JAGANNATH MONDAL

Tata Institute of Fundamental Research, Hyderabad

Jagannath Mondal is a computational biophysicist at TIFR Hyderabad. He completed his B.Sc. in Chemistry at Calcutta University in 2004 and M.Sc. in IIT Kanpur in 2006. He earned his PhD at University of Wisconsin Madison, USA (Research Advisor: Arun Yethiraj) in 2011. He pursued his postdoctoral research at Columbia University, USA (Research Advisor: Bruce J. Berne) during the period of 2011–2015. Subsequently, he joined Tata Institute of Fundamental Research, Hyderabad in July 2015 and is currently serving as a Reader. His research interest involves computer simulation of chemically and biologically relevant processes. The current research project in his group ranges diverse topics including dynamics of biomolecular recognition at real time, optimization of collective variables and cellular biological processes. He is a Ramanujan fellow. Jagannath Mondal was selected Associate in 2016.

JAGANNATH MONDAL

SESSION 1C – Inaugural Lectures by Fellows/Associates

Arnab Rai Chaudhuri

Computer simulation of biomolecular recognition at atomistic precision and in real time View Presentation

Underlying the drug discovery, there exists the critical process of molecular recognition of ligand by the target protein. However, computational approaches on molecular recognition have heavily relied on docking-based techniques whose accuracies are limited by sampling issues. His research group has undertaken a completely different approach where they attempt to capture the entire process of ligand diffusing to the protein cavity at atomistic resolution and in real time. So far, they have successfully applied this approach to two protein/ligand system, namely T4 Lysozyme/benzene and cytochrome P450/camphor. In both cases, they have been able to simulate the complete process at crystallographic accuracy and at correct kinetics. The ligand binding pathways that emerge from these simulations are novel and shed light on the atomistic mechanism involving complete biomolecular recognition.