Workshop details
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7-Day Workshop on Pharmacophore and QSAR Modeling
About the Workshop
This workshop covers the fundamentals and applications of pharmacophore modeling and Quantitative Structure-Activity Relationship (QSAR) analysis to aid rational drug design.
Who Can Join
Students, researchers, and professionals in medicinal chemistry, computational biology, and drug discovery.
Prerequisites
Basic chemistry and molecular biology knowledge. Familiarity with molecular docking and cheminformatics is a plus.
Day 1: Introduction to Pharmacophore Modeling
- Concept and significance of pharmacophores in drug design
- Types of pharmacophore features (hydrogen bond donors/acceptors, hydrophobic, aromatic)
- Tools overview: LigandScout, PharmaGist
- Creating pharmacophore models from ligand sets
- Validation techniques (ROC curve, enrichment studies)
- Screening compound libraries against pharmacophores
- Filtering hits based on fit score and drug-likeness
- QSAR principles and descriptors (2D, 3D, physicochemical)
- Dataset preparation and descriptor calculation
- Tools: PaDEL, Dragon, RDKit
- Regression and classification models (MLR, PLS, Random Forest)
- Model training, validation, and interpretation
- Predicting activity of new compounds
- Applicability domain and model limitations
- Real-world applications of pharmacophore and QSAR models in drug discovery
- Participant project presentations
- Discussion on integrating these methods with docking and molecular dynamics