SOP‐GPU: influence of solvent‐induced hydrodynamic interactions on dynamic structural transitions in protein assemblies. Issue 17 (26th March 2016)

• Record Type: Journal Article
• Authors: Alekseenko, Andrey; Kononova, Olga; Kholodov, Yaroslav; Marx, Kenneth A.; Barsegov, Valeri
• Is Part Of: Journal of computational chemistry. Volume 37:Issue 17(2016)
• Page Start: 1537
• Page End: 1551
• Publication Date: 2016-03-26
• Subjects: hydrodynamic interactions -- Rotne–Prager–Yamakawa tensor -- nanomanipulation in silico -- GPU computing -- Langevin simulations -- coarse‐grained modeling; Chemistry -- Data processing -- Periodicals; 542.85
• DOI: 10.1002/jcc.24368
• Languages: English
• ISSNs: 0192-8651

Abstract

Abstract : Hydrodynamic interactions (HI) are incorporated into Langevin dynamics of the Cα ‐based protein model using the Truncated Expansion approximation (TEA) to the Rotne–Prager–Yamakawa diffusion tensor. Computational performance of the obtained GPU realization demonstrates the model's capability for describing protein systems of varying complexity (10 2 –10 5 residues), including biological particles (filaments, virus shells). Comparison of numerical accuracy of the TEA versus exact description of HI reveals similar results for the kinetics and thermodynamics of protein unfolding. The HI speed up and couple biomolecular transitions through cross‐communication among protein domains, which result in more collective displacements of structure elements governed by more deterministic (less variable) dynamics. The force‐extension/deformation spectra from nanomanipulations in silico exhibit sharper force signals that match well the experimental profiles. Hence, biomolecular simulations without HI overestimate the role of tension/stress fluctuations. Our findings establish the importance of incorporating implicit water‐mediated many‐body effects into theoretical modeling of dynamic processes involving biomolecules. © 2016 Wiley Periodicals, Inc. Abstract : Theoretical modeling of dynamic processes involving protein assemblies requires an accurate description of their physico‐chemical properties, which, due to the finite rates of these processes, are influenced by hydrodynamic interactions among their structural elements. Hydrodynamic coupling is incorporated into the Cα–based protein model on GPUs using the Truncated Expansion of Rotne–Prager–Yamakawa diffusion tensor. The results of nanomanipulations in silico show the importance of implicit water‐mediated many‐body effects in describing dynamic transitions in protein assemblies.