A guest lecture was arranged by Dr. Paramita Das

4 Feb 2025

The lecture was given on the topic Revolutionising drug Discovery: The contribution of In Silico Techniques for better lead optimisation and target identification Computational (in silico) methods have reshaped drug discovery by compressing timelines, reducing costs, and improving decision quality from target identification through lead optimisation and candidate selection. Advances in structural biology (e.g., cryo EM, predicted structures), molecular simulation, machine learning, and multi omics integration now enable mechanism focused discovery at scale. This review synthesises the core toolkit—target deconvolution, structure and ligand based virtual screening, QSAR/ML modelling, molecular dynamics (MD), free energy methods, de novo design, ADMET and PBPK/PKPD modelling, and network pharmacology—and shows how they interlock into a modern, data centric workflow. We highlight best practices, typical pitfalls, and future directions including active learning, foundation models, digital twins, and AI assisted synthesis planning.