricted hybrid HF-DFT calculation was performed in order to obtain the most stable conformer of each ligand and a series of DFT calculations using the B3LYP levels with 6-31G* basis set has been conducted. The docking studies of the quinolone compounds will be performed with the CLC Drug Discovery Workbench to identify and visualize the ligand-receptor interaction mode.

This study comprehensively investigates Al2O3's mechanical properties, focusing on fracture toughness, surface energy, Young's modulus, and crack propagation. The density functional theory (DFT) is employed to model the vacancies in Al2O3, providing essential insights into this material’s structural stability and defect formation. The DFT simulations reveal a deep understanding of vacancy-related properties and their impact on mechanical behavior. In conjunction with molecular dynamics (MD) simulations, the fracture toughness and crack propagation in Al2O3 are explored, offering valuable information on material strength and durability. The surface energy of Al2O3 is also assessed using DFT, shedding light on its interactions with the surrounding environment. The combination of DFT and MD simulations provides a robust framework for a comprehensive understanding of Al2O3's mechanical properties, with implications for material science and engineering applications.

In this paper, the boiling flow inside a nanochannel with 700000 argon particle has been simulated by molecular dynamics (MD) simulation. This approach has been employed to analysis the superheated flow and its heat transfer pattern as well. For all simulations an external thrust force varying from 1 PN to 12 PN is exerted on inlet nanoparticles along the channel to have the forced annular boiling flow. Computations reveal that saturation condition and superheat degree have significant impacts on the liquid-vapor interface. Furthermore, because of the major influence of surface tension throughout a nanochannel, the x-velocity of liquid film and vapor core has not considerable fluctuations and stay smooth. All provided results show the behaviors completely similar to the available outcomes in the literature.

Complex colloidal fluids, depending on particulates’ shapes and packing fractions, may have a wide range of shear thinning and thickening behaviors. A particular interesting way to transition between different types of such behavior is by infusing functional complex particles that can be manufactured using modern techicques such as 3D printing. In this paper, we display 2D molecular dynamics simulations of such fluids with infused star-shaped functional particles, with variable leg length and number of legs, as they are infused in a non-interacting, coarse-grained fluid. We vary the packing fraction (ϕ) of the system, and for each different system we apply shear with various strain rate that turns the fluid into a jammed state and rise the apparent viscosity of fluid. We demonstrate the dependence of viscosity with the particles’ packing fraction. We show the role of shape and design dependence of the functional particles towards the transition to a shear thickening fluid .

2-Hydroxypropyl-β-cyclodextrin (HPβCD) has unique properties to enhance the stability and the solubility of low water-soluble compounds by inclusion complexation. Understanding of the structural properties of HPβCD and its derivatives based on the number of 2-hydroxypropyl (HP) substituents at the a-D-glucopyranose subunits is rather important. In this work, replica exchange molecular dynamics simulations were performed to investigate the conformational changes of single- and double-sided HP-substitution called as 6-HPβCDs and 2,6-HPβCDs, respectively. The results show that glucose subunits in both 6-HPβCDs and 2,6-HPβCDs have lower chance to flip than in βCD. Also, HP groups are occasionally blocking the hydrophobic cavity of HPβCDs, thus hindering the drug inclusion. We found that HPβCDs with high number of HP-substitutions are more likely to be blocked, while HPβCDs with double-sided HP-substitution are even more probable to be blocked. Overall, 6-HPβCDs with three and four HP-substitutions are highlighted as the most suitable structures for guest encapsulation based on our conformational analyses such as structural distortion, radius of gyration, circularity and cavity self-closure of the HPβCDs.

The oncogenic potential of high-risk HPVs is focused on producing the E6 and E7 oncoproteins responsible for disrupting the control of the cell cycle. Epidemiological studies propose the presence of the N29S and H51N variants of the HPV16 E7 protein as a significant association with cervical cancer. It has been suggested that changes in the amino acid sequence of E7 variants may affect the oncoprotein 3D structure; however, this remains unknown. Analysis of the structural differences of the HPV16 E7 protein and its variants (N29S and H51N) was performed through homology modeling and structural refinement by molecular dynamics simulation. We propose for the first time a 3D structure of the E7 reference protein and two of its variants (N29S and H51N) and conclude that the mutations induced by the variants in N29S and H51N have a significant influence on the 3D structure of the E7 protein of HPV16, which could be related to the oncogenic capacity of this protein.

In this study, modified red mud after phosphorus adsorption was used as the adsorbent, and hydrochloric acid and deionized water were used as desorbents to desorb phosphorus. The components in the adsorbent were optimized based on density functional theory, and adsorbent and desorbent models were established. Molecular dynamics simulation was performed to determine the phosphorus concentration before and after desorption, interaction energies, radial distribution function(RDF), mean-square displacement(MSD), and diffusion coefficient. The Monte Carlo method was used to simulate the desorption isotherm, desorption site, heat of desorption, and desorption energy. Simulation results showed that deionized water could only desorb phosphorus on the adsorbent surface, and the stability of the system deteriorated upon adding hydrochloric acid. Hydrochloric acid destroyed the ionic and hydrogen bonding between the O atoms in H2PO4− and reactive metal and oxygen atoms in the activated red mud particles. Moreover, the van der Waals force decreased considerably. The ionic and hydrogen bonds between H2PO4− and the surface of activated red mud particles were broken by hydrochloric acid, which accelerated the desorption of phosphorus from the adsorbent surface. The interaction between hydrochloric acid and phosphorus accelerated the diffusion, which decreased the adsorption capacity. Moreover, the desorption capacity increased with increasing temperature.

A major public health emergency has been created by the COVID-19 pandemic, which is brought on by the SARS-CoV-2 virus. Due to its crucial function in viral replication, the primary protease (Mpro) of the virus is a prime target for therapeutic research. In this study, we used molecular modeling and molecular dynamics simulations to examine the potential therapeutic uses of Mpro inhibitors for the treatment of COVID-19. Using induced fit docking and molecular dynamics simulations, we confirmed the top compounds after screening a library of compounds for their ability to bind to Mpro. Simulation interaction diagrams were used to investigate protein-ligand interactions, and MM-GBSA was used to determine binding energies. The Swiss ADME server was used to predict ADME properties. According to our findings, numerous substances are strong COVID-19 medication candidates since they have excellent ADME features and high binding affinities. This work serves as a foundation for additional experimental research and drug development initiatives aimed at Mpro.

Biological membranes are fascinating. Santiago Ramón y Cajal, who received the Nobel prize in 1906 together with Camillo Golgi for their work on the nervous system, wrote “[..]in the study of this membrane[..] I felt more profoundly than in any other subject of study the shuddering sensation of the unfathomable mystery of life”[1]. The visualization and conceptualization of these biological objects have profoundly shaped many aspects of modern biology, drawing inspiration from experiments, computer simulations, as well as from the imagination of scientists and artists. The aim of this review is to provide a fresh look on current ideas of biological membrane organization and dynamics by discussing selected examples across fields [1] The full quotation is “I must not conceal the fact that in the study of this membrane I for the first time felt my faith in Darwinism (hypothesis of natural selection) weakened, being amazed and confounded by the supreme constructive ingenuity revealed not only in the retina and in the dioptric apparatus of the vertebrates but even in the meanest insect eye. There, in fine, I felt more profoundly than in any other subject of study the shuddering sensation of the unfathomable mystery of life.” from the autobiography Recollections of My Life.

Sustainable development of our society demands recycling of metallic wastes which may contain a variety of metallic impurities. Thus, it is desirable to develop a ‘universal’ structure, such as an amorphous alloy tolerating high concentrations of metallic pollutants. We performed ab initio molecular dynamics simulations to manufacture a novel multicomponent amorphous alloy of twenty elements (20e-HEAA). Analysis reveals both topological and chemical compositional short-range ordering in the obtained 20e-HEAA and formation of B-B clusters. Electronic structure calculations reveal the metallic nature of the amorphous alloy with its Fermi level falling in a valley in the density of states. Moreover, the Zn 3d and Cd 4d electrons exhibit a localized nature and thus, should be excluded from the valence electron concentration (VEC) analysis in the study of high-entropy alloys. The information obtained here is helpful to get insight into multicomponent high entropy materials, especially multicomponent high-entropy amorphous alloys as potential circular metals.

We performed for the first time to our knowledge fully ab initio molecular dynamics simulations of additive tribochemistry in boundary lubrication conditions. We consider an organophosphourus additive that has been experimentally shown to reduce friction in steel-on-steel sliding contacts thanks to the tribologically-induced formation of an iron phosphide tribofilm. The simulations allow us to observe in real time the molecular dissociation at the sliding iron interface under pressure and to understand the mechanism of iron phosphide formation. We discuss the role played by the mechanical stress by comparing the activation times for molecular dissociation observed in the tribological simulations at different applied loads with that expected on the basis of the dissociation barrier.

The diffusion process of water molecules within a polyetherimide (PEI) glassy matrix has been analyzed by combining the experimental analysis of water sorption kinetics performed by FTIR spectroscopy with theoretical information gathered from Molecular Dynamics simulations and with the expression of water chemical potential provided by a non-equilibrium lattice fluid model able to describe the thermodynamics of glassy polymers. This approach allowed to construct a convincing description of the diffusion mechanism of water in PEI providing molecular details of the process related to the effects of the cross- and self-hydrogen bondings established in the system on the dynamics of water mass transport.

