Enhanced sampling of protein conformational states for dynamic cross-docking within the protein-protein docking server SwarmDock.
journal contributionposted on 24.07.2020, 13:02 by Mieczyslaw Torchala, Tereza Gerguri, Raphael AG Chaleil, Patrick Gordon, Francis Russell, Miriam Keshani, Paul A Bates
The formation of specific protein-protein interactions is often key to a protein's function. During complex formation, each protein component will undergo a change of conformational state, for some these changes are relatively small and reside primarily at the sidechain level; however, others may display notable backbone adjustments. One of the classic problems in the protein docking field is to be able to a priori predict the extent of such conformational changes. In this work, we investigated three protocols to find the most suitable input structure conformations for cross-docking, including a robust sampling approach in normal mode space. Counterintuitively, knowledge of the theoretically best combination of normal modes for unbound-bound transition doesn't always lead to the best results. We used a novel spatial partitioning library, Aether Engine (see Supplementary Materials), to efficiently search the conformational states of 56 receptor/ligand pairs, including a recent CAPRI target, in a systematic manner and selected diverse conformations as input to our automated docking server, SwarmDock; a server that allows moderate conformational adjustments during the docking process. In essence, here we present a dynamic cross-docking protocol, which when benchmarked against the simple simpler approach of just docking the unbound components, shows a 10% uplift in quality of the top docking pose. This article is protected by copyright. All rights reserved.
Crick (Grant ID: 10316, Grant title: Bates FC001003)
Aether EngineCAPRIDFIRE2SwarmDockconformational selectionconformational states space samplingcrossdockinginduced fitnormal modesprotein-protein dockingprotein-protein interactionscross-dockingBates FC001003Bioinformatics06 Biological Sciences08 Information and Computing Sciences01 Mathematical Sciences