PROTDYN: A FOUNDATION PROTEIN LANGUAGE MODEL FOR THERMODYNAMICS AND DYNAMICS GENERATION

Yikai Liu, Haoyang Zheng, Lining Mao, Yanbin Wang, Ming Chen, Guang Lin

Keywords: Transformer, Protein Language Model, Protein ensemble generation, Protein dynamics, generative model

TL;DR: A unified generative model for simultaneously generating protein conformation ensemble and dynamic trajectories

Abstract: Molecular dynamics (MD) simulation has long been the principal computational tool for exploring protein conformational landscapes, but its application is limited by high computational cost. We present ProTDyn, a foundation protein language model that unifies conformational ensemble generation and multi-timescale dynamics modeling within a single framework. Unlike prior approaches that treat these tasks separately, ProTDyn allows flexible i.i.d ensemble sampling and dynamic trajectory simulation. Across diverse protein systems, ProTDyn yields thermodynamically consistent ensembles, faithfully reproduces dynamical properties over multiple timescales, and generalizes to proteins beyond its training data—offering a scalable and efficient alternative to conventional MD simulations.

Primary Area: applications to physical sciences (physics, chemistry, biology, etc.)

Submission Number: 4922