Pharmacophore Modeling and Molecular Docking: Bridging the Gap Between Structure and Function

• Understand pharmacophore modeling concepts and its role in drug design.
• Learn molecular docking principles for ligand-target interaction predictions.
• Analyze and interpret docking results for binding affinity and molecular interactions.
• Use computational tools for virtual screening and hit identification.
• Apply pharmacophore modeling and docking simulations to design drug-like compounds.

Day 1: Introduction to Pharmacophore Modeling

• Pharmacophore Concept: What it is, and its role in drug discovery
• Pharmacophore Generation: Methods to create pharmacophore models (3D-QSAR, receptor-based, ligand-based)
• Tools: MOE, LigandScout, Discovery Studio
• Mini task: Generate a pharmacophore model for a selected drug target using LigandScout

Day 2: Molecular Docking Fundamentals

• Docking Theory: Docking algorithms, scoring functions, and their application in virtual screening
• Preparing Receptors and Ligands: Receptor preparation, ligand conformer generation, and energy minimization
• Key Analyses: Binding affinity, RMSD, and interaction profiles
• Tools: AutoDock Vina, PyRx, DockingServer
• Mini task: Perform molecular docking of a ligand with a receptor and analyze interaction scores and binding modes

Day 3: Advanced Applications and Research-Grade Reporting

• Advanced Docking: Induced fit docking, protein flexibility, and multi-target docking
• Binding Site Analysis: Identifying and visualizing active sites, interaction networks, and water-mediated interactions
• Pharmacophore-Docking Integration: Integrating pharmacophore models into docking workflows for virtual screening
• Reproducibility and Reporting: Best practices for reporting docking results and ensuring reproducibility in publications
• Tools: AutoDock, PyMOL, Chimera, and optional PLUMED overview
• Mini task: Create a 1-page research-grade docking report (including binding site visualization, ligand poses, and interaction analysis)

Participants will be able to:

• Create and apply pharmacophore models to identify key binding features in drug design.
• Perform molecular docking studies to predict protein-ligand interactions.
• Interpret docking results and evaluate binding affinity for drug candidates.
• Conduct virtual screening using docking simulations for lead discovery.
• Understand the practical use of computational chemistry tools like AutoDock and MOE.

• Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
• Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
• University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
• Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
• Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.