An Integrated QSAR-MD-DCCM Pipeline: A Predictive Computational Platform for the Rational Design and Dynamic Functional Validation of Dual-Target Directed Ligands

The development of Multi-Target-Directed Ligands (MTDLs) offers a compelling therapeutic strategy for multifactorial diseases like cancer and Alzheimer's disease (AD), which share pathological pathways, notably microtubule abnormalities. This study introduces and validates a state-of-the-art computational pipeline, the QSAR-MD-DCCM workflow, designed to accelerate the discovery of dual-acting agents targeting tubulin polymerization and acetylcholinesterase (AChE). Two highly predictive QSAR models (R2 > 0.83), built upon the trimethoxyphenyl scaffold, guided the rational design of 16 novel compounds. Subsequent ADMET screening identified compounds 15 and 16 as optimal leads, demonstrating excellent physicochemical properties and CNS penetrability. Molecular docking and rigorous 100 ns Molecular Dynamics (MD) simulations confirmed strong, persistent binding to both targets (PDB ID: 4O2B for tubulin; 1EVE for AChE), with the compounds showing complementary, target-differentiated potency. Subsequent MM-GBSA/MM-PBSA binding free energy calculations provided the essential energetic validation, confirming highly favorable binding for both leads. Crucially, Dynamic Cross-Correlation Map (DCCM) analysis provided novel mechanistic insights into the functional allosteric coupling of residues upon ligand binding, reinforcing the stability and distinct dynamic modes of action for both compounds. This integrated methodological approach successfully delivered two highly validated virtual MTDL candidates, establishing a robust and predictive platform for accelerating dual-target drug discovery.