A computational tool to infer enzyme activity using post-translational modification profiling data
Abstract Enzymes play a pivotal role in orchestrating complex cellular responses to external stimuli and environmental changes through signal transduction pathways. Despite their crucial roles, measuring enzyme activities is typically indirect and performed on a smaller scale, unlike protein abundan...
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Nature Portfolio
2025-01-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-025-07548-4 |
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| author | Dehui Kong Aijun Zhang Ling Li Zuo-Fei Yuan Yingxue Fu Long Wu Ashutosh Mishra Anthony A. High Junmin Peng Xusheng Wang |
| author_facet | Dehui Kong Aijun Zhang Ling Li Zuo-Fei Yuan Yingxue Fu Long Wu Ashutosh Mishra Anthony A. High Junmin Peng Xusheng Wang |
| author_sort | Dehui Kong |
| collection | DOAJ |
| description | Abstract Enzymes play a pivotal role in orchestrating complex cellular responses to external stimuli and environmental changes through signal transduction pathways. Despite their crucial roles, measuring enzyme activities is typically indirect and performed on a smaller scale, unlike protein abundance measured by high-throughput proteomics. Moreover, it is challenging to derive the activity of enzymes from proteome-wide post-translational modification (PTM) profiling data. To address this challenge, we introduce enzyme activity inference with structural equation modeling under the JUMP umbrella (JUMPsem), a novel computational tool designed to infer enzyme activity using PTM profiling data. We demonstrate that the JUMPsem program enables estimating kinase activities using phosphoproteome data, ubiquitin E3 ligase activities from the ubiquitinome, and histone acetyltransferase (HAT) activities based on the acetylome. In addition, JUMPsem is capable of establishing novel enzyme-substrate relationships through searching motif sequences. JUMPsem outperforms widely used kinase activity tools, such as IKAP and KSEA, in terms of the number of kinases and the computational speed. The JUMPsem program is scalable and publicly available as an open-source R package and user-friendly web-based R/Shiny app. Collectively, JUMPsem provides an improved tool for inferring protein enzyme activities, potentially facilitating targeted drug development. |
| format | Article |
| id | doaj-art-bcee18af6025428796dc249b3dbe544d |
| institution | Kabale University |
| issn | 2399-3642 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj-art-bcee18af6025428796dc249b3dbe544d2025-01-26T12:48:08ZengNature PortfolioCommunications Biology2399-36422025-01-01811810.1038/s42003-025-07548-4A computational tool to infer enzyme activity using post-translational modification profiling dataDehui Kong0Aijun Zhang1Ling Li2Zuo-Fei Yuan3Yingxue Fu4Long Wu5Ashutosh Mishra6Anthony A. High7Junmin Peng8Xusheng Wang9Department of Genetics, Genomics and Informatics, University of Tennessee Health Science CenterDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science CenterDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science CenterCenter for Proteomics and Metabolomics, St. Jude Children’s Research HospitalCenter for Proteomics and Metabolomics, St. Jude Children’s Research HospitalCenter for Proteomics and Metabolomics, St. Jude Children’s Research HospitalCenter for Proteomics and Metabolomics, St. Jude Children’s Research HospitalCenter for Proteomics and Metabolomics, St. Jude Children’s Research HospitalDepartment of Structural Biology, St. Jude Children’s Research HospitalDepartment of Genetics, Genomics and Informatics, University of Tennessee Health Science CenterAbstract Enzymes play a pivotal role in orchestrating complex cellular responses to external stimuli and environmental changes through signal transduction pathways. Despite their crucial roles, measuring enzyme activities is typically indirect and performed on a smaller scale, unlike protein abundance measured by high-throughput proteomics. Moreover, it is challenging to derive the activity of enzymes from proteome-wide post-translational modification (PTM) profiling data. To address this challenge, we introduce enzyme activity inference with structural equation modeling under the JUMP umbrella (JUMPsem), a novel computational tool designed to infer enzyme activity using PTM profiling data. We demonstrate that the JUMPsem program enables estimating kinase activities using phosphoproteome data, ubiquitin E3 ligase activities from the ubiquitinome, and histone acetyltransferase (HAT) activities based on the acetylome. In addition, JUMPsem is capable of establishing novel enzyme-substrate relationships through searching motif sequences. JUMPsem outperforