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An Evolutionary Conservation & Rigidity Analysis Machine Learning Approach for Detecting Critical Protein Residues

Published: 22 September 2013 Publication History

Abstract

In proteins, certain amino acids may play a critical role in determining their structure and function. Examples include flexible regions which allow domain motions, and highly conserved residues on functional interfaces which play a role in binding and interaction with other proteins. Detecting these regions facilitates the analysis and simulation of protein rigidity and conformational changes, and aids in characterizing protein-protein binding. We present a machine-learning based method for the analysis and prediction of critical residues in proteins. We combine amino-acid specific information and data obtained by two complementary methods. One method, KINARI-Mutagen, performs graph-based analysis to find rigid clusters of amino acids in a protein, and the other method uses evolutionary conservation scores to find functional interfaces in proteins. We devised a machine learning model that combines both methods, in addition to amino acid type and solvent accessible surface area, to a dataset of proteins with experimentally known critical residues, and were able to achieve over 77% prediction rate, more than either of the methods separately.

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  • (2018)Low Rank Smoothed Sampling Methods for Identifying Impactful Pairwise MutationsProceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3233547.3233714(681-686)Online publication date: 15-Aug-2018
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  1. An Evolutionary Conservation & Rigidity Analysis Machine Learning Approach for Detecting Critical Protein Residues

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    cover image ACM Conferences
    BCB'13: Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics
    September 2013
    987 pages
    ISBN:9781450324342
    DOI:10.1145/2506583
    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 ACM 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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    Publication History

    Published: 22 September 2013

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    Author Tags

    1. Critical residues
    2. conservation
    3. machine learning
    4. rigidity

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    September 22 - 25, 2013
    Wshington DC, USA

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    BCB'13 Paper Acceptance Rate 43 of 148 submissions, 29%;
    Overall Acceptance Rate 254 of 885 submissions, 29%

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    Cited By

    View all
    • (2019)Robust Prediction of Single and Multiple Point Protein Mutations Stability ChangesBiomolecules10.3390/biom1001006710:1(67)Online publication date: 31-Dec-2019
    • (2018)Predicting the Effect of Single and Multiple Mutations on Protein Structural StabilityMolecules10.3390/molecules2302025123:2(251)Online publication date: 27-Jan-2018
    • (2018)Low Rank Smoothed Sampling Methods for Identifying Impactful Pairwise MutationsProceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3233547.3233714(681-686)Online publication date: 15-Aug-2018
    • (2018)Ensemble Voting Schemes that Improve Machine Learning Models for Predicting the Effects of Protein MutationsProceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics10.1145/3233547.3233606(211-219)Online publication date: 15-Aug-2018
    • (2017)ProMuteHTProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3116251(655-660)Online publication date: 20-Aug-2017
    • (2017)Predicting the Effect of Point Mutations on Protein Structural StabilityProceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics10.1145/3107411.3107492(247-252)Online publication date: 20-Aug-2017
    • (2016)Methods for Detecting Critical Residues in ProteinsIn Vitro Mutagenesis10.1007/978-1-4939-6472-7_15(227-242)Online publication date: 6-Oct-2016

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