title: Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses.
abstract: The prediction of protein-protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state-of-the-art scoring functions (BACH-SixthSense, PIE/PISA and Rosetta) in discriminating finite-temperature ensembles of structures corresponding to the native state and to non-native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH-SixthSense and PIE/PISA perform better in distinguishing near-native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312-1320. © 2016 Wiley Periodicals, Inc.
authors.affiliation: SISSA, via Bonomea 265, Trieste, I-34136, Italy.
authors.forename: Edoardo
authors.initials: E
authors.lastname: Sarti
authors.affiliation: SISSA, via Bonomea 265, Trieste, I-34136, Italy.
authors.forename: Ivan
authors.initials: I
authors.lastname: Gladich
authors.affiliation: SISSA, via Bonomea 265, Trieste, I-34136, Italy.
authors.forename: Stefano
authors.initials: S
authors.lastname: Zamuner
authors.affiliation: Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale De Lausanne, Lausanne, Switzerland.
authors.forename: Bruno E
authors.initials: BE
authors.lastname: Correia
authors.affiliation: SISSA, via Bonomea 265, Trieste, I-34136, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Laio
mesh_terms: D048868:Adaptor Proteins, Signal Transducing / Q000737:chemistry*; D000465:Algorithms; D001665:Binding Sites; D006801:Humans; D015233:Models, Statistical; D062105:Molecular Docking Simulation; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D055503:Protein Multimerization; D017433:Protein Structure, Secondary; D012107:Research Design; D017415:Ribonucleoprotein, U5 Small Nuclear / Q000737:chemistry*; D012984:Software; D012997:Solvents / Q000737:chemistry
chemical_list: D048868:Adaptor Proteins, Signal Transducing; C120378:CD2BP2 protein, human; D017415:Ribonucleoprotein, U5 Small Nuclear; D012997:Solvents
keywords: BACH-SixthSense; MD; PIE/PISA; Rosetta; comparative study; native discrimination; protein-protein interaction; refinement; rigid docking; scoring function