Drug Discovery Masterclass: Molecular Docking from Scratch- recorded courses
Master the essential computational technique for predicting how small molecules bind to therapeutic targets to accelerate lead identification. Go from raw chemical structures to high-confidence binding poses using industry-standard AI tools and physics-based scoring functions.
Course Description
In the rapidly evolving 2026 pharmaceutical landscape, Computational Aided Drug Design (CADD) is no longer optional—it is the backbone of modern R&D. This masterclass offers a comprehensive journey into Molecular Docking, starting from the absolute basics of structural biology to advanced Virtual Screening workflows. You will learn to navigate the Protein Data Bank (PDB), prepare "docking-ready" proteins, and generate optimized 3D ligand conformations. The course integrates cutting-edge Generative AI and Machine Learning models like DiffDock to enhance pose prediction accuracy and speed. By mastering the synergy between physics-informed neural networks and traditional force fields, you will be able to identify potent drug candidates while minimizing costly "wet-lab" failures. This is your roadmap to becoming a "Scientific Translator" in the high-demand fields of Pharmacoinformatics and Precision Medicine.
What You'll Learn
Structural Bioinformatics Foundations: Understand protein-ligand interactions, hydrogen bonding, and hydrophobic effects at the atomic level.
Target Preparation: Master the removal of water molecules, addition of polar hydrogens, and Gasteiger charge assignment for receptors.
Advanced Docking Algorithms: Compare and contrast Rigid vs. Flexible docking using Monte Carlo and Genetic Algorithms.
AI-Powered Virtual Screening: Use Deep Learning tools to screen libraries of millions of compounds against a single target in hours.
Result Interpretation: Analyze Binding Affinity (kcal/mol), Root-Mean-Square Deviation (RMSD), and 2D interaction maps for publication-quality reports.
Curriculum
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Structural Bioinformatics Foundations: Understand protein-ligand interactions, hydrogen bonding, and hydrophobic effects at the atomic level.
Lesson -
Target Preparation: Master the removal of water molecules, addition of polar hydrogens, and Gasteiger charge assignment for receptors.
Lesson -
Advanced Docking Algorithms: Compare and contrast Rigid vs. Flexible docking using Monte Carlo and Genetic Algorithms.
Lesson -
AI-Powered Virtual Screening: Use Deep Learning tools to screen libraries of millions of compounds against a single target in hours.
Lesson -
Result Interpretation: Analyze Binding Affinity (kcal/mol), Root-Mean-Square Deviation (RMSD), and 2D interaction maps for publication-quality reports.
Lesson
