dbMPIKT: A database of kinetic and thermodynamic mutant protein interactions

Liu, Q; Chen, P; Wang, B; Zhang, J; Li, J

dbMPIKT: A database of kinetic and thermodynamic mutant protein interactions

Liu, Q Chen, P Wang, B Zhang, J Li, J

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Publication Type:: Journal Article
Citation:: BMC Bioinformatics, 2018, 19 (1)
Issue Date:: 2018-11-27

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Field	Value	Language
dc.contributor.author	Liu, Q	en_US
dc.contributor.author	Chen, P	en_US
dc.contributor.author	Wang, B	en_US
dc.contributor.author	Zhang, J	en_US
dc.contributor.author	Li, J https://orcid.org/0000-0003-1833-7413	en_US
dc.date.available	2018-11-13	en_US
dc.date.issued	2018-11-27	en_US
dc.identifier.citation	BMC Bioinformatics, 2018, 19 (1)	en_US
dc.identifier.uri	http://hdl.handle.net/10453/131364
dc.description.abstract	© 2018 The Author(s). Background: Protein-protein interactions (PPIs) play important roles in biological functions. Studies of the effects of mutants on protein interactions can provide further understanding of PPIs. Currently, many databases collect experimental mutants to assess protein interactions, but most of these databases are old and have not been updated for several years. Results: To address this issue, we manually curated a kinetic and thermodynamic database of mutant protein interactions (dbMPIKT) that is freely accessible at our website. This database contains 5291 mutants in protein interactions collected from previous databases and the literature published within the last three years. Furthermore, some data analysis, such as mutation number, mutation type, protein pair source and network map construction, can be performed online. Conclusion: Our work can promote the study on PPIs, and novel information can be mined from the new database. Our database is available in http://DeepLearner.ahu.edu.cn/web/dbMPIKT/for use by all, including both academics and non-academics.	en_US
dc.relation.ispartof	BMC Bioinformatics	en_US
dc.relation.isbasedon	10.1186/s12859-018-2493-7	en_US
dc.subject.classification	Bioinformatics	en_US
dc.subject.mesh	Protein Binding	en_US
dc.subject.mesh	Kinetics	en_US
dc.subject.mesh	Mutation	en_US
dc.subject.mesh	Thermodynamics	en_US
dc.subject.mesh	Internet	en_US
dc.subject.mesh	Databases, Protein	en_US
dc.subject.mesh	Mutant Proteins	en_US
dc.subject.mesh	Protein Interaction Maps	en_US
dc.title	dbMPIKT: A database of kinetic and thermodynamic mutant protein interactions	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	19	en_US
utslib.for	080301 Bioinformatics Software	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	06 Biological Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	19	en_US

Abstract:

© 2018 The Author(s). Background: Protein-protein interactions (PPIs) play important roles in biological functions. Studies of the effects of mutants on protein interactions can provide further understanding of PPIs. Currently, many databases collect experimental mutants to assess protein interactions, but most of these databases are old and have not been updated for several years. Results: To address this issue, we manually curated a kinetic and thermodynamic database of mutant protein interactions (dbMPIKT) that is freely accessible at our website. This database contains 5291 mutants in protein interactions collected from previous databases and the literature published within the last three years. Furthermore, some data analysis, such as mutation number, mutation type, protein pair source and network map construction, can be performed online. Conclusion: Our work can promote the study on PPIs, and novel information can be mined from the new database. Our database is available in http://DeepLearner.ahu.edu.cn/web/dbMPIKT/for use by all, including both academics and non-academics.

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http://hdl.handle.net/10453/131364