title: Assessing the potential of atomistic molecular dynamics simulations to probe reversible protein-protein recognition and binding.
abstract: Protein-protein recognition and binding are governed by diffusion, noncovalent forces and conformational flexibility, entangled in a way that only molecular dynamics simulations can dissect at high resolution. Here we exploited ubiquitin's noncovalent dimerization equilibrium to assess the potential of atomistic simulations to reproduce reversible protein-protein binding, by running submicrosecond simulations of systems with multiple copies of the protein at millimolar concentrations. The simulations essentially fail because they lead to aggregates, yet they reproduce some specificity in the binding interfaces as observed in known covalent and noncovalent ubiquitin dimers. Following similar observations in literature we hint at electrostatics and water descriptions as the main liable force field elements, and propose that their optimization should consider observables relevant to multi-protein systems and unfolded proteins. Within limitations, analysis of binding events suggests salient features of protein-protein recognition and binding, to be retested with improved force fields. Among them, that specific configurations of relative direction and orientation seem to trigger fast binding of two molecules, even over 50 Å distances; that conformational selection can take place within surface-to-surface distances of 10 to 40 Å i.e. well before actual intermolecular contact; and that establishment of contacts between molecules further locks their conformations and relative orientations.
authors.affiliation: Laboratory for Biomolecular Modeling, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: Luciano A
authors.initials: LA
authors.lastname: Abriata
authors.affiliation: Laboratory for Biomolecular Modeling, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
authors.forename: Matteo
authors.initials: M
authors.lastname: Dal Peraro
mesh_terms: D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D011487:Protein Conformation; D060066:Protein Interaction Maps / Q000235:genetics*; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics; D025801:Ubiquitin / Q000737:chemistry; D014867:Water / Q000737:chemistry
chemical_list: D011506:Proteins; D025801:Ubiquitin; D014867:Water