Teaching & Research
Jawaharlal Nehru University (JNU), New Delhi
Pradipta Bandyopadhyay is a Professor for Computational Biophysical Chemistry at JNU. He is primarily interested in understanding chemical and biological phenomena from the first principle. The problems he investigates are interdisciplinary in nature, so are the tools uses. He develops and uses a variety of computer simulation techniques and applies them to chemical and biological problems.
Members in his group are currently working on:
- Development of enhanced Monte Carlo simulation techniques to explore the energy landscape of water clusters and biomolecules.
- Properties of RNA with the non-Watson-Crick base pair.
- Development of a model of the cytoplasm of a bacterial cell and understanding diffusion and hydrodynamics.
- Development of Random Walk models to study anomalous diffusion.
- Effect of molecular crowding on biomolecular systems.
- Elucidation of allosteric inhibition mechanism.
Pradipta worked as post-doctoral fellow at Iowa State University and the University of California, San Francisco. He worked as an Assistant Professor at IIT Guwahati and Visiting Associate Professor at the University of California, San Francisco (2008).
Pradipta Bandyopadhyay is interested in the development of potential energy function for molecular simulation using machine learning techniques.
- Use of machine learning techniques for problems in molecular biophysics.
- Analysis of computer simulation trajectories using machine learning
Field of Expertise
- Theoretical and Computational Molecular Biophysics
- Statistical Mechanics
- Computer Simulation
- An analytical correlated random walk model and its application to understand subdiffusion in crowded environment.
Sabeeha Hasnain and Pradipta Bandyopadhyay, J.Chem.Phys, 143 (11), 114104 (2015).
- A New Coarse-Grained Model for E. coli Cytoplasm: Accurate Calculation of the Diffusion Coefficient of Proteins and Observation of Anomalous Diffusion.
Sabeeha Hasnain, Christopher L. McClendon, Monica T. Hsu, Matthew P. Jacobson and Pradipta Bandyopadhyay, PloS one, 9(9), e106466 (2014).
- Monte Carlo Temperature Basin Paving with Effective Fragment Potential: An Efficient and Fast Method for Finding Low Energy Structures of Water Clusters (H2O)20 and (H2O)25 Sudhanshu Shanker and Pradipta Bandyopadhyay, J. Phys. Chem. A, 115(42), 11866-11875 (2011).
- Accelerating QM/MM sampling using pure MM potential: the case of effective fragment potential.
Pradipta Bandyopadhyay, Journal of Chemical Physics, 122, 2005 (1st March issue).
- Microscopic picture of water-ethylene glycol interaction near a model DNA by computer simulation: Concentration dependence, structure, and localized thermodynamics
Atul Kumar Jaiswal, Rakesh Srivastava, Preeti Pandey and Pradipta Bandyopadhyay, PloS one, 13 (11), e0206359 (2018).
School of Computational & Integrative Sciences