Welcome to the Computational and Structural Research in Drug Discovery Lab

About Us

CSRDD Lab is dedicated to leveraging computational methods for innovative drug development targeting infectious diseases, pathogenic viruses, bacteria, and cancer mechanisms. The lab employs diverse computer-based tools to expedite drug discovery by identifying potential drug candidates, optimizing their attributes, and predicting interactions with biological targets. Molecular modeling generates 3D structures of biomolecules, aiding in the study of molecular interactions and binding sites crucial for drug-target engagement. Virtual drug screening employs computational methods to assess large chemical compound databases, forecasting their binding affinity for specific targets. Techniques like docking predict binding modes and affinities. Ligand-based design uses existing ligands to create new compounds with similar features and interactions, supported by QSAR models correlating structural features with biological activities. High-end computers perform molecular dynamics simulations, divulging biomolecular behavior insights. Quantum Mechanics (QM) investigates enzyme catalysis mechanisms using DFT and ab initio calculations, guiding enzyme engineering for enhanced catalysis. QM combines with molecular dynamics for comprehensive insights. Specialized software tools predict drug properties, and the lab aims to develop tailored software and algorithms for drug design. Their approach, backed by experimental validation and clinical research, strives to discover targeted therapeutic agents for cancer and viral infections.