Constraining redundancy to improve protein docking

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Predicting protein-protein complexes (protein docking) is an important factor for understanding the majority of biochemical processes. In general, protein docking algorithms search through a large number of possible relative placements of the interacting partners, filtering out the majority of the candidates in order to produce a manageable set of candidates that can be examined in greater detail. This is a sixdimensional search through three rotational degrees of freedom and three translational degrees of freedom of one partner (the probe) relative to the other (the target). The standard approach is to use a fixed step both for the rotation (typically 10° to 15°) and the translation (typically 1Å). Since proteins are not isotropic, a homogeneous rotational sampling can result in redundancies or excessive displacement of important atoms. A similar problem occurs in the translational sampling, since the small step necessary to find the optimal fit between the two molecules results in structures that differ by so little that they become redundant. In this paper we propose a constraint-based approach that improves the search by eliminating these redundancies and adapting the sampling to the size and shape of the proteins involved. A test on 217 protein complexes from the protein-protein Docking Benchmark Version 5 shows an increase of over 50% in the average number of non-degenerate acceptable models retained for the most difficult cases. Furthermore, for about 75% of the complexes in the benchmark, computation time is decreased by half, on average.

Original languageEnglish
Title of host publicationPrinciples and Practice of Constraint Programming - 22nd International Conference, CP 2016, Proceedings
EditorsM. Rueher
Place of PublicationCham, Switzerland
PublisherSpringer-Verlag
Pages721-732
Number of pages12
ISBN (Electronic)978-3-319-44953-1
ISBN (Print)978-331944952-4
DOIs
Publication statusPublished - 2016
Event22nd International Conference on Principles and Practice of Constraint Programming, CP 2016 - Toulouse, France
Duration: 5 Sep 20169 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer-Verlag
Volume9892 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Principles and Practice of Constraint Programming, CP 2016
CountryFrance
CityToulouse
Period5/09/169/09/16

Keywords

  • Constraints
  • Geometric search
  • Protein docking

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