The selectivity in the simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA) has been an open problem in the biosensing field. Many surface modification methods were carried out for glassy carbon electrodes (GCE), including the use of graphene oxide and amino acids as a selective layer. In this work, molecular dynamics (MD) simulations were performed to investigate the role of serine oligomers on the selectivity of the AA, DA, UA analytes. Our models consisted of a graphene oxide (GO) sheet under a solvent environment. Serine tetramers were added into the simulation box and were adsorbed on the GO surface. Then, the adsorption of each analyte on the mixed surface was monitored from MD trajectories. It was found that the adsorption of AA was preferred by serine oligomers due to the largest number of hydrogen-bond forming functional groups of AA, while UA was the least preferred due to its highest aromaticity. Finally, the role of hydrogen bonds on the electron transfer selectivity of biosensors was discussed with some previous studies.

Amorphous solid dispersions are considered a promising formulation strategy for the oral delivery of poorly soluble drugs. The limiting factor for the applicability of this approach is the physical (in)stability of the amorphous phase in solid samples. Minimizing the risk of reduced shelf life for a new drug by establishing a suitable excipient/polymer-type from first principles would be desirable to accelerate formulation development. Here we perform Molecular Dynamics simulations to determine properties of blends of eight different polymer-small molecule drug combinations for which stability data is available from a consistent set of literature data. We calculate thermodynamic factors (mixing energies) as well as mobilities (diffusion rates and roto-vibrational fluctuations). We find that either of the two factors, mobility and energetics, can determine the relative stability of the amorphous form for a given drug. Which factor is rate limiting depends on physico-chemical properties of the drug and the excipients/polymers. The methods outlined here can be readily employed for an in-silico pre-screening of different excipients for a given drug to establish a qualitative ranking of the expected relative stabilities, thereby accelerating and streamlining formulation development.

Natural products from plants such as, chemopreventive agents attract huge attention because of their low toxicity and high specificity. The rational drug design in combination with structure based modeling and rapid screening methods offer significant potential for identifying and developing lead anticancer molecules. Thus, the molecular docking method plays an important role in screening a large set of molecules based on their free binding energies and proposes structural hypotheses of how the molecules can inhibit the target. Several peptide based therapeutics have been developed to combat several health disorders including cancers, metabolic disorders, heart-related, and infectious diseases. Despite the discovery of hundreds of such therapeutic peptides however, only few peptide-based drugs have made it to the market. Moreover, until date the activities of cyclic peptides towards molecular targets such as protein kinases, proteases, and apoptosis related proteins have never been explored. In this study we explore the in silico kinase and protease inhibitor potentials of cyclosaplin as well as study the interactions of cyclosaplin with other cancer-related proteins. Previously, the structure of cyclosaplin was elucidated by molecular modeling associated with dynamics that was used in the current study. Docking studies showed strong affinity of cyclosaplin towards cancer-related proteins. The binding affinity closer to 10 indicated efficient binding. Cyclosaplin showed strong binding affinities towards protein kinases such as EGFR, VEGFR2, PKB and p38 indicating its potential role in protein kinase inhibition. Moreover, it displayed strong binding affinity to apoptosis related proteins and revealed the possible role of cyclosaplin in apoptotic cell death. The protein-ligand interactions using LigPlot displayed some similar interactions between cyclosaplin and peptide-based ligands especially in case of protein kinases and a few apoptosis related proteins. Thus, the in silico analyses gave an insight of cyclosaplin as a potential apoptosis inducer and protein kinase inhibitor.

Molecular dynamics simulation is currently the theoretical technique eligible to simulate a wide range of systems from soft condensed matter to biological systems. However, of the excellent results that the technique has arrogated, this approach remains computationally expensive, but with the emergence of the new supercomputing technologies bases on graphics processing units graphical processing units-based systems GPUs, the perspective has changed. The GPUs allow performing large and complex simulations at a significantly reduced time. In this work, we present recent innovations in the acceleration of molecular dynamics in GPUs to simulate non-Hamiltonian systems. In particular, we show the performance of measure-preserving geometric integrator in the canonical ensemble, that is, at constant temperature. We provide a validation and performance evaluation of the code by calculating the thermodynamic properties of a Lennard-Jones fluid. Our results are in excellent agreement with reported data reported from literature, which were calculated with CPUs. The scope and limitations for performing simulations of high-throughput MD under rigorous statistical thermodynamics in the canonical ensemble are discussed and analyzed.

The global pandemic caused by the new SARS-COV-2 coronavirus makes it necessary to search for drugs for its control. Within of this research it has been known that the ivermectin drug, a FDA-approved drugs which is formulated as an 80:20 mixture of ivermectin B1a and B1b and used commonly for parasitic infections, has an inhibitory effect on viruses, includes SARS-COV-2 at in vitro level. In the particular case of SARS-COV-2 its mechanism of action remains elusive and controversial. Interestingly, the energy of interaction of ivermectin with any of the proteins the SARS-CoV-2 and the possible structural alterations at the protein level that this drug can cause have not been reported. In this sense, we carried out a bioinformatics study with docking strategies and molecular dynamics to predict the binding and disturbance induced by ivermectin in proteins associated with SARS-CoV-2. We use DockThor and Molegro docking scores. The DockThor server and myPresto software were used to build complexes and dynamics studies, respectively. The results obtained suggested that ivermectin is capable of docking with the 3CL protease and the HR2 domain, and may promote structural changes in these proteins by inducing unfolding/folding. Specifically, ivermectin brings protease to a significantly more deployed conformational state and the HR2 domain to a more compact state compared to the native state. Finally, it is shown that B1a and B1b macrocyclic lactones have a behavior different from to each target protein. These results suggest a possible inhibitory effect against SARS-CoV-2 due to a synergistic role of this drug to spontaneously bind to two important proteins involve in the proliferation of this virus. However, more studies are required on this possible mechanism of action.

Background: Currently, limited number of therapeutic options are available to treat Diabetes mellitus, and to find a potential candidate, laboratory work takes time and also needs animal studies. So, the aim of this study was to determine the efficacy of some natural phytocompounds with the aid of molecular docking, bioinformatics and in silico drug design approaches. Method: Two proteins (Human CYP3A4 linked to metformin and Human dipeptidyl peptidase-IV) were selected and molecular docking studies were conducted using Pymol, AutoDock Vina, PyRx, and Discovery Studio. Different important pharmacokinetic parameters like ADME and toxicity data were obtained from online databases SwissADME and pkCSM program. Results: It was found that human dipeptidyl peptidase-IV (PDB ID: 4A5S) has exhibited a maximal affinity of -9.7 Kcal/mol for bryonolic acid and hesperidin, but only -6.7 kcal/mol for metformin hydrochloride. Similarly, the highest affinity of hesperidin for human CYP3A4 bound to metformin (PDB ID: 5G5J) is -10.7 Kcal/mol compared to metformin hydrochlor (-6.3 Kcal/mol). Besides, all the compounds have been documented outstanding ADMET profile, and accepted by drug-likeness or Lipinski rule. Conclusions: The present study suggested that these compounds can be further investigated in vitro and in vivo to establish them as lead compounds against Diabetes mellitus..

The human serotonin transporter (hSERT) terminates neurotransmission by removing serotonin from the synaptic cleft, which is an essential process plays an important role in depression. In addition to substrate serotonin, hSERT is also the target of drugs of abuse like cocaine and clinically used antidepressants such as escitalopram and paroxetine. To date, few studies attempt to investigate the unbinding mechanism underlying the orthosteric and allosteric modulation of hSERT. The high-resolution X-ray structure of hSERT resolved recently enables us to theoretically study the unbinding of the above four ligands against the S1 or S2 site of hSERT, by means of molecular docking, molecular dynamics (MD) and potential of mean force (PMF) simulations. We proved that for either the S1 or S2 site, the other three ligands (cocaine, escitalopram and paroxetine) are much more favorable than the original substrate serotonin, whether in kinetics along the unbinding pathways or in thermodynamics at the equilibrium states. Furthermore, the S1 site is much more favorable than the S2 site, for each ligand. Interestingly, inspection revealed that there are ~ 3Å lengths between the allosteric site of serotonin and cocaine, and an unseen un-binding pathway for escitalopram at the S1 site except for verification of the broadest trail.

In the dynamic landscape of drug discovery, Computer-rAided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADD's historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADD's predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. The paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery.

Efficient thermal management of modern electronics requires the use of thin films with highly anisotropic thermal conductivity. Such films enable the effective dissipation of excess heat along one direction while simultaneously providing thermal insulation along the perpendicular direction. In this study, we investigate the thermal conductivity of bilayer graphene (BLG) sheets using non-equilibrium molecular dynamics, examining both in-plane and cross-plane thermal conductivities. The in-plane thermal conductivity of 10 nm × 10 nm BLG with zigzag and armchair edges at room temperature is found to be around 204 W/m.K and 124 W/m.K, respectively. The in-plane thermal conductivity of BLG increases with sheet length. For all sizes, BLG with a zigzag edge exhibits higher thermal conductivity than that of the armchair edge, with this difference becoming more pronounced as the lengths of the sheets increase. In addition, increasing temperature from 300 K to 600 K decreases the in-plane thermal conductivity of a 10 nm× 10 nm zigzag BLG by about 34%. Similarly, the application of a 12.5% tensile strain induces a 51% reduction in its thermal conductivity compared to the strain-free values. Armchair configurations exhibit similar responses to variations in temperature and strain, but with less sensitivity. Furthermore, the cross-plane thermal conductivity of BLG at 300 K is estimated to be 0.05 W/m·K, significantly lower than the in-plane results by approximately four orders of magnitude. The cross-plane thermal conductance of BLG decreases with increasing temperatures, specifically, at 600 K, its value is almost 16% of that observed at 300 K.

The adsorption of proteins on polymer is widely used in biosensors. Here, molecular dynamics (MD) simulation was used to study the immobilization of angiotensin converting enzyme II (ACE2) with six initial orientations proposed on polystyrene (PS) at the ambient conditions of pH (4.5, 6, 7, 8, 9.5) and NaCl (0.01, 0.05, 0.1, 0.15, 0.2, 0.25 M). ACE2 immobilization under favorable ambient conditions was characterized by minimum distance (short), settlement time (fast), interaction energy (substantial) and protein configuration (stable). ACE2 orientations proposed in 0.15M NaCl were respectively preferable to (90, 0, 0), (0, 0, 0) and (0, 270, 0), (180, 0, 0) and (0, 90, 0), (90, 0, 0) at pH 4.5, 6, 7, 9.5. ACE2 immobilization was further evaluated at pH 7 by optimizing NaCl concentration. Its proposed orientations of (i) (0, 270, 0), (ii) (0, 0, 0) and (90, 0, 0), and (iii) (0, 90, 0) and (90, 0, 0) were preferable in 0.05, 0.1 and 0.2 M NaCl, respectively. The great significance of cubic-orientation settlement mode provides tangible improvement for the microfabrication of biochips for rapid diagnosis of severe acute respiratory syndrome coronavirus II (SARS-CoV-2).

One of the strategies to reduce the contents of the low density lipoproteins (LDLs) in a blood is a hemoperfusion, in which case they are selectively retracted from plasma by an adsorber located outside the patient body. Recently, a photo-controllable smart surface was developed for this purpose characterised by high selectivity and reusability [C.Guo et al., ACS Applied Materials & Interfaces 2022, DOI:10.1021/acsami.2c07193]. We present a mesoscopic model for such a setup involving the azobenzene-containing polymer brush and the model LDL particles. The latter comprise an uniform spherical core covered by a shell of elongated particles representing phospholipids. The system is studied using the coarse-grained molecular dynamics simulation. We examined the dependences of the binding energy on both the length of polymer chains and the grafting density of a brush, and established optimal conditions for the adsorption. These are explained by a competition between the concentration of azobenzenes and phospholipids in the same spatial region, flexibility of polymer chains, and excluded volume effects.

Marburg virus disease (MVD) is a hemorrhagic fever and cause death up to 88% of people and is the same as Ebola virus, It is transmitted through skin contact or mucous membrane in the eyes, nose or mouth with blood or body fluids like urine, saliva sweat, feces and by object contaminated with body fluids. Despite these facts, yet there is no approved vaccine have been developed for the eradication of Marburg virus infections. Therefore, this study described a multi epitope-based peptide vaccine against Marburg virus viral protein 35, using several immunoinformatics tools combined with molecular docking studies. Utilizing Vaxijen 2.0 server, the V35 protein revealed to be antigenic with a score of 0.4316. Prediction of the T-cell and B-cell epitopes was then conducted. RTFDAFLGV epitope was found to be the most promising one with binding affinity to the highest numbers of MHC I alleles, a positive score in the Class I immunogenicity study and non-allergen. These results were further confirmed by the good interaction of RTFDAFLGV to the groove of HLA-A*02:01 with binding energy of -8.1 kcal/mole. Finally, the vaccine was cloned in silico to ensure its validity and efficiency of expression. To ensure its safety and immunogenic profile, in-vitro and in-vivo bioassays are recommended to confirm these findings.

Molecular dynamics(MD) simulations are carried out to characterize the mechanicalproperties and failure behavior of van der Waals heterostructures composed ofgraphene and hexagonal boron nitride(hBN) single layer sheets. The graphene–hBNand hBN–graphene–hBN heterostructures simulations are carried out under tensileand shear deformation. Accordingly, stress versus strain curves of each systemare plotted and various properties of heterostructures, namely elastic modulusand shear modulus as well as failure stress and failure strain, are evaluatedand compared with one another as well as with the pristine graphene and hBNsheets. Subsequently, the failure mechanism/characterization of each sheet in theheterostructures is described. Alternatively, the elastic and shear modulus of eachheterostructure are computed by means of rule of mixture(ROM) which are in goodagreement with results that are obtained from MD simulations.

Dysregulation of the Cyclin-dependent kinase 8 (CDK8) activity has been associated to many diseases including the colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But while human CDK family members are generally activated in two steps that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated to CycC while adopted an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than for the other members of CDK family. Through MD simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8 on the one hand, and the structural molecular basis of the protein-protein interaction between the two partners on the other hand. We found that CycC has a stabilizing effect on CDK8 and identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity, to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of the CycC may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

Molecular dynamics(MD) simulations are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals the solvent structure and preferential interaction sites (hot spots) on the protein surface. This information is largely transferable across all classes of protein ligands (from water to drugs) and can be used very effectively to understand ligand recognition and improve the predictive capability of well-established methods such as molecular docking. MD simulations for protein and drug or drug-like compounds are now being used but are still computationally expensive and can only be applied to specific cases. On the other hand, MDmix simulations can now be used in SBDD and we will describe the latest developments and implementations. We expect to see an increase in the application of these techniques to a plethora of protein targets to identify new drug candidates with the advent of new tools and faster computers.

The Novel Coronavirus (COVID-19) is a positive-sense single-stranded RNA ((+)ssRNA) virus. The COVID-19 Main Proteases play very important role in the propagation of the Novel Coronavirus (COVID-19). It has already killed more than 8000 people around the world and thousands of people are getting infected every day. Therefore, it is very important to identify a potential inhibitor against COVID-19 Main Proteases to inhibit the propagation of the Novel Coronavirus (COVID-19). We have applied a drug repurposing approach of computational methodology, depending on the synergy of molecular docking and virtual screening techniques, aimed to identify possible potent inhibitors against Novel Coronavirus (COVID-19) from FDA approved antiviral compounds and from the library of active phytochemicals. On the basis of recently resolved COVID-19 Main Protease crystal structure (PDB:6LU7), the library of 100 FDA approved antiviral compounds and 1000 active components of Indian Medicinal Plants extracted for screening against COVID-19 Main Protease. The compounds were further screened using Pyrex virtual screening tool and then best inhibitors, top 19 compounds optimally docked to the COVID-19 Main Protease structure to understand the participation of specific amino acids with inhibitors at active sites. Total 19 best compounds were identified after screening based on their highest binding affinity with respect to the other screened compounds. Out of 19, 6 best compounds were further screened based on their binding affinity and best ADME properties. Nelfinavir exhibited highest binding energy -8.4 kcal/mol and strong stability with the TRP207, ILE281, LEU282, PHE3, PHE291, GLN127, ARG4, GLY283, GLU288, LYS5, LYS137, TYR126, GLY138, TYR126, SER139 and VAL135 amino acid residues of COVID-19 Main Protease participating in the interaction at the binding pocket. In addition to Nelfinavir (-8.4), Rhein (-8.1), Withanolide D (-7.8), Withaferin A (-7.7), Enoxacin (-7.4), and Aloe-emodin (-7.4) also showed good binding affinity and best ADME properties. Our findings suggest that these compounds can be used as potential inhibitors against COVID-19 Main Protease, which could be helpful in inhibiting the propagation of the Novel Coronavirus (COVID-19). Moreover, further in vitro and in vivo validation of these findings would be very helpful to bring these inhibitors to next level study.

The process of viral integration into the host genome is an essential step of the HIV-1 life cycle. The viral Integrase (IN) enzyme catalyses integration. IN is an ideal therapeutic enzyme targeted by several drugs; raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG) and bictegravir (BIC) having been approved by the USA Food and Drug Administration (FDA). Due to high HIV-1 diversity, it is not well understood how specific naturally occurring polymorphisms (NOPs) in IN may affect the structure/function and binding affinity of Integrase Strand Transfer Inhibitors (INSTIs). In this study, we applied computational methods of molecular modelling and docking to analyse the effect of NOPs on the full-length IN structure and INSTI binding. We identified 16 NOPs within the Cameroonian derived CRF02_AG IN sequences and further identified 17 NOPs within HIV-1C South African sequences. The NOPs in the IN structures did not show any effect on INSTI binding. INSTIs displayed similar binding affinities to each IN structure. All INSTIs are clinically effective against diverse HIV-1 strains from INSTI treatment naïve populations. This study supports the use of second-generation INSTI DTG as part of first-line combination antiretroviral therapy (cART) regimens, due to DTG possessing a stronger genetic barrier to the emergence of drug resistance.

Some α-Pyrone derivatives isolated from Alternaria phragmospora fungus showed promising anti leukemic activities, while others were inactive. CRM1/XPO1 (chromosome region maintenance 1 protein, also called exportin1 or PO1 in humans) has been chosen as a target for antileukemic molecular docking study for those compounds to understand their modes of interaction and structure activity relationships. The results showed that two (2 and 4), out of six, natural α-Pyrone derivatives exhibited well-established interactions with the amino acids of the receptor, which was in agreement with the experimental anti-leukemic results of these compounds. Moreover, twenty hypothetical chemically modified α-Pyrone derivatives (7-27) have been designed. Compounds 7, 8, 22 and 24 showed more efficient docking properties than the previously considered natural compounds.

