Mechanisms of nanonewton mechanostability in a protein complex revealed by molecular dynamics simulations and single-molecule force spectrosco

Can molecular dynamics simulations predict the mechanical behavior of protein complexes? Can simulations decipher the role of protein domains of unknown function in large macromolecular complexes? Here, we employ a wide-sampling computational approach to demonstrate that molecular dynamics simulations, when carefully performed and combined with single-molecule atomic force spectroscopy experiments, can predict and explain the behavior of highly mechanostable protein complexes. As a test case, we studied a previously unreported homologue from Ruminococcus flavefaciens called X-module-Dockerin (XDoc) bound to its partner Cohesin (Coh). By performing dozens of short simulation replicas near the rupture event, and analyzing dynamic network fluctuations, we were able to generate large simulation statistics and directly compare them with experiments to uncover the mechanisms involved in mechanical stabilization. Our single-molecule force spectroscopy experiments show that the XDoc-Coh homologue complex withstands forces up to 1 nN at loading rates of 10(5) pN/s. Our simulation results reveal that this remarkable mechanical stability is achieved by a protein architecture that directs molecular deformation along paths that run perpendicular to the pulling axis. The X-module was found to play a crucial role in shielding the adjacent protein complex from mechanical rupture. These mechanisms of protein mechanical stabilization have potential applications in biotechnology for the development of systems exhibiting shear enhanced adhesion or tunable mechanics141371475214763sem informaçãosem informaçãoWe would like to thank Prof. Klaus Schulten (in memoriam), whose contribution to this work, particularly at its early stages, is of inestimable value. Support for this work was provided by the EU seventh Framework Programme NMP4-SL-2013-604530 (CellulosomePlus), the Nanosystems Initiative Munich and the ERC Advanced Grant CelluFuel. M.A.N. acknowledges support from an ERC Starting Grant (#715207). This work was supported by National Institutes of Health (NIH) Grant P41-GM104601, “Center for Macromolecular Modeling and Bioinformatics”. R.C.B. is partially supported by the National Science Foundation (NSF) Grant MCB-1616590, “Molecular Modeling of Bioenergetic Systems”, as well as the Energy Biosciences Institute. Equilibrium molecular dynamics simulations made use of ALCF/Mira and NERSC/Edison supercomputers as part of the DoE ALCC program. This research partially used resources of the Argonne Leadership Computing Facility (ALCF), which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. This research partially used resources of the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. Steered molecular dynamics simulations were performed on GPU-accelerated nodes of Blue Waters supercomputer as part of the Petascale Computational Resource (PRAC) Grant The Computational Microscope, which is supported by the National Science Foundation (Award Number ACI-1713784). The state of Illinois and the National Science Foundation (Awards OCI-0725070 and ACI-1238993) support Blue Waters sustained-petascale computing project. We thank Lukas F. Milles for providing the force curve analysis software, as well as Thomas Nicolaus and Angelika Kardinal for laboratory assistance. We thank Marcelo C. R. Melo for the help with SMD analysis and Maximilian Scheurer for the help with PyContac