Scoring a diverse set of high-quality docked conformations: a metascore based on electrostatic and desolvation interactions.
Predicting protein-protein interactions involves sampling and scoring docked conformations. Barring some large structural rearrangement, rapidly sampling the space of docked conformations is now a real possibility, and the limiting step for the successful prediction of protein interactions is the scoring function used to reduce the space of conformations from billions to a few, and eventually one high affinity complex. An atomic level free-energy scoring function that estimates in units of kcal/mol both electrostatic and desolvation interactions (plus van der Waals if appropriate) of protein-protein docked conformations is used to rerank the blind predictions (860 in total) submitted for six targets to the community-wide Critical Assessment of PRediction of Interactions (CAPRI; http://capri.ebi.ac.uk). We found that native-like models often have varying intermolecular contacts and atom clashes, making unlikely that one can construct a universal function that would rank all these models as native-like. Nevertheless, our scoring function is able to consistently identify the native-like complexes as those with the lowest free energy for the individual models of 16 (out of 17) human predictors for five of the targets, while at the same time the modelers failed to do so in more than half of the cases. The scoring of high-quality models developed by a wide variety of methods and force fields confirms that electrostatic and desolvation forces are the dominant interactions determining the bound structure. The CAPRI experiment has shown that modelers can predict valuable models of protein-protein complexes, and improvements in scoring functions should soon solve the docking problem for complexes whose backbones do not change much upon binding. A scoring server and programs are available at http://structure.pitt.edu.
Camacho
Carlos J
CJ
Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA. ccamacho@pitt.edu
Ma
Hui
H
Champ
P Christoph
PC
D008954:Models, Biological; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D012997:Solvents / Q000737:chemistry*; D055672:Static Electricity
D011506:Proteins; D012997:Solvents