Biophysical Society Thematic Meeting | Hamburg 2022

Biophysics at the Dawn of Exascale Computers

Friday Speaker Abstracts

TWISTING DNA WITH SALT Sergio Cruz-Leon 1 ; Willem Vanderlinden 2 ; Peter Müller 2 ; Tobias Forster 2 ; Georgina Staudt 2 ; Yi-Yun Lin 2 ; Jan Lipfert 2 ; Nadine Schwierz 1 ; 1 Max Planck Institute of Biophysics, Theoretical Biophysics, Frankfurt am Main, Germany 2 LMU Munich, Department of Physics and Center for Nanoscience (CeNS), Munich, Germany The structure and properties of DNA change with the environment, in particular with the ionic atmosphere. In this work, we resolve how cations influence the helical twist of DNA -one of its central properties- by combining single-molecule magnetic tweezer experiments with extensive all-atom molecular dynamics simulations for monovalent alkali and divalent alkaline earth cations. Two interconnected trends emerged: First, DNA twist strongly depends on cation identity. For example, at 50 mM concentration, DNA twist increases as Na + < K + < Ba 2+ < Rb + < Li + ≈ Cs + < Sr 2+ < Mg 2+ < Ca 2+ . Second, DNA twist increases with increasing concentration for all ions investigated. MD simulations reveal a preferential binding of the cations to the DNA backbone or nucleobases, which have an opposite effect on DNA twist and provide an atomic explanation of the overall effect. Simultaneously, the quantitative comparison between MD simulation and high-resolution experimental twist measurements provides a stringent test for the existing simulation force fields and reveals their shortcomings. The comprehensive view obtained from our integrated approach provides the foundation for understanding and predicting DNA changes induced by the ionic environment in nature and nanotechnology. COMPUTING PROTEIN BINDING KINETICS: CHALLENGES IN BRIDGING TIMESCALES. Rebecca C. Wade 1,2 ; 1 Heidelberg Institute for Theoretical Studies, Heidelberg, Germany 2 Heidelberg University, Heidelberg, Germany The rates at which molecules associate and dissociate are important determinants of biological function. Such rates are challenging to compute as they often on timescales far beyond those accessible to classical atomic-detail molecular dynamics simulations. Growing evidence that the efficacy of a drug can be correlated to target binding kinetics has however led to the development of many new methods aimed at computing rate constants for receptor-ligand binding processes [1,2], see also kbbox.h-its.org. Here, I will describe our recent studies to explore the determinants of structure-kinetic relationships and to develop computationally efficient methods - employing multiresolution molecular simulations and machine learning - to estimate protein-ligand and protein-protein binding kinetic parameters. [1] Bruce NJ, Ganotra GK, Kokh DB, Sadiq SK, Wade RC. New approaches for computing ligand-receptor binding kinetics. Curr Opin Struct Biol. 2018, 49: 1-10.[2] Nunes-Alves A, Kokh DB, Wade RC. Recent progress in molecular simulation methods for drug binding kinetics Curr Opin Struct Biol. 2020, 64:126-133

41