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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/41940
Title: AnkPlex: Algorithmic structure for refinement of near-native ankyrin-protein docking
Authors: Tanchanok Wisitponchai
Watshara Shoombuatong
Vannajan Sanghiran Lee
Kuntida Kitidee
Chatchai Tayapiwatana
Chiang Mai University
Mahidol University
Commission on Higher Education
University of Malaya
Keywords: Biochemistry, Genetics and Molecular Biology;Computer Science
Issue Date: 19-Apr-2017
Citation: BMC Bioinformatics. Vol.18, No.1 (2017)
Abstract: © 2017 The Author(s). Background: Computational analysis of protein-protein interaction provided the crucial information to increase the binding affinity without a change in basic conformation. Several docking programs were used to predict the near-native poses of the protein-protein complex in 10 top-rankings. The universal criteria for discriminating the near-native pose are not available since there are several classes of recognition protein. Currently, the explicit criteria for identifying the near-native pose of ankyrin-protein complexes (APKs) have not been reported yet. Results: In this study, we established an ensemble computational model for discriminating the near-native docking pose of APKs named "AnkPlex". A dataset of APKs was generated from seven X-ray APKs, which consisted of 3 internal domains, using the reliable docking tool ZDOCK. The dataset was composed of 669 and 44,334 near-native and non-near-native poses, respectively, and it was used to generate eleven informative features. Subsequently, a re-scoring rank was generated by AnkPlex using a combination of a decision tree algorithm and logistic regression. AnkPlex achieved superior efficiency with ≥1 near-native complexes in the 10 top-rankings for nine X-ray complexes compared to ZDOCK, which only obtained six X-ray complexes. In addition, feature analysis demonstrated that the van der Waals feature was the dominant near-native pose out of the potential ankyrin-protein docking poses. Conclusion: The AnkPlex model achieved a success at predicting near-native docking poses and led to the discovery of informative characteristics that could further improve our understanding of the ankyrin-protein complex. Our computational study could be useful for predicting the near-native poses of binding proteins and desired targets, especially for ankyrin-protein complexes. The AnkPlex web server is freely accessible at http://ankplex.ams.cmu.ac.th.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018515149&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/41940
ISSN: 14712105
Appears in Collections:Scopus 2016-2017

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