Research

Chakrabarty Lab

Research Overview

Our research operates at the intersection of computational molecular biophysics, theoretical physical chemistry, and data science. We design and apply advanced computational approaches — grounded in statistical mechanics, molecular thermodynamics, and machine learning — to problems where molecular dynamics controls biology and function. A defining feature of our group is the co-development of novel in-house algorithms alongside their application to real biological systems.

On the methods side, we develop and release in-house algorithms — PathGennie (direction-guided adaptive sampling for rapid rare-event pathway generation), WeTICA and CoWERA (directed weighted-ensemble enhanced sampling for rare-event kinetics), IceCoder (variational-autoencoder identification of crystal/ice phases), and PPIscout (mixed-solvent mapping of protein–protein interaction hotspots). On the applications side, our work spans dynamic protein allostery and cellular signalling; druggable cryptic-pocket discovery and protein–protein-interaction inhibition (PCSK9, PLK1, Rho GTPases); prion misfolding and aggregation; enzyme promiscuity and selective inhibition (laccase, acetylcholinesterase); the structure of water around solutes and interfaces; and the molecular thermodynamics of soft matter — gas hydrates, designer ionic liquids, self-assembly and nucleation.

Research Themes
Allostery, Signalling & Protein–Protein Interactions
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Allostery, Signalling & Protein–Protein Interactions

We decode how proteins relay signals between distant sites — the basis of cellular regulation and a powerful, selective handle for drug design. Combining all-atom and mixed-solvent molecular dynamics with QM/MM, we established the electrostatics-driven, dynamic nature of allostery in PDZ domains, mapped nucleotide- and phosphorylation-controlled switching in Rho-family GTPases, and uncovered druggable cryptic pockets that let us inhibit otherwise ‘undruggable’ protein–protein interactions such as PCSK9–LDLR and PLK1.

Selected Publications

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Folding, Misfolding & Enzyme Catalysis
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Folding, Misfolding & Enzyme Catalysis

We connect molecular structure and dynamics to biological function — and dysfunction. Our simulations resolve how prion proteins misfold and aggregate into disease-associated states, how mini-proteins navigate their folding landscapes, and how enzymes such as laccase achieve broad substrate promiscuity or are selectively inhibited (acetylcholinesterase) — bridging fundamental biophysics with bioremediation and drug discovery.

Selected Publications

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Soft Matter, Self-Assembly & Interfaces
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Soft Matter, Self-Assembly & Interfaces

We apply molecular thermodynamics to complex, real-world soft-matter systems: the nucleation and growth of gas (methane) hydrates relevant to energy and flow assurance, designer ionic liquids that stabilise biomolecules, surfactant and polymer self-assembly, nanoparticle nucleation, and stimuli-responsive liquid crystals — frequently in close partnership with experiment and industry.

Selected Publications

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Interested in joining?

We are always looking for motivated PhD students and postdoctoral researchers with backgrounds in chemistry, physics, or computational biology.