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Native fold and docking pose discrimination by the same residue-based scoring function

TitleNative fold and docking pose discrimination by the same residue-based scoring function
Publication TypeJournal Article
Year of Publication2015
AuthorsSarti, E, Granata, D, Seno, F, Trovato, A, Laio, A
JournalProteins: Structure, Function, and Bioinformatics
Pagination621 - 630
Date Published2015/04/01
ISBN Number0887-3585
Keywordsknowledge based potentials, molecular recognition, protein-protein interaction, quality assessment, structure prediction

Structure prediction and quality assessment are crucial steps in modeling native protein conformations. Statistical potentials are widely used in related algorithms, with different parametrizations typically developed for different contexts such as folding protein monomers or docking protein complexes. Here, we describe BACH-SixthSense, a single residue-based statistical potential that can be successfully employed in both contexts. BACH-SixthSense shares the same approach as BACH, a knowledge-based potential originally developed to score monomeric protein structures. A term that penalizes steric clashes as well as the distinction between polar and apolar sidechain-sidechain contacts are crucial novel features of BACH-SixthSense. The performance of BACH-SixthSense in discriminating correctly the native structure among a competing set of decoys is significantly higher than other state-of-the-art scoring functions, that were specifically trained for a single context, for both monomeric proteins (QMEAN, Rosetta, RF_CB_SRS_OD, benchmarked on CASP targets) and protein dimers (IRAD, Rosetta, PIE*PISA, HADDOCK, FireDock, benchmarked on 14 CAPRI targets). The performance of BACH-SixthSense in recognizing near-native docking poses within CAPRI decoy sets is good as well.

Short TitleProteins: Structure, Function, and Bioinformatics

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