Assessing models of force-dependent unbinding rates via infrequent metadynamics

Peña Ccoa, Willmor J.; Hocky, Glen M.

doi:10.1063/5.0081078

Title: Assessing models of force-dependent unbinding rates via infrequent metadynamics

Journal Article · Fri Mar 25 00:00:00 EDT 2022 · Journal of Chemical Physics

DOI:https://doi.org/10.1063/5.0081078· OSTI ID:1862010

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New York Univ. (NYU), NY (United States)

Protein–ligand interactions are crucial for a wide range of physiological processes. Many cellular functions result in these non-covalent “bonds” being mechanically strained, and this can be integral to proper cellular function. Broadly, two classes of force dependence have been observed—slip bonds, where the unbinding rate increases, and catch bonds, where the unbinding rate decreases. Despite much theoretical work, we cannot predict for which protein–ligand pairs, pulling coordinates, and forces a particular rate dependence will appear. Here, we assess the ability of MD simulations combined with enhanced sampling techniques to probe the force dependence of unbinding rates. We show that the infrequent metadynamics technique correctly produces both catch and slip bonding kinetics for model potentials. We then apply it to the well-studied case of a buckyball in a hydrophobic cavity, which appears to exhibit an ideal slip bond. Finally, we compute the force-dependent unbinding rate of biotin–streptavidin. Here, the complex nature of the unbinding process causes the infrequent metadynamics method to begin to break down due to the presence of unbinding intermediates, despite the use of a previously optimized sampling coordinate. Allowing for this limitation, a combination of kinetic and free energy computations predicts an overall slip bond for larger forces consistent with prior experimental results although there are substantial deviations at small forces that require further investigation. Furthermore, this work demonstrates the promise of predicting force-dependent unbinding rates using enhanced sampling MD techniques while also revealing the methodological barriers that must be overcome to tackle more complex targets in the future.

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Research Organization:: New York Univ. (NYU), NY (United States); Parallel Works Inc., Chicago, IL (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: SC0019695

OSTI ID:: 1862010

Alternate ID(s):: OSTI ID: 1856621; OSTI ID: 2310261

Journal Information:: Journal of Chemical Physics, Vol. 156, Issue 12; ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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