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Pharmacophore modeling identifies the essential features required for a molecule to bind to a specific biological target, while molecular docking simulates the interaction between small molecules (ligands) and target macromolecules (usually proteins) to predict binding affinity. These methods are key in the early stages of drug design, allowing researchers to virtually screen large libraries of compounds, optimize molecular interactions, and identify potential drug candidates.
This workshop will provide a comprehensive understanding of both pharmacophore modeling and molecular docking, teaching participants how to create pharmacophore models, perform docking studies, and analyze docking results. Participants will also learn to use popular tools for pharmacophore-based virtual screening and molecular docking simulations. Dry-lab sessions will cover software tools such as AutoDock, GOLD, and MOE and demonstrate practical workflows in computational drug discovery.
This workshop aims to teach participants the principles and applications of pharmacophore modeling and molecular docking for drug discovery. It covers how pharmacophore-based approaches can identify key functional groups and how docking techniques predict interactions between small molecules and macromolecular targets. The program emphasizes integrating structure-based approaches into drug design workflows, supporting researchers and professionals in drug discovery, computational chemistry, and molecular modeling.
01/15/2026
IST 07:00 PM
01/15/2026 ā 01/17/2026
IST 08:00 PM
Participants will be able to:
ā¹1799 | $70
ā¹2799 | $80
ā¹3799 | $95
ā¹4799 | $110
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PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
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