Ananya Chakravarti

So excited for #BiophysicsWeek2025! Join the festivities on Thursday, March 27 for some fascinating talks in IDPSeminars 🥳

This summer in beautiful Santa Barbara we will run a 3-day conference on “Biological Physics of Biomolecular Condensates: Bridging Theory and Experiment” June 16 to 18th. Register now: www.kitp.ucsb.edu/activities/b...

Accurate prediction of thermoresponsive phase behavior of disordered proteins Protein responses to environmental stress, particularly temperature fluctuations, have long been a subject of investigation, with a focus on how proteins maintain homeostasis and exhibit thermoresponsive properties. While UCST-type (upper critical solution temperature) phase behavior has been studied extensively and can now be predicted reliably using computational models, LCST-type (lower critical solution temperature) phase transitions remain less explored, with a lack of computational models capable of accurate prediction. This gap limits our ability to probe fully how proteins undergo phase transitions in response to temperature changes. Here, we introduce Mpipi-T, a residue-level coarse-grained model designed to predict LCST-type phase behavior of proteins. Parametrized using both atomistic simulations and experimental data, Mpipi-T accounts for entropically driven protein phase separation that occurs upon heating. Accordingly, Mpipi-T predicts temperature-driven protein behavior quantitatively in both single- and multi-chain systems. Beyond its predictive capabilities, we demonstrate that Mpipi-T provides a framework for uncovering the molecular mechanisms underlying heat stress responses, offering new insights into how proteins sense and adapt to thermal changes in biological systems. ### Competing Interest Statement The authors have declared no competing interest.

Our work helps bridge the gap between fundamental biophysics and real-world applications. Want to learn more? Read @jerelleaj.bsky.social and my new preprint on BioRXiv! biorxiv.org/content/10.1... 📖 (4/4)

Mpipi-T provides new insights into proteins that phase separate under heat stress—key for understanding disease, climate adaptation, and materials design. 🌎 (3/4)

We developed Mpipi-T, a coarse-grained model that predicts thermoresponsive phase behavior of proteins with quantitative accuracy. It captures both UCST (low temp) and LCST (high temp) phase separation. 🔬 (2/4)

Cells have evolved to adapt to changing environments to maintain homeostasis. Can we predict how temperature affects protein phase separation? 🌡️ (1/4)