Version 1
: Received: 1 October 2023 / Approved: 4 October 2023 / Online: 4 October 2023 (05:14:41 CEST)
How to cite:
Praveen, M.; Ullah, I.; Buendia, R.; Ahmad Khan, I.; Sayed, M.G.; Bhatt, M.A.; L. zeidan, N.; Yaseen, M. Network Pharmacology of Potentilla nepalensis Extract Revealed p53, Nf-kB1, and HSP Proteins As Potential Biomarkers. Preprints2023, 2023100208. https://doi.org/10.20944/preprints202310.0208.v1
Praveen, M.; Ullah, I.; Buendia, R.; Ahmad Khan, I.; Sayed, M.G.; Bhatt, M.A.; L. zeidan, N.; Yaseen, M. Network Pharmacology of Potentilla nepalensis Extract Revealed p53, Nf-kB1, and HSP Proteins As Potential Biomarkers. Preprints 2023, 2023100208. https://doi.org/10.20944/preprints202310.0208.v1
Praveen, M.; Ullah, I.; Buendia, R.; Ahmad Khan, I.; Sayed, M.G.; Bhatt, M.A.; L. zeidan, N.; Yaseen, M. Network Pharmacology of Potentilla nepalensis Extract Revealed p53, Nf-kB1, and HSP Proteins As Potential Biomarkers. Preprints2023, 2023100208. https://doi.org/10.20944/preprints202310.0208.v1
APA Style
Praveen, M., Ullah, I., Buendia, R., Ahmad Khan, I., Sayed, M.G., Bhatt, M.A., L. zeidan, N., & Yaseen, M. (2023). Network Pharmacology of Potentilla nepalensis Extract Revealed p53, Nf-kB1, and HSP Proteins As Potential Biomarkers. Preprints. https://doi.org/10.20944/preprints202310.0208.v1
Chicago/Turabian Style
Praveen, M., Noha L. zeidan and Muhammad Yaseen. 2023 "Network Pharmacology of Potentilla nepalensis Extract Revealed p53, Nf-kB1, and HSP Proteins As Potential Biomarkers" Preprints. https://doi.org/10.20944/preprints202310.0208.v1
Abstract
Potentilla nepalensis belongs to the Rosaceae family, and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in our earlier studies. However, the PCs affecting human genes and their roles in the body are not disclosed till now. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDS), and MMGBSA methodologies. SMILES format of PCs from the PubChem used as input to DIGEP-Pred, 764 identified as the inducing genes. Their enrichment studies have shown inducing genes gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analysing parameters done in Cytoscape v3.10 revealed three biomarkers, TP53 from MS, NR, and NS induced genes; HSPCB and Nf-kB1 from MR induced genes. From 40 PCs, two PCs 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6, and -8.0; three PCs 3a, (NR) 4a and 4c (NS) with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Biomarkers identified in this study, have a prominent role in numerous cancers. Thus, further investigations such as in-vivo and in-vitro should be done to find the molecular functions and interlaying mechanism of the identified biomarkers on numerous cancer cell lines in considering the PCs of P.nepalensis.
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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