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Article: Systematic characterization and prediction of post-translational modification cross-talk between proteins

TitleSystematic characterization and prediction of post-translational modification cross-talk between proteins
Authors
Issue Date2019
Citation
Bioinformatics, 2019, v. 35, n. 15, p. 2626-2633 How to Cite?
Abstract© 2018 The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. Motivation: Protein post-translational modifications (PTMs) regulate a wide range of cellular protein functions. Many PTM sites from the same (intra) or different (inter) proteins often cooperate with each other to perform a function, which is defined as PTM cross-talk. PTM cross-talk within proteins attracted great attentions in the past a few years. However, the inter-protein PTM cross-talk is largely under studied due to its large protein pair space and lack of a gold standard dataset, even though the PTM interplay between proteins is a key element in cell signaling and regulatory networks. Results: In this study, 199 inter-protein PTM cross-talk pairs in 82 pairs of human proteins were collected from literature, which to our knowledge is the first effort in compiling such dataset. By comparing with background PTM pairs from the same protein pairs, we found that inter-protein cross-talk PTM pairs have higher sequence co-evolution at both PTM residue and motif levels. Also, we found that cross-talk PTMs have higher co-modification across multiple species and 88 human tissues or conditions. Furthermore, we showed that these features are predictive for PTM cross-talk between proteins, and applied a random forest model to integrate these features with achieving an area under the receiver operating characteristic curve of 0.81 in 10-fold cross-validation, prevailing over using any single feature alone. Therefore, this method would be a valuable tool to identify inter-protein PTM cross-talk at proteome-wide scale. Availability and implementation: A web server for prioritization of both intra- and inter-protein PTM cross-talk candidates is at http://bioinfo.bjmu.edu.cn/ptm-x/. Python code for local computer is also freely available at https://github.com/huangyh09/PTM-X. Supplementary information: Supplementary data are available at Bioinformatics online.
Persistent Identifierhttp://hdl.handle.net/10722/280503
ISSN
2023 Impact Factor: 4.4
2023 SCImago Journal Rankings: 2.574
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHuang, Rongting-
dc.contributor.authorHuang, Yuanhua-
dc.contributor.authorGuo, Yubin-
dc.contributor.authorJi, Shangwei-
dc.contributor.authorLu, Ming-
dc.contributor.authorLi, Tingting-
dc.date.accessioned2020-02-17T14:34:11Z-
dc.date.available2020-02-17T14:34:11Z-
dc.date.issued2019-
dc.identifier.citationBioinformatics, 2019, v. 35, n. 15, p. 2626-2633-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/280503-
dc.description.abstract© 2018 The Author(s) 2018. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. Motivation: Protein post-translational modifications (PTMs) regulate a wide range of cellular protein functions. Many PTM sites from the same (intra) or different (inter) proteins often cooperate with each other to perform a function, which is defined as PTM cross-talk. PTM cross-talk within proteins attracted great attentions in the past a few years. However, the inter-protein PTM cross-talk is largely under studied due to its large protein pair space and lack of a gold standard dataset, even though the PTM interplay between proteins is a key element in cell signaling and regulatory networks. Results: In this study, 199 inter-protein PTM cross-talk pairs in 82 pairs of human proteins were collected from literature, which to our knowledge is the first effort in compiling such dataset. By comparing with background PTM pairs from the same protein pairs, we found that inter-protein cross-talk PTM pairs have higher sequence co-evolution at both PTM residue and motif levels. Also, we found that cross-talk PTMs have higher co-modification across multiple species and 88 human tissues or conditions. Furthermore, we showed that these features are predictive for PTM cross-talk between proteins, and applied a random forest model to integrate these features with achieving an area under the receiver operating characteristic curve of 0.81 in 10-fold cross-validation, prevailing over using any single feature alone. Therefore, this method would be a valuable tool to identify inter-protein PTM cross-talk at proteome-wide scale. Availability and implementation: A web server for prioritization of both intra- and inter-protein PTM cross-talk candidates is at http://bioinfo.bjmu.edu.cn/ptm-x/. Python code for local computer is also freely available at https://github.com/huangyh09/PTM-X. Supplementary information: Supplementary data are available at Bioinformatics online.-
dc.languageeng-
dc.relation.ispartofBioinformatics-
dc.titleSystematic characterization and prediction of post-translational modification cross-talk between proteins-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1093/bioinformatics/bty1033-
dc.identifier.pmid30590394-
dc.identifier.scopuseid_2-s2.0-85070724733-
dc.identifier.volume35-
dc.identifier.issue15-
dc.identifier.spage2626-
dc.identifier.epage2633-
dc.identifier.eissn1460-2059-
dc.identifier.isiWOS:000484378200013-

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