A Talk on “The Polymer Physics and Data Landscapes of Disordered Proteins: Linking Molecular Fluctuations to Aggregation Dynamics” by Dr Saikat Chakraborty

About the Talk

Proteins are complex biopolymers composed of amino acid residues whose sequential arrangements dictate their three-dimensional structures and functions. A fascinating subset, intrinsically disordered proteins (IDPs), lack a well-defined structure under physiological conditions and instead sample a vast ensemble of conformations. Remarkably, nearly half of all known human proteins are fully or partially disordered. This intrinsic flexibility enables IDPs to participate in diverse biological processes such as genome regulation, molecular recognition, and phase separation into biomolecular condensates. However, the disorder also makes them susceptible to aberrant aggregation linked to neurodegenerative and other terminal diseases. Understanding the dynamics, conformational landscapes, and aggregation mechanisms of IDPs is therefore critical to connecting structure, function, and dysfunction.

In this talk, Dr Saikat Chakraborty will present a data-driven and physics-informed investigation of the disordered protein beta-casein using atomistic molecular dynamics (MD) simulations. For an isolated beta-casein chain in water, we find that no single polymeric scaling law can describe its conformational ensemble, which marks a departure from conventional polymer physics expectations [1]. The protein exhibits a coil-to-globule conformational switch [1,2], revealing multiscale heterogeneity in its structural fluctuations. When multiple beta-casein chains aggregate, the neutron scattering spectra reveal anomalous diffusion, which our MD simulations trace to spatially heterogeneous mobilities within the aggregate. By integrating computational modeling, and statistical analysis of high-dimensional conformational data, we uncover how disorder and heterogeneity shape the physical behavior of IDPs. This multidisciplinary approach bridges physics-based modeling, biological insight, and data science techniques to illuminate the principles governing protein disorder and aggregation.

[1] Saikat Chakraborty*, Tatiana Morozova, Jean-Louis Barrat, Intrinsically disordered proteins can behaves as different polymers across conformational ensemble, Journal of Physical Chemistry B 2025, 129, 9, 2359-2369.

[2] Suman Majumder* and Saikat Chakraborty*, Scale-free Cluster-Cluster Aggregation during Polymer Collapse, Macromolecules 2025, 58, 19, 10212-10223.

About the Speaker

Saikat Chakraborty obtained his PhD from JNCASR, Bangalore, India, under the supervision of Professor Subir K Das. His thesis investigated growth dynamics in biological and abiotic model systems through statistical physics and molecular simulations. Later, he worked as a postdoctoral researcher at the Max Planck Institute for Polymer Research and Johannes Gutenberg University, both in Mainz, Germany. He now holds a postdoctoral position at the University of Grenoble Alpes in France. His research focuses on understanding disordered protein aggregation through molecular dynamics simulations, polymer physics, and interpretable machine learning methods. Saikat is also fascinated by the evolution of language and aims to apply data science to trace the origins of Indian languages, particularly his mother tongue, Bengali.