QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs
dc.contributor.author | Smaili, Fatima Zohra | |
dc.contributor.author | Tian, Shuye | |
dc.contributor.author | Roy, Ambrish | |
dc.contributor.author | Alazmi, Meshari | |
dc.contributor.author | Arold, Stefan T. | |
dc.contributor.author | Mukherjee, Srayanta | |
dc.contributor.author | Hefty, P. Scott | |
dc.contributor.author | Chen, Wei | |
dc.contributor.author | Gao, Xin | |
dc.date.accessioned | 2022-10-26T21:11:01Z | |
dc.date.available | 2022-10-26T21:11:01Z | |
dc.date.issued | 2021-02-23 | |
dc.identifier.citation | Smaili, Fatima Zohra et al. “QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs.” Genomics, proteomics & bioinformatics vol. 19,6 (2021): 998-1011. doi:10.1016/j.gpb.2021.02.001 | en_US |
dc.identifier.uri | http://hdl.handle.net/1808/33628 | |
dc.description.abstract | The number of available protein sequences in public databases is increasing exponentially. However, a significant percentage of these sequences lack functional annotation, which is essential for the understanding of how biological systems operate. Here, we propose a novel method, Quantitative Annotation of Unknown STructure (QAUST), to infer protein functions, specifically Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. QAUST uses three sources of information: structure information encoded by global and local structure similarity search, biological network information inferred by protein–protein interaction data, and sequence information extracted from functionally discriminative sequence motifs. These three pieces of information are combined by consensus averaging to make the final prediction. Our approach has been tested on 500 protein targets from the Critical Assessment of Functional Annotation (CAFA) benchmark set. The results show that our method provides accurate functional annotation and outperforms other prediction methods based on sequence similarity search or threading. We further demonstrate that a previously unknown function of human tripartite motif-containing 22 (TRIM22) protein predicted by QAUST can be experimentally validated. | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2021 The Authors. Published by Elsevier B.V. and Science Press on behalf of Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. This is an open access article under the CC BY-NC-ND license. | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0 | en_US |
dc.subject | Protein function prediction | en_US |
dc.subject | GO term | en_US |
dc.subject | EC number | en_US |
dc.subject | Protein structure similarity | en_US |
dc.subject | Functionally discriminative motif | en_US |
dc.title | QAUST: Protein Function Prediction Using Structure Similarity, Protein Interaction, and Functional Motifs | en_US |
dc.type | Article | en_US |
kusw.kuauthor | Hefty, P. Scott | |
kusw.kudepartment | Molecular Bioscience | en_US |
dc.identifier.doi | 10.1016/j.gpb.2021.02.001 | en_US |
kusw.oaversion | Scholarly/refereed, publisher version | en_US |
kusw.oapolicy | This item meets KU Open Access policy criteria. | en_US |
dc.identifier.pmid | PMC9403031 | en_US |
dc.rights.accessrights | openAccess | en_US |
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Except where otherwise noted, this item's license is described as: © 2021 The Authors. Published by Elsevier B.V. and Science Press on behalf of Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China. This is an open access article under the CC BY-NC-ND license.