The β-amyloid cleaving enzyme 1 (BACE1) is regarded as an important target of drug design toward treatment of Alzheimer's disease (AD). In this study, three separate molecular dynamics (MD) simulations and calculations of binding free energies were carried out to comparatively probe identification mechanism of BACE1 on three inhibitors 60W, 954 and 60X. The analyses on MD trajectories indicate that the presence of three inhibitors influences structural stability, flexibility and internal dynamics of BACE1. Binding free energies calculated by using solvated interaction energy (SIE) and molecular mechanics generalized Born surface area (MM-GBSA) methods reveal that the hydrophobic interactions provide decisive forces for inhibitor-BACE1 binding. The calculations of residue-based free energy decomposition suggest that the sidechains of residues L91, D93, S96, V130, Q134, W137, F169 and I179 play key roles in inhibitor-BACE1 binding, which provides a direction for future drug design toward treatment of AD.

This work aims to investigate the effect of Pt concentration on crystal growth mechanism of Platinum-Palladium (Pt-Pd) binary alloy system during the annealing process starting from amorphous phase until some definite temperatures. The calculations have been performed by using molecular dynamic (MD) simulations. Interatomic interactions are described by on Sutton-Chen type Embedded Atom Potential Energy function. In order to understand the main structural properties at the stable and unstable phases, changes in RDF curves versus time have been analysed for different annealing temperatures. Crystalline type bonded pairs have been determined using MD calculations which is required for the computation of Avrami coefficients and for understanding crystal growth mechanism. The results demonstrate that the increase in concentration of Pt during annealing leads to migration of atoms in the crystal lattice points, elimination of dislocations and formation of perfect crystal structure.

Shut-in after fracturing is generally adopted for wells in shale oil reservoirs, and imbibition occurring in matrix nanopores has been proven as an effective way to improve recovery. In this research, the molecular dynamics (MD) simulation was used to investigate the effects of wettability and pressure on nanopores imbibition during shut-in for a typical shale reservoir Jimsar. The results indicate that the microscopic advancement mechanism of the imbibition front is the competitive adsorption between “interfacial water molecules” at the imbibition front and “adsorbed oil molecules” on the pore wall. The essence of spontaneous imbibition involves the adsorption and aggregation of water molecules onto the hydroxyl groups on the pore wall. The flow characteristics of shale oil suggest that the overall push of the injected water to the oil phase is the main reason for the displacement of adsorbed oil molecules. Thus, shale oil especially the heavy hydrocarbon component in the adsorbed layer tends to slip on the walls. However, the weak slip ability of heavy components on the wall surface is an important reason that restricts the displacement efficiency of shale oil during spontaneous imbibition. The effectiveness of spontaneous imbibition is strongly dependent on the hydrophilicity of the matrix pore's wall. The better hydrophilicity of the matrix pore's wall facilitates higher levels of adsorption and accumulation of water molecules on the pore wall and requires less time for “interfacial water molecules” to compete with adsorbed oil molecules. During the forced imbibition process, the pressure difference acts on both the bulk oil and the boundary adsorption oil, but mainly on the bulk oil, which leads to the occurrence of wetting hysteresis. Meanwhile, shale oil still existing in the pore always maintains a good stratified adsorption structure. Because of the wetting hysteresis phenomenon, as the pressure difference increases, the imbibition effect gradually increases, but the actual capillary pressure gradually decreases and there is a loss in the imbibition velocity relative to the theoretical value. Simultaneously, the decline in hydrophilicity further weakens the synergistic effect of pressure difference because of the more pronounced wetting hysteresis. Thus, selecting an appropriate well pressure enables cost savings and maximizes the utilization of the formation's natural power for EOR.

Chlorotoxin (CTX) is a 36–amino acid peptide with 8 Cys residues that forms four Cys-Cys bonds. It has high affinity for the glioma-specific chloride channel and matrix metalloprotease-2. Structural and binding properties of CTX analogs with various Cys residue substitutions with L-a-aminobutyric acid (Abu) have been previously reported. Using 4.2 ìs molecular dynamics, we compared the conformational and essential space sampling of CTX and analogs [Abu/Ser^2,19]CTX, [Abu/Ser^5,28]CTX, [Abu/Ser^16,33]CTX, [Abu/Ser^20,35]CTX, and [Abu/Ser^{2,5,16,19,20,28,33,35}]CTX. The native and substituted peptides maintained a high degree of a-helix propensity from residues 8 through 21, with the exception of [Ser^5,28]CTX and [Abu^16,33]CTX. In agreement with previous circular dichroism spectropolarimetry results, the C-terminal b-sheet content varied less from residues 25 through 29 and 32 through 36 and was well conserved in all analogs, except: [Abu^16,33]CTX, [Ser^20,35]CTX, [Abu^{2,5,16,19,20,28,33,35}]CTX, and [Ser^{2,5,16,19,20,28,33,35}]CTX. The Cys¹⁶-Cys³³ and Cys²⁰-Cys³⁵ Cys-Cys bonds appear to be required to maintain the ab-motif of CTX. Their selective substitution with Ser^16,33 however, may mitigate the destabilizing effect of Cys¹⁶-Cys³³ substitution by the formation of an inter residue H-bond from OgH of Ser¹⁶ to OgH of Ser³³ bridged by a water molecule. All peptides shared considerable sampled conformational space, which explains the retained receptor binding of the nonnative analogs.

We have synthesized quinoxaline analogs (1-25), characterized by 1HNMR and HREI-MS and evaluated for thymidine phosphorylase inhibition. Among the series, nineteen analogs showed better inhibition when compared with the standard inhibitor 7-Deazaxanthine (IC50 = 38.68 ± 4.42 µM). The most potent analog among the series is analog 25 with IC50 value 3.20 ± 0.10 µM. Sixteen analogs 1, 2, 3, 4, 5, 6, 7, 12, 13, 14, 15, 16, 17, 18, 21and 24 showed outstanding inhibition which is many folds better than the standard 7-Deazaxanthine. Two analogs 8 and 9 showed moderate inhibition. A structure- activity relationship has been established mainly based upon the substitution pattern on the phenyl ring. The binding interactions of the active compounds were confirmed through molecular docking studies.

Nitrile butadiene rubber (NBR) and its various composites are extensively studied as matrix materials for oil-free lubricated mechanical friction surfaces. While numerous macroscopic friction experiments can compare the frictional performance of different NBR composites, the complex material preparation and low experimental efficiency pose challenges. Nanoscale molecular dynamics (MD) simulations can help develop materials with improved friction properties, but they cannot directly provide the friction coefficients of actual macroscopic friction surfaces. Therefore, it is important to integrate the advantages of macroscopic and nanoscale friction studies and perform a synergistic analysis to modify the friction properties of composite materials. In this study, a multi-scale approach is proposed to simulate the frictional characteristics of carbon nanotube (CNT)-reinforced NBR by combining the MD friction simulation， micromechanical bridging model, and macroscopic finite element analysis (FEA) methods. The results of the multi-scale friction simulation of copper (Cu)-CNT/NBR composites show that the addition of CNTs significantly improves the frictional properties of NBR, and the extent of the improvement is related to the mass fraction of CNTs. As the mass fraction of CNTs increases (0%, 1.25%, 2.5%, 5%), the coefficient of friction decreases from 0.50 to 0.38. The results are validated by ring-block friction experiments at the same scale as the simulations.

The analysis of high-temperature physicochemical properties of theK₃AlF₆-Na₃AlF₆-AlF₃ molten salt system is crucial for practical production of electrolytic aluminum. In this paper, the physicochemical properties of the K₃AlF₆-Na₃AlF₆-AlF₃ molten salt electrolyte system at 1173 K and standard atmospheric pressure were simulated using molecular dynamics calculations. The effects of Zr、B、C、W、Ti、Hf、Nb、and Ta on the radial distribution function, coordination number, viscosity and conductivity of the electrolyte system are discussed in detail. The simulation results show that the coordination number between Al-F and the conductivity is decreasing as the content of B²- increases. And the coordination number between Al-F and the viscosity is decreasing as the content of Zr⁴⁺ increases. With the addition of impurity elements such as C, W, Ti, Hf, Nb, and Ta, the data show that C has no significant effect on this electrolyte system, while the presence of W will decrease the coordination number between Al-F in the system. The presence of Ti, Hf, Nb, and Ta may intensify the decomposition reaction between one of the Al-F ligands, which increases the coordination number between Al-F and the number of ions in the electrolyte. This work provides theoretical support for the subsequent study of inert anodes containing Zr, B, Ti, Hf, Nb, and Ta.

A sedentary lifestyle associated with unregulated diets rich in high-calorie foods have contributed to the great prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) latterly, with up to 60% in high-risk population and 25% in the general population. The absence of specific pharmacological strategies for this syndrome represents one of the major problems in the management of MASLD patients. Lifestyle interventions and adherence to a healthy diet are the main cornerstones of current therapies. The identification of nutraceuticals useful in the treatment of MASLD appears to be one of the most promising strategies for the development of new effective and safe treatments for this disease. The onion, one of the most widely studied foods in the field of nutraceuticals, serves as an inexhaustible reservoir of potent compounds with various beneficial effects. The following preliminary study analyses, mediating in silico studies, the iteration of a library of typical onion compounds with 3-hydroxy-3-methylglutaryl-coenzyme A reductase, Liver receptors X α and β as well as Peroxisome proliferator-activated receptors α and γ. In this study fort the first time promising smart molecules from the onion that could have a beneficial action in MASLD patients were identified.

