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Compare local pocket and global protein structure models by small structure patterns

Published: 09 September 2015 Publication History

Abstract

Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed.
In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11; 669 pairs of predicted and native local protein pocket models from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient.
Source codes and executables are publicly available at http://www.cbrc.kaust.edu.sa/prosta/

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Cited By

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  • (2019)Homologous Protein DetectionEncyclopedia of Bioinformatics and Computational Biology10.1016/B978-0-12-809633-8.90698-8(697-705)Online publication date: 2019
  • (2018)A Novel Geometry-Based Approach to Infer Protein Interface SimilarityScientific Reports10.1038/s41598-018-26497-z8:1Online publication date: 29-May-2018
  • (2016)CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure predictionBioinformatics10.1093/bioinformatics/btw27132:12(i332-i340)Online publication date: 15-Jun-2016

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cover image ACM Conferences
BCB '15: Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics
September 2015
683 pages
ISBN:9781450338530
DOI:10.1145/2808719
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 09 September 2015

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Author Tags

  1. critical assessment of techniques for protein structure prediction (CASP)
  2. optimal superposition
  3. pocket
  4. protein
  5. protein pocket
  6. protein structure
  7. quality assessment of predicted protein structures
  8. structure

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  • King Abdullah University of Science and Technology (KAUST)

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BCB '15
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BCB '15 Paper Acceptance Rate 48 of 141 submissions, 34%;
Overall Acceptance Rate 254 of 885 submissions, 29%

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Cited By

View all
  • (2019)Homologous Protein DetectionEncyclopedia of Bioinformatics and Computational Biology10.1016/B978-0-12-809633-8.90698-8(697-705)Online publication date: 2019
  • (2018)A Novel Geometry-Based Approach to Infer Protein Interface SimilarityScientific Reports10.1038/s41598-018-26497-z8:1Online publication date: 29-May-2018
  • (2016)CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure predictionBioinformatics10.1093/bioinformatics/btw27132:12(i332-i340)Online publication date: 15-Jun-2016

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