Accelerated sampling of protein dynamics using BioEmu augmented molecular simulation

Abstract We introduce a workflow that integrates BioEmu-generated conformational ensemble with physics-based molecular simulations and Markov State Models to sample Boltzmann-weighted conformational populations across biomolecules. Molecular simulations initiated from BioEmu ensemble capture active-to-inactive transitions in CDK2 and BRAF, two members of the serine-threonine kinase family, and elucidate how the disease-causing V600E mutation in BRAF drives population shifts among distinct metastable states relative to the wild type. Furthermore, we combined BioEmu ensemble with experimental cryo-EM data to construct all-atom conformational ensembles of biomolecules. In comparison to the AlphaFold2 reduced multiple sequence alignment (rMSA-AF2) approach, BioEmu-generated ensembles sample a broader conformational space for serine–threonine kinases but fail to capture conformational heterogeneity in several cases, including Glycine transporter 1 (GlyT1), a membrane transporter, and plasmepsin-II (PlmII), an aspartic protease. Systems where side-chain conformational heterogeneity governs protein dynamics such as cryptic pocket opening in PlmII or transitions between multiple metastable states in GlyT1; molecular simulations initiated from BioEmu generated ensemble do not capture the full spectrum of conformational heterogeneity. Overall, this study presents a straightforward framework for integrating generative AI based protein emulators with statistical physics to recover Boltzmann-weighted conformational ensembles at scale, while also highlighting critical limitations that necessitate careful, system-specific analysis when interpreting protein conformational landscapes. Competing Interest Statement The authors have declared no competing interest. Footnotes ↵* Email: sbhakat{at}allotec.bio (SB) evas{at}wustl.edu (EMS) This version of the manuscript ion has been revised to update the following: 1. We have added additional results of how we can integrate cryo-EM with BioEmu to capture protein dynamics and showed some challenging cases where BioEmu augmented mD simulation fails to capture protein dynamics. See sections "Integration of BioEmu with Cryo-EM and molecular simulation captures partial conformational transitions in GlyT1" and "BioEmu generated ensemble fails to capture sidechain conformations necessary for cryptic pocket opening in plasmepsin-II". 2. We have amended the Figures and added new Figure 3-7 which highlights population dynamics of metastable states across diverse system. 3. The Abstract, Introduction, Methods and Discussion sections are amended accordingly to reflect all the changes. 4. Additional author has been added to the manuscript.