Course

Unit 1

Why Computational Drug Design? The Drug Discovery pipeline; Chemical Space; Cheminformatics and Virtual High Throughput Screening; Lipinski’s Rules of 5 and ADMET Modelling; Pharmacodynamics and pharmacokinetics; Structure-Based and Ligand-Based Drug Design.

Unit 2

Chemical File Formats and Representations; Topological Indices; Substructural Descriptors and 2D fingerprints; Local Molecular Surface Property Descriptors; 3D Shape and Chiral descriptors; Molecular Similarity Measures and Kernels; Chemical and Biological Networks.

Unit 3

Linear Free Energy Relationships; Pharmacophores and Molecular Interaction Fields; Model Validation; Structure Based Methods – Docking & Scoring; Molecular Simulation (Monte-Carlo, Molecular dynamics) – Structure and dynamics properties (normal mode analysis) – Gaussian and Gauss view – Density functional theory.

Unit 4

Linear and Non-Linear Models; Classification, Regression and Ranking; Data preprocessing, Performance Measures and unbalanced datasets; Dimensionality reduction and Feature selection; Evolutionary computing; Kernel methods; Best Practices in Predictive Modeling; Applications of Deep Learning in Pharma.

Course Objectives

• To educate students on fundamentals stages of drug discovery pipeline and how computational and informatics techniques can accelerate the pace of drug discovery.
• To teach them how to encode a molecule into numerical molecular descriptors and strings, allowing computational treatment of molecules.
• Discuss drug-likeness, informatics approaches to the prediction of chemical properties – QSAR, pharmacophores, pharmacokinetics, and pharmacodynamics.
• To teach them how to apply AI / ML techniques and construct validated classification and regression models for biological endpoints.

Course Outcomes

After completing this course, students will be able to

CO-PO Mapping

Evaluation Pattern

Text Books / References

Johann Gasteiger, Thomas Engel, Chemoinformatics: A Textbook (Wiley-VCH, 2003)

Jürgen Bajorath (Editor), Chemoinformatics and Computational Chemical Biology (Methods in Molecular Biology) (Humana Press, 2004)

Andrew R. & Leach, Valerie Gillet, An Introduction to Chemoinformatics (Springer International, New Delhi, 2009)

Merz Jr, K.M., Ringe, D. and Reynolds, C.H. (Editors) Drug design: structure-and ligand-based approaches (Cambridge University Press, 2010).

1. Sukumar, et al, Computational Drug Discovery: A Primer (Ion Cure Press, 2023).

John L. Lamattina, Drug Truths: Dispelling the Myths about Pharma R&D (John Wiley, Hoboken, NJ, 2008)

Barry Werth, The Billion Dollar Molecule: One Company’s Quest for the Perfect Drug (Simon & Schuster, 1995)