Literature DB >> 17243180

A protein-specifically adapted scoring function for the reranking of docking solutions.

Wolfgang Müller1, Heinrich Sticht.   

Abstract

In this work, we developed a protein-specifically adapted scoring function and applied it to the reranking of protein-protein docking solutions generated with a conventional docking program. The approach was validated using experimentally determined structures of the bacterial HPr-protein in complex with four structurally nonhomologous binding partners as an example. A sufficiently large data basis for the generation of protein-specifically adapted pair potentials was generated by modeling all orthologous complexes for each type of interaction resulting in a total of 224 complexes. The parameters for potential generation were systematically varied and resulted in a total of 66,132 different scoring functions that were tested for their ability of successful reranking of 1000 docking solutions generated from modeled structures of the unbound binding partners. Parameters that proved critical for the generation of good scoring functions were the distance cutoff used for the generation of the pair potential, and an additional cutoff that allows a proper weighting of conserved and nonconserved contacts in the interface. Compared to the original scoring function, application of this novel type of scoring functions resulted in a significant accumulation of acceptable docking solutions within the first 10 ranks. Depending on the type of complex investigated one to five acceptable complex geometries are found among the 10 highest-ranked solutions and for three of the four systems tested, an acceptable solution was placed on the first rank. (c) 2007 Wiley-Liss, Inc.

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Year:  2007        PMID: 17243180     DOI: 10.1002/prot.21310

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  4 in total

1.  Classification of heterodimer interfaces using docking models and construction of scoring functions for the complex structure prediction.

Authors:  Yuko Tsuchiya; Eiji Kanamori; Haruki Nakamura; Kengo Kinoshita
Journal:  Adv Appl Bioinform Chem       Date:  2009-09-22

2.  NPPD: A Protein-Protein Docking Scoring Function Based on Dyadic Differences in Networks of Hydrophobic and Hydrophilic Amino Acid Residues.

Authors:  Edward S C Shih; Ming-Jing Hwang
Journal:  Biology (Basel)       Date:  2015-03-24

3.  The scoring of poses in protein-protein docking: current capabilities and future directions.

Authors:  Iain H Moal; Mieczyslaw Torchala; Paul A Bates; Juan Fernández-Recio
Journal:  BMC Bioinformatics       Date:  2013-10-01       Impact factor: 3.169

4.  Classification and prediction of protein-protein interaction interface using machine learning algorithm.

Authors:  Subhrangshu Das; Saikat Chakrabarti
Journal:  Sci Rep       Date:  2021-01-19       Impact factor: 4.379

  4 in total

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