Ponnaiya's Madurai Bioscience Hub - Advanced Research and Development

CAG & MBH - Guest Lecture Series – June 2026 - Computer Aided Drug Discovery (CADD) in Practice -Insights from the Bench to the Algorithm

CADD in Practice — Insights from the Bench to the AlgorithmJoin us for an engaging guest lecture on the practical applications of Computer-Aided Drug Discovery (CADD) -Insights from the Bench to the Algorithm.This session will take participants through the complete CADD workflow, from target identification and structure retrieval to virtual screening, molecular dynamics validation, and hit prioritization. Beyond the technical steps, the lecture will focus on the real-world challenges of drug discovery, including the limitations of molecular docking, the importance of protein dynamics, the role of cheminformatics and RDKit-based automation, and the growing impact of Artificial Intelligence in the field.Participants will also gain valuable insights into why computationally promising compounds often fail during experimental validation and why scientific understanding and human judgment remain essential for successful drug discovery.About the SpeakerDr. Dinesh Kumar Sriramulu was a Postdoctoral Researcher at the Institute of Molecular and Translational Medicine (IMTM), Faculty of Medicine and Dentistry, Palacký University, Czech Republic. His research focuses on Computer-Aided Drug Design (CADD), molecular docking, molecular dynamics simulations, chemoinformatics, virtual screening, and computational modeling of biomolecular interactions. He earned his Ph.D. in Chemical Engineering from Pusan National University, South Korea, where his doctoral research investigated the factors influencing the predictive accuracy of molecular docking tools. Throughout his career, Dr. Sriramulu has contributed to several interdisciplinary drug discovery projects and has authored multiple research publications in molecular docking, protein–ligand interactions, computational structural biology, and AI-assisted drug design. His work combines computational methods with practical drug discovery applications, providing valuable insights into both the capabilities and limitations of modern CADD approaches.Key Topics1. End-to-end CADD workflow in research and industry2. Molecular docking beyond scoring functions3. Molecular dynamics: understanding proteins in motion4. Cheminformatics and automated pipelines using RDKit5. AI in drug discovery: capabilities, limitations, and future prospects6. Common pitfalls and failures in computational drug discovery7. Integrating computational predictions with experimental validationWho Can Attend?Students, Research Scholars, Faculty Members, Industry Professionals, and anyone interested in Bioinformatics, Computational Biology, Biotechnology, Pharmaceutical Sciences, Medicinal Chemistry, and Drug Discovery.Benefits✔ Learn practical CADD workflows used in research and industry✔ Understand the strengths and limitations of computational methods✔ Gain insights into modern AI-driven drug discovery approaches✔ Interact with experts and fellow researchersRegister now and explore how computational tools, scientific reasoning, and experimental validation work together to drive successful drug discovery.