An Integrated QSAR-MD-DCCM Pipeline: A Predictive Computational Platform for the Rational Design and Dynamic...

Area of Science:

• Medicinal Chemistry
• Computational Drug Design
• Pharmacology

Background:

• Multi-Target-Directed Ligands (MTDLs) are crucial for complex diseases.
• Cancer and Alzheimer's disease (AD) involve overlapping pathologies.
• Developing dual-target inhibitors is a key therapeutic strategy.

Purpose of the Study:

• To establish a computational framework for designing dual-target inhibitors.
• To identify novel MTDLs with potential against cancer and AD targets.
• To guide the rational design of trimethoxyphenyl-based analogues.

Main Methods:

• Integrated computational pipeline: QSAR, Molecular Docking, MD simulations, DCCM analysis.
• Developed two QSAR models from 57 tubulin inhibitors.
• Designed and filtered 16 novel analogues, identifying Leads 15 and 16.

Main Results:

• Validated Leads 15 and 16 via docking against β-tubulin and Acetylcholinesterase.
• MD simulations and MM-GBSA confirmed stable, favorable binding.
• DCCM analysis indicated functional synchrony in protein-ligand complexes.

Conclusions:

• Validated structural hypothesis for dual-target inhibition.
• Leads 15 and 16 exhibit strong predictive potential.
• Prioritized compounds for synthesis and in vitro evaluation.