PICS Colloquium: From Stability to Dissociation: Elucidating Unbinding Kinetics of Protein-Protein Complexes via Atomistic Simulations with Omar Valsson
April 10 at 2:00 PM - 3:00 PM
Abstract: Protein-protein interactions (PPI) are ubiquitous in biological processes. Their study has significant implications for drug discovery as PPIs are important pharmacological targets for small molecules and important in various therapeutic modalities, such as targeted protein degradation and antibodies. Therefore, understanding the stability and dissociation of protein-protein complexes is of great fundamental and practical interest. In particular, the unbinding/residence times of ligands and peptide therapeutics from their target proteins (i.e., k_off, the dissociation rate constant) is a vital parameter for drug discovery and development as it is known that the dissociation kinetics are directly correlated to the pharmacological activity and efficacy of drug molecules [1]. Therefore, obtaining the dissociation kinetics from atomistic simulations has been a fundamental task in the atomistic modeling field [2]. Here, enhanced sampling methods are needed as the unbinding/dissociation event is a rare event on the simulation time scale [3]. While considerable effort has been made to obtain the unbinding/residence times in protein-ligand complexes, there have been much more limited applications towards the more challenging case of protein-protein dissociation kinetics [2].
In this talk, I will present my group’s research program that is focused on elucidating the dissociation kinetics of protein-protein complexes using atomistic simulations augmented with enhanced sampling methods, such as infrequent metadynamics [3]. I will present our results for various challenging protein-protein system, including MDM2-p53 and barnase-barstar. I will present how atomistic simulations can predict the effect of amino acid mutations on protein-protein unbinding kinetics. I will discuss how the protein model (i.e., force field) can affect the results. I will discuss the future perspective of our research program, including investigating how stabilizing molecules effect the stability and dissociation kinetics of protein-protein complexes, and the design of peptide binders using machine learning-based approaches.
References
[1] R. A. Copeland, “The drug–target residence time model: a 10-year retrospective”, Nat. Rev. Drug Discov., 15, 87–95 (2016).
[2] J. Wang, H. N. Do, K. Koirala, and Y. Miao, “Predicting Biomolecular Binding Kinetics: A Review”, J. Chem. Theory Comput., 19, 2135-2148 (2023).
[3] J. Hénin, T. Lelièvre, M. R. Shirts, O. Valsson, and L. Delemotte, “Enhanced Sampling Methods for Molecular Dynamics Simulation”, Living J. Comput. Mol. Sci. 4, (2022).
Omar Valsson
Assistant Professor in the Department of Chemistry at the University of North Texas
Omar Valsson is a tenure-track assistant professor in the Department of Chemistry at the University of North Texas, Denton, Texas, USA. His research group focuses on developing and applying advanced atomistic simulation approaches and machine learning methods to study chemical, material, and biological systems. He received his PhD degree from the University of Twente in the Netherlands in 2012, where he worked under the supervision of Prof. Claudia Filippi. He was a postdoctoral researcher at ETH Zurich and USI Lugano, Switzerland, from 2012 to 2017, working with Prof. Michele Parrinello. From 2017 to 2021, he was a Group Leader in the Theory Department headed by Prof. Kurt Kremer at the Max Planck Institute for Polymer Research in Mainz, Germany. In January 2022, he joined the Department of Chemistry at the University of North Texas. He was awarded the US Department of Energy Office of Science Early Career Award in 2023.