Prototype of a family of at least nine members, c-src tyrosine kinase is a therapeutically interesting target, because its inhibition might be of interest not only in a number of malignancies, but also in a diverse array of conditions, from neurodegenerative pathologies to certain viral infections. Computational methods in drug discovery are considerably cheaper than conventional methods and offer opportunities of screening very large numbers of compounds in conditions that would be simply impossible within the wet lab experimental settings. We have explored the use of global QSAR models and molecular ligand docking in the discovery of new c-src tyrosine kinase inhibitors. Using a data set of 1038 compounds from ChEMBL and 19 blocks of molecular descriptors, we have developed over 200 QSAR classification models, based on six machine learning algorithms and 17 feature selection methods. We have selected 49 with reasonably good performance (positive predictive value and balanced accuracy higher than 70% in nested cross validation) and the models were assembled by stacking with a simple majority vote and used for the virtual screening of over the “named” ZINC data set (over 100,000 compounds). 744 compounds were predicted by at least 50% of the QSAR models as active, 147 compounds were within the applicability domain and predicted by at least 75% of the models to be active. The latter 147 compounds were submitted to molecular ligand docking using Vina and Ledock, and a number of 90 were predicted to be active based on the binding energy. External data from CHEMBL and PUBCHEM confirmed that at least 7.83% (in the case of QSAR) or 6.67% (in the case of integrated QSAR and molecular docking) of the compounds are active on the c-src target.

Periodontitis is a disease that originates from gingival tissue, and if left untreated, can cause inflammation to spread to deeper tissues, altering bone homeostasis, and even leading to tooth loss. When the bacteria in plaque reach sufficient numbers, the immune system responds by activating immune cells that will produce cytokines, including interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). These immune signaling molecules will coordinate the inflammatory responses. IL-1 binds to the IL-1 receptor (IL-1R) on the surface of target cells, initiating an inflammatory response by activating intracellular signalling pathways. Inhibition of IL-1R can prevent the interaction of IL-1 with this receptor, thereby halting the activation of the inflammatory pathway. By substituting this connection with active anti-inflammatory substances, it is possible to prevent the contact between IL-1 and IL-1R. The licorice plant, Glycyrrhiza glabra, includes eight types of flavonoids with significant anti-inflammatory potential, namely isoliquiritigenin, glyzaglabrin, prunetin, shinpterocarpin, licochalcone A, glabridin, glisoflavone, and isoangustone A. This study aims to assess the potential of such flavonoids as candidates for periodontitis treatment through molecular docking, using AutoDock Tools v.1.5.6. All tested compounds showed highly stable bonds to IL-1R, with a binding affinity values below -7 kcal/mol. Van der Waals forces, hydrogen bonds, and hydrophobic bonds all contribute to the stability of these interactions. Among the eight tested compounds, glisoflavone, which has a Ki value of 90.89 nM and a ΔG value of -9.61 kcal/mol, has the highest binding stability to IL-1R.

ND1 subunit possesses the majority of the inhibitor binding domain of the human MRC-I. This is an attractive target for the search for new inhibitors that seek mitochondrial dysfunction. It is known, from in vitro experiments, some metabolites from Annona muricata called acetogenins have important biological activities such as anticancer, antiparasitic, and insecticide. Previous studies propose an inhibitory activity of bovine MRC-I by bis-THF acetogenins such as annocatacin B, however, there are few studies on its inhibitory effect on human MRC-I. In this work, we evaluate the molecular and energetic affinity of the annocatacin B molecule with the human ND1 subunit in order to elucidate its potential capacity to be a good inhibitor of this subunit. For this purpose, QM optimizations, MD simulations and MM/PBSA analysis were performed. As a control to compare our outcomes, the molecule rotenone, which is a known MRC-I inhibitor, was chosen. Our results show that annocatacin B has a greater affinity for the ND1 structure, its size and folding were probably the main characteristics that contributed to stabilize the molecular complex. Furthermore, the MM/PBSA calculations showed a 35% stronger BFE compared to the rotenone complex. Detailed analysis of the BFE shows that the aliphatic chains of annocatacin B play a key role in molecular coupling by distributing favorable interactions throughout the major part of the ND1 structure. These results are consistent with experimental studies that mention that acetogenins may be good inhibitors of MRC-I.

Small molecule modulators of neurotensin receptor 1 (NTSR1), a class A G protein-coupled receptor (GPCR), has been emerging as promising therapeutics for psychiatric disorders and cancer. Interestingly, a chemical group substitution of NTSR1 modulators can launch different downstream regulation, highlighting the significance of deciphering the internal fine-tuning mechanism. Here, we conducted synergistic application of Gaussian accelerated molecular dynamics simulation, conventional molecular dynamics simulation, and Markov state models (MSM) to investigate the underpinning mechanism of ‘driver chemical groups’ of modulators triggering inverse signaling. The result indicated that the flexibility of leucine moiety in NTSR1 agonists contributes to the inward displacement of TM7 through a loosely coupled allosteric pathway, while the rigidity of adamantane moiety in NTSR1 antagonists leads to unfavorable downward transduction of agonistic signaling. Furthermore, we found that R3226.54, Y3196.51, F3537.42, R1483.32, S3567.45 and S3577.46 may play a key role in inducing the activation of NTSR1. Together, our findings not only highlight the ingenious signal transduction within class A GPCRs, but also lay a foundation for the development of targeted drugs harboring different regulatory function of NTSR1.

In the search of potent α-amylase inhibitors, we have synthesized seventeen derivatives of 2-mercaptobenzimidazole bearing sulfonamide (1-17) and evaluated for their α-amylase inhibitory potential. All compounds display a variable degree of α-amylase activity having IC50 values ranging between 0.90 ± 0.05 to 11.20 ± 0.30 µM when compared with the standard drug acarbose having IC50 value 1.70 ± 0.10 µM. Compound 1, 2, 11, 12 and 14 having IC50 values 1.40 ± 0.10, 1.30 ± 0.05, 0.90 ± 0.05, 1.60 ± 0.05 and 1.60 ± 0.10 µM respectively were found many folds better than the standard drug acarbose. The remaining analogs showed good inhibitory potentials. All the synthesized compounds were characterized by HREI-MS, 1H and 13C-NMR. Structure activity relationship (SAR) has been recognized for all newly synthesized analogs. Through molecular docking study, binding mode of active analogs with α-amylase enzyme was confirmed.

New class of triazinoindole bearing thiosemicarbazide (1-25) was synthesized and evaluated for α-glucosidase inhibitory potential. All synthesized analogues exhibited excellent inhibitory potential having IC50 values ranging from 1.30 ± 0.01 to 35.80 ± 0.80 µM when compared with the standard acarbose having IC50 value 38.60 ± 0.20 µM. Among series the analogues 1 and 23 was found the most potent having IC50 values 1.30 ± 0.05 and 1.30 ± 0.01 µM respectively. Structure activity relationship (SAR) was mainly based upon by bring about difference of substituents on phenyl rings. To confirm the binding interactions, molecular docking study was performed. Synthesized analogues were characterized through HREI-MS, 1H and 13C-NMR analysis.

Nuclear export of viral mRNAs, is an essential step in the HIV replication cycle. This role is played by a small regulatory protein of HIV-1 called Rev.The N-terminal region of Rev contains an arginine-rich sequence. The arginine-rich motif (ARM) is located between amino acids 38-50 and forms an alpha-helical secondary structure. Expression of the structural proteins of human immunodeficiency virus type 1 requires the direct interaction of multiple copies of the viral Rev protein with its highly structured RNA target sequence, the Rev Response element (RRE). The major viral proteins are not produced if this transport of RNA is stopped. Therefore, knowledge of Rev structure is essential for understanding of its cooperative binding to the RRE, for understanding the mechanism of HIV infection and for the development of antiviral drugs that interfere with Rev’s essential functions and for acknowledgment of good candidate drugs for treatment of AIDS. To understand how REV interact with RRE element of HIV-RNA and its formation of oligomeric complex it is better to characterize the domain wise structure of REV with regard in function of each domain. Due to lack of structural data on Rev no single compound is reported as inhibitor of REV expect antiviral drugs. Identification of a high-affinity RNA-binding site for the human immunodeficiency virus type 1 Rev Protein is much more important. The ARM is a highly specific sequence which allows for the multimerization of Rev and also binding of REV with RNA. Here we are first time exploring the structural characteristics of REV protein both in free form and in complex with RNA at domain function level especially explore the role of ARM motif in REV HIV-1 protein as RNA binding sites by molecular dynamics (MD) simulation and homology modeling studies. Results indicate that the arginine-rich motif (ARM) is crucial in stability of this complex. The residues ARG38, 39, 41, 43, 44, 48, 50, and ASN40 are most interacting with nucleobases of RRE in Crystal structure of Rev and Rev-response-element RNA complex. Our study plays a major role in elaboration of binding of RNA with REV and pave the way for further investigation for therapeutically agent for HIV.

We research the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional-graphene(Graphene33). Their curvatures decrease sequentially, and all of CNT are single-walled carbon nanotubes. We have observed that as the curvature of CBNs decreases, the adsorption effect of 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the π-π interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and “Benzene-like” Pro also have a strong adsorption effect with carbon-based nanoparticles.

Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.

The molecular dynamics simulation has been used to investigate the structural and transport properties of (Ba_0.5-xSr_x)La_0.5InO_3-δ (x=0, 0.1, 0.2) oxygen-ion conductor. The previous studies reported that the ionic conductivity of Ba-doped LaInO3 decreases because Ba dopant forms narrow oxygen path in the lattice, which could hinder the diffusion of oxygen ion. In this study, we reveal the mechanism to improve the ionic conductivity by Ba and Sr co-doping on La site in LaInO3 perovskite oxide. The results show that the ionic conductivity of (Ba_0.5-xSr_x)La_0.5InO_3-δ increases with increasing numbers of Sr ions, which oxygen diffusion paths including Sr ion have larger critical radius than Ba ions. The RDF calculations showed the heights of peak in composition including Sr ions is lower and broaden, so oxygen ions moved easily into other oxygen sites.

Rotavirus (RV) replicates within viroplasms, membrane-less electron-dense globular cytosolic inclusions with liquid-liquid phase properties. In these structures occur the virus transcription, replication, and packaging of the virus genome in newly assembled double-layered particles. The viroplasms are composed of virus proteins (NSP2, NSP5, NSP4, VP1, VP2, VP3, and VP6), single and double-stranded virus RNAs, and host components such as microtubules, perilipin-1 and chaperonins. The formation, coalescence, maintenance, and perinuclear localization of viroplasms rely on their association with the cytoskeleton. A stabilized microtubule network involving microtubules and kinesin Eg5 and dynein molecular motors is associated with NSP5, NSP2, and VP2, facilitating dynamic processes such as viroplasm coalescence and perinuclear localization. Key post-translation modifications, particularly phosphorylation events of RV proteins NSP5 and NSP2, play pivotal roles in orchestrating these interactions. Actin filaments also contribute, triggering the formation of the viroplasms through the association of soluble cytosolic VP4 with actin and the molecular motor myosin. This review explores the evolving understanding of RV replication, emphasizing the host requirements essential for viroplasm formation and highlighting their dynamic interplay within the host cell.

Drug repurposing, the practice of utilizing existing drugs for novel clinical indications, has tremendous potential for improving human health outcomes and increasing therapeutic development efficiency. The goal of multidisease multitarget drug repurposing, also known as shotgun drug repurposing, is to develop platforms that assess the therapeutic potential of each existing drug for every clinical indication. Our Computational Analysis of Novel Drug Opportunities (CANDO) platform for shotgun multitarget repurposing implements several pipelines via large scale modelling and simulation of interactions between comprehensive libraries of drugs/compounds and protein structures. In these pipelines, each drug is described by an interaction signature that is then compared to all other signatures that are then sorted and ranked based on similarity. Pipelines within the platform are benchmarked based on their ability to recover known drugs for all indications in our library, and predictions are generated based on the hypothesis that (novel) drugs with similar signatures may be repurposed for the same indication(s). The drug-protein interactions in the platform used to create the drug-proteome signatures may be determined by any screening or docking method but the primary approach used thus far has been an in house similarity docking protocol. In this study, we calculated drug-proteome interaction signatures using the publicly available molecular docking method Autodock Vina and created hybrid decision tree pipelines that combined our original bio- and cheminformatic approach with the goal of assessing and benchmarking their drug repurposing capabilities and performance. The hybrid decision tree pipeline outperformed the corresponding two docking-based pipelines it was synthesized from, yielding an average indication accuracy of 13.3% at the top10 cutoff (the most stringent), relative to 10.9% and 7.1% for its constituent pipelines, and a random control accuracy of 2.2%. We demonstrate that docking based virtual screening pipelines have unique performance characteristics and that the CANDO shotgun repurposing paradigm is not dependent on a specific docking method. Our results also provide further evidence that multiple CANDO pipelines can be synthesized to enhance drug repurposing predictive capability relative to their constituent pipelines. Overall, this study indicates that pipelines consisting of varied docking based signature generation methods can capture unique and useful signal for accurate comparison of drug-proteome interaction signatures, leading to improvements in the benchmarking and predictive performance of the CANDO shotgun drug repurposing platform.

The current study describes the preparation of chitosan nanoparticles (CNPs) using hydroxychloroquine (HCQ), widely used in traditional medicine due to its diverse phar-macological and medicinal uses. This work aims to combine the HCQ drug with CS NPs to generate a novel nanocomposite with improved characteristics and bioavailability. HCQ@CS NPs is roughly shaped like roadways and has a smooth surface with an average size of 159.3±7.1 nm, a PdI of 0.224±0.101, and a zeta potential of +46.6±0.8 mV. To aid in the development of pharmaceutical systems for use in cancer therapy, the binding mech-anism and affinity of the interaction between HCQ and HCQ@CS NPs and BSA were ex-amined using stopped-flow, other spectroscopic approaches, supplemented by molecular docking analysis. HCQ and HCQ@CS NPs binding with BSA is driven by a ground-state complex formation that may be accompanied by a non-radiative energy transfer process, and binding constants indicated that HCQ@CS NPs-BSA was more stable than HCQ-BSA. The stopped-flow analysis demonstrated that, in addition to increasing BSA affinity, the nano formulation HCQ@CS NPS changes the binding process and may open up new routes for interaction. Docking experiments verified the development of the HCQ-BSA complex, with HCQ binding to the site I on the BSA structure, primarily with the amino acids Thr 578, Gln 579, Gln 525, Tyr 400, and Asn 404. Furthermore, the nano-formulation HCQ@CS NPS not only increased cytotoxicity against the A549 lung cancer cell line (IC50 = 28.57±1.72 g/ml) compared to HCQ (102.21±0.67) g/ml), but also exhibited higher anti-bacterial activity against both Gram-positive and Gram-negative bacteria when compared to HCQ and chloramphenicol which in agreement with the binding constants. The nano formulation developed in this study may offer a viable therapy option for A549 lung cancer.

Introduction: Oral candidiasis is an opportunistic fungal infection, often caused by Candida albicans. One of the virulence factors of C. albicans is sterol 14a-demethylase or CYP51. Compounds of anthocyanins (ternatin, cyanin) and flavonoids (rutin, isoquercetin, kaempferol, myricetin, limocitrin) from the extract of the Clitoria ternatea (butterfly pea) plant are believed to have potential to inhibit the CYP51 virulence factor of C. albicans to suppress oral candidiasis. The purpose of this research was to investigate the interaction between the ligands of anthocyanins and flavonoids from C. ternatea (butterfly pea) with CYP51. Methods: The in silico study applied molecular docking to examine the molecular interactions (binding affinity) between the anthocyanin and flavonoid ligands of interest from C. ternatea and the CYP51 receptor of C. albicans. Results: Predicted interactions exist between the ligands of anthocyanins (ternatin, cyanin) and flavonoids (rutin, isoquercetin, kaempferol, myricetin, limocitrin) from C. ternatea and the CYP51 receptor of C. albicans. Conclusion: C. ternatea has the potential to provide anti-fungal agents that can inhibit or slow down the occurrence of oral candidiasis, as indicated by in silico studies. However, it is important to conduct additional research regarding the properties of the plant to determine the unknown aspects of its effects to the human body.

This work is devoted to consideration and analysis of the application of molecular dynamics simulation (MDS) methods to the study of nanosized polymer polyvinylidene fluoride (PVDF) thin ferroelectric films (two-dimensional ferroelectrics) and their composites with graphene layers: 1) to study and calculations of the polarization switching time depending on the electric field and PVDF film thickness; 2) to study and calculations of the polarization switching time depending changes of the PVDF on PVDF-TrFE film; 3) to study the polarization switching time in PVDF under influence of graphene layers. All calculations at each MDS step were carried out using quantum semi-empirical methods PM3. A comparison and analysis of the results of these calculations and the kinetics of polarization switching within the framework of the Landau-Ginzburg-Devonshire theory for homogeneous switching in ferroelectric polymer films is carried out. The study of the composite heterostructures of the “graphene-PVDF” type and calculations of their polarization switching times were presented too. It is shown that replacing PVDF with PVDF-TrFE significantly changes the polarization switching times in these thin polymer films, and that introducing various graphene layers into the PVDF layered structure leads to both an increase and a decrease in the polarization switching time. Here everything also depends on the position and displacement of the ferroelectric coercive field depending on the system damping parameters.

In the course of SARS-CoV-2 infection, the 3CL or nsp5 protease plays a pivotal role as the most important viral protease required for the maturation of viral proteins during host infection. Herein, we simulated for 500 ns 3CLproWT, 3CLproH41A, , 3CLproBeta, and 3CLproOmicron, in complex with the substrates nsp 4|5 and nsp 5|6. Our results show that mutations in the 3CLpro present in the SARS-CoV-2 variant of concerns (VOCs) did not lead to significant conformational changes or changes in substrate binding affinities. However, significantly high cleavage rates for the boundary between nsp4 and nsp5 were obtained for 3CLproBeta and 3CLproOmicron and may play a key role in the viral replication and virus fitness gain. Our molecular dynamics data suggest that the cleavage rate of nsp4|5 may be related to the increased amount of viral load observed for these VOCs, releasing more nsp4 than other non-structural proteins. Based on our hydrogen bonding analyses, we also discovered that Gly143 and Glu166 are key residues in substrate recognition, suggesting that these residues may be incorporated as pharmacophoric centers for Beta and Omicron variants in drug design. Our results suggest that Gly143 and Glu166 are essential residues to interact with Gln6 of the different substrates and, therefore, are potential broad-spectrum pharmacophoric centers of SARS-CoV-2 3CLpro.

Nanoporous membranes promise energy-efficient water desalination. Hexagonal boron nitride (h-BN), like graphene, exhibits outstanding physical and chemical properties, making it a promising candidate for water treatment. We employed Car–Parrinello molecular dynamics simulations to establish accurate modeling of Na+ and Cl- permeation through hydrogen passivated nanopores in graphene and h-BN membranes. In these complex systems the classical potentials cannot properly account for the physics at play. We demonstrate that ion separation works well for the h-BN by imposing a barrier of 0.13 eV and 0.24 eV for Na+ and Cl- permeation respectively, compared to the graphene where the Cl- ion faces a negative barrier of 0.68 eV and is prone toward blockade and Na+ permeation is associated with a slightly negative barrier of 0.03 eV. From the change in the solvation shell, we get the following trend: Na/h-BN > Na/G > Cl/G > Cl/h-BN. We argue that the trend in the permeation barrier changes to Cl-h-BN > Na-h-BN > Na-G > Cl-G due to a combination of several interactions, including the distortion of the water network induced by the ions, the ion-water interaction, and the ion-nanopore interaction. Overall, the desalination performance of h-BN surpasses that of their graphene counterparts.

In this paper, the nanoscale dissipative mechanisms of a Cu pad in a Ball Grid Array (BGA) packaging structure during isothermal ageing and uniaxial tension were investigated by the molecular dynamics (MD) method and experiments. From the result of the isothermal ageing test, a nonuniform consumption of Cu and large amount of Kirkendall voids were observed at the interface of Cu and Cu₃Sn. To study the effect of pressure and orientation on this phenomenon, MD simulations were conducted on four types of Cu-Cu₃Sn interface structures with different orientations of Cu. By comparing the diffusion coefficients of atoms in those cases, it was found that the tensile stress would inhibit the diffusion of atoms, whereas compressive stress would accelerate it, and this would be more significant under a larger magnitude of stress and temperature. Note that, in the model with the (101) surface Cu at the interface, both Cu and Cu₃Sn have a higher diffusion coefficient compared with the model with (001) surface Cu. Thus, the orientation of Cu will also contribute to the uniform consumption of the pad. Uniaxial tension simulation combined with DXA and CSP analyses on those models also shows the model with (001) surface Cu has a greater mechanical reliability in our simulations and related experiments.

Background: COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. Associated with its infection are cough, fever and respiratory problems causes more than 15% mortality worldwide. It is caused by a positive, single stranded RNA virus from the enveloped coronaviruse family. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction.Objectives: The present in silico study was designed to evaluate the effect of Eucalyptol (1,8 cineole), a essential oil component from eucalyptus oil, on Mpro by docking study.Methods: In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.Results: The calculated parameters such as RMSD, binding energy, and binding site similarity indicated effective binding of eucalyptol to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/eucalyptol complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions.Conclusions: Therefore, eucalyptol may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.

A derivative series of 3,4-dimethoxy-β-nitrostyrene were synthesized and identified including new compound 6. The effect of antimicrobial activity of 3,4-alkyloxy modification of β-nitrostyrene was investigated. A molecular docking was also performed to obtain information about their interactions with Protein Tyrosine Phosphatase 1B (PTP1B). PTP1B containing cysteine 215 and arginine 221 as essential active residues plays a key role in signaling pathways that regulate various cell functions of microorganisms, which also act as negative regulator in signaling pathways of insulin that are involved in type 2 diabetes and other metabolic diseases. Compound 5 and 6 were the most potent as fragment of PTP1B inhibitor based on molecular docking, but compound 5 was more effective against Candida albicans. These compounds interact with serine 216 and arginine 221 residues. However, further research is needed to investigate their potential medicinal use.

The spread of the global COVID-19 pandemic, the lack of specific treatment and the urgent situation requires use of all resources to remedy this scourge. In the present study, using molecular docking, we identify new probable inhibitors of COVID-19 by molecules from Nigella sativa L, which is highly reputed healing herb in North African societies and both Islamic and Christian traditions. The discovery of the M^pro protease structure in COVID-19 provides a great opportunity to identify potential drug candidates for treatment. Focusing on the main proteases in CoVs (3CL^pro/M^pro) (PDB ID 6LU7 and 2GTB); docking of compounds from Nigella Sativa and drugs under clinical test was performed using Molecular Operating Environment software (MOE). Nigelledine docked into 6LU7 active site gives energy complex about -6.29734373 Kcal/mol which is close to the energy score given by chloroquine (-6.2930522 Kcal/mol) and better than energy score given by hydroxychloroquine (-5.57386112 Kcal/mol) and favipiravir (-4.23310471 kcal/mol). Docking into 2GTB active site showed that α- Hederin gives energy score about-6.50204802 kcal/mol whcih is better energy score given by chloroquine (-6.20844936 kcal/mol), hydroxychloroquine (-5.51465893 kcal/mol)) and favipiravir (-4.12183571kcal/mol). Nigellidine and α- Hederin appeared to have the best potential to act as COVID-19 treatment. Further, researches are necessary to testify medicinal use of identified and to encourage preventive use of Nigella Sativa against coronavirus infection.

In its prefusion state, the SARS-CoV-2 Spike protein (similarly to other class I viral fusion proteins) is metastable, which is considered to be an important feature for optimizing or regulating their functions. After the binding process of its S1 subunit (S1) with the ACE2, the Spike protein (S) suffers a dramatic conformational change where S1 splits from the S2 subunit, which then penetrates the membrane of the host cell, promoting the fusion of the viral and cell membranes. This results in the infection of the host cell. In a previous work, we showed -using large scale molecular dynamics simulations- that the application of external electric fields (EF) induces drastic changes and damage in the receptor-binding domain (RBD) of the wild type Spike protein, as well of the Alpha, Beta and Gamma variants, leaving a structure which cannot be recognized any more by ACE2. In this work, we first extend the study to the Delta and Omicron variants and confirm the high sensitivity and extreme vulnerability of S to moderate EF (as weak as 104 V m-1), but, more importantly, we also show that, in contrast, the postfusion state of the spike protein does not suffer structural damage even if electric field intensities four orders of magnitude higher are applied. These results provide a solid scientific basis to confirm the prefusion state metastability roots of the SARS-CoV-2 Spike protein susceptibility to be damaged by EF. After the virus docks to the ACE2 receptor, the stable and robust postfusion conformation develops, which exhibits a similar resistance to EF (damage threshold higher than 108 V m-1) like most globular proteins.

Cervical cancer is a significant global health concern, with human papillomavirus (HPV) infection being a crucial risk factor. Photodynamic therapy (PDT) is an attractive, minimally invasive treatment for HPV-related cervical lesions, which uses photosensitizers and light to selectively de-stroy abnormal cells. We aim to provide an overview of the various sorts of dyes that are utilized in PDT for decreasing the incidence and mortality of cervical cancer. Besides, the article discusses ongoing clinical trials for PDT in low-grade squamous intraepithelial neoplasia (LSIL) and high-grade squamous intraepithelial lesions (HSIL), as well as preclinical approaches for PDT in cervical cancer using various dyes. Moreover, it highlights potential dyes for PDT, examine them in in-silico condition, their pros and cons and also the solutions for enhancing their anticancer com-patibility. We also display that PDT is a promising therapeutic strategy for the diagnosis and treatment of HPV-associated cervical lesions. Moreover, it shows that using different classes of dyes improves the anticancer effects of PDT. Finally, among all dyes which are used in PDT, Fullerene demonstrated high tendency to over expressed receptors in cervical cancer cells and seems to be a proper candidate for be used in PDT more than before, but further research is necessary to assess its long-term efficacy and safety.

Among bryophytes, the Plagiochila genus represents a large group of leafy liverworts, with over 500 species. Plagiochilins A-to-X are sesquiterpenoids isolated from Plagiochila species. The lead compound plagiochilin A (Plg-A), endowed with anticancer and anti-parasitic properties, has been characterized as a potent mitosis inhibitor, acting selectively at the late stage of cytokinesis termed abscission. The compound perturbs the dynamic of microtubules, blocking cell cycle progression and triggering the death of malignant cells. Based on the compound mechanism of action and the analogy with other natural products bearing a dihydro-pyrone moiety, we postulated that Plg-A could bind to the pironetin site of α-tubulin. A molecular docking analysis has been performed to compare binding of all 24 plagiochilins to α-tubulin and to establish structure-binding relationships. The identification of Plg-E and Plg-G as the best binders in the series pointed out to the importance of the C13-OH or C=O group for α-tubulin recognition. This observation led to the testing of the natural product ester plagiochilin A-15-yl n-octanoate and the corresponding alcohol (Plg-OH), both identified as robust α-tubulin binders. The study provides a rational to explain potentially the mechanism of action of Plg-A and to guide the design of new derivatives.

Atomic force microscopes are used, beside their principal function as surface imaging tools, in surface manipulation and measurement of interfacial properties. In particular, they can be modified to measure lateral friction forces that occur during the sliding of the tip against the underlying substrate. However, the shape, size, and deformation of the tips profoundly affect the measurements in a manner that is difficult to predict. In this work, we investigate the contribution of these effect to the magnitude of the lateral forces during sliding. The surface substrate is chosen to be few-layer AB-stacked graphene surface whereas the tip is initially constructed from face-centered cubic gold. In order to separate the effect of deformation from shape, rigid tips of three different shapes were considered first, namely a cone, a pyramid and a hemisphere. The shape was seen to dictate all aspects of the interface during sliding, from temperature dependence to stick-slip behavior. Deformation was investigated next by comparing a rigid hemispherical tip to one of identical shape and size but with all but the top three layers of atoms free to move. The deformation, as also verified by an indentation analysis, occurs by means of the lower layers collapsing on the upper ones, thereby increasing the contact area. This collapse mitigates the friction force and decreases it with respect to the rigid tip for the same vertical distance. Finally, the size effect is studied by means of calculating the friction forces for a much larger hemispherical tip whose atoms are free to move. In this case, the deformation is found to be much smaller but the stick-slip behavior is much more clearly seen.

This study employs molecular docking experiments to investigate the binding interactions of Hypericin with key proteins implicated in Alzheimer's disease (AD). Hypericin demonstrated a significant binding energy of -10.1 kcal/mol with ABAD (3-hydroxyacyl-CoA dehydrogenase type II). The analysis revealed multiple binding interactions, including hydrogen bonds with arginine 6, serine 7, and glutamic acid 140, as well as hydrophobic bonds involving leucine 11, aspartic acid 142, and aspartic acid 86. These findings illuminate the intricate molecular interactions between Hypericin and ABAD, suggesting its potential as a lead compound for further therapeutic development in the context of Alzheimer's disease. Additionally, a parallel docking investigation was conducted for Beta-secretase 1 (BACE1), a protein pivotal in the generation of beta-amyloid peptides—a hallmark of Alzheimer's disease. Inhibiting BACE1 activity is considered a promising therapeutic strategy for AD. Computational analyses suggest that Hypericin may serve as a potential inhibitor of BACE1. Molecular Docking results reveal a robust binding affinity between Hypericin and BACE1, supported by a significant binding energy score of -10.3 kcal/mol. Notably, both ABAD and BACE1 exhibit high binding affinity with Hypericin. This theoretical exploration provides an initial understanding of the intricate molecular pathways involved in Alzheimer's disease and proposes Hypericin as a potential therapeutic compound for mitigating its progression.

Based on screening in computational biology and biological in vitro assays, five natural products isolated from extracts of the herbal medicine toad skin, such as cinobufagin (CBFi), bufalin (BFi), arenobufagin (ABFi), telocinobufagin (TBFi), bufotalin (BFTi), were subjected to molecular docking calculations with the use of SARS-CoV-2 main protease (PDB 6LU7 and 7BTF) and top-scoring ligand-receptor complexes were obtained. The results showed that the binding energy of ABFi to the 3CL protein was -17.044kcal/mol, which was higher than CBFi and TBFi. However, the binding energy of ABFi to the RdRp protease was -23.250 kcal/mol, which was much lower than that of CBFi and TBFi, EVEN lower than that of ABFi to the 3CL protein. ABFi also has polar interactions with amino acids such as Glu811, Ser814, Ser681 and Thr680 of RdRp enzyme. The results revealed that ABFi had a moderate inhibitory effect on the cell proliferation of SARS-CoV-2 in vitro, with an inhibition rate of 61.12%, even weaker than Remdesivir. This new discovery provides us with new ideas for in-depth studies on the development of natural products with this class of structural generalizations as inhibitors of SARS-CoV-2, and provides an experimental basis for the next step of mechanistic studies.

Chemotherapy represents the most applied approach to cancer treatment. Owing to the frequent onset of chemoresistance and tumor relapses, there is an urgent need to discover novel and more effective anticancer drugs. In search for therapeutic alternatives to treat the cancer disease, a se-ries of hybrid pyrazolo[3,4-d]pyrimidin-4(5H)-ones tethered with hydrazide-hydrazones, 5a-h, was synthesized from condensation reaction of pyrazolopyrimidinone-hydrazide 4 with a series of arylaldehydes in EtOH, in acid catalysis. In vitro assessment of antiproliferative effects against MCF-7 breast cancer cells, unveiled that 5a, 5e, 5g, and 5h were the most effective compounds of the series and exerted their cytotoxic activity through apoptosis induction and G0/G1 phase cell-cycle arrest. To explore their mechanism at a molecular level, 5a, 5e, 5g, and 5h were evalu-ated for their binding interactions with two well-known anticancer targets, namely the epider-mal growth factor receptor (EGFR) and the G-quadruplex DNA structures. Molecular docking simulations highlighted high binding affinity of 5a, 5e, 5g, and 5h towards EGFR. CD experi-ments suggested 5a as a stabilizer agent of the G-quadruplex from the KRAS oncogene promot-er. In the light of these findings, we propose the pyrazolo-pyrimidinone scaffold bearing a hy-drazide-hydrazone moiety as a lead skeleton for designing novel anticancer compounds.

This dissertation presents a method for the synthesis of substituted indoles bearing heterocyclic substituents onto the 3- position. The route for the synthesis of the heterocyclic substituents indoles starts from 3-acetyl indole nucleus depend on two parts. One part: Reaction of 3-acetylindole 1 with hydrazide compounds such as phenyl hydrazine, hydrazine hydrate, and thio-semicarbazide, to yield 3-(1-(2-phenylhydrazono) ethyl)-1H-indole 2, 3-(1-hydrazonoethyl)-1H-indole 6, and thiosemicarbazone 10 respectively. 3-(1-Hydrazonoethyl)-1H-indole 6 reacted with thiophene-2-carboxaldeyde, isatin and 3-acetyl indole. In the same way, 3-(1-(2-phenylhydrazono) ethyl)-1H-indole 2 reacted with thioglycollic acid, glycine and benzaldehyde. 3-Acetylindole 1 thiosemicarbazone reacted with acetic anhydride, piperidine, concentration of hydrochloric acid and thiophene-2-carboxaldeyde. Second part. Reaction of 3-acetyl indole 1 with amines compounds such as p-nitroaniline to formed Schiff base 15 which it reacted with thioglycollic acid to give compound 16. 3-Acetyl indole 1 reacted with ethylene diamine to afford bis imine indole to afford compound 17. The reports of this docking study revealed that the new compounds exhibit good antibacterial activity. The synthesized compounds screened in vitro for their antibacterial activity revealed remarkable inhibitory effects against the selected microorganisms. And also an anti-oxidant activity studying for some synthesized compounds. Structures of the newly synthesized compounds examination by spectral data (IR, 1H- NMR and 13C -NMR).

Cathepsin D (CatD; EC 3.4.23.5) family peptidases of parasitic organisms are regarded as potential drug targets as they play critical roles in the physiology and pathobiology of parasites. Previously, we characterized the biochemical features of cathepsin D isozyme 2 (CatD2) in the carcinogenic liver fluke Clonorchis sinensis (CsCatD2). In this study, we performed all-atomic molecular dynamics simulations by applying different systems for the ligand-free/bound forms under neutral and acidic conditions to investigate the pH-dependent structural alterations and associated functional changes in CsCatD2. CsCatD2 showed several distinctive characteristics as follows: 1) CsCatD2-inhibitor complex formed more hydrogen bonds; 2) acidic pH caused major conformational transitions from open to closed state in this enzyme; 3) neutral pH induced displacement of the N-terminal part to hinder the accessibility of the active site and open allosteric site of this enzyme; and 4) the flap dynamics metrics, including distance (d1), TriCα angles (θ1 and θ2), and dihedral angle (ϕ), account for the asymmetrical twisting motion of the active site of this enzyme. These findings provide an in-depth understanding of the pH-dependent structural dynamics of CsCatD2 and basic information for the rational design of an inhibitor as a drug targeting CsCatD2.

Corona Virus Infectious Disease-2019 (COVID-19) outbreak originated recently at Wuhan, China in December 2019. It has already spread rapidly to more than 200 countries and has been declared a pandemic by WHO. It is caused by a beta-coronavirus named as SARS-CoV-2. There is no definitive cure, either drug or vaccine, to treat or prevent this viral disease. Recently, the crystal structure of the main protease M^pro has been determined. M^pro is responsible for the proteolytic maturation of the polyprotein essential for the viral replication and transcription, which makes it an important drug target. The discovery of new drug molecules may take years before getting to the clinics. So, considering urgency we performed molecular docking studies using FDA approved drugs to identify molecules that could potentially bind to the substrate-binding site and inhibit SARS-CoV-2 main protease (M^pro). We used the Glide module in Schrodinger software suite to perform molecular docking studies followed by MM-GBSA based energy calculations to score the hit molecules. Molecular docking and manual analysis suggest that several drugs may bind and potentially inhibit M^pro. We also performed molecular simulations studies for selected compounds to evaluate protein-drug interactions. Interestingly, we observed only one antiviral compound, Adefovir, in the top50 list of compounds. Considering bioavailability, lesser toxicity, route of administration some of the top-ranked drugs including lumefantrine (antimalarial), dipyridamole (coronary vasodilator), dihydroergotamine (used for treating migraine), hexoprenaline (anti- asthmatic), riboflavin (vitamin B2) and pantethine (vitamin B5) may be taken forward for further in vitro and in vivo experiments to investigate their therapeutic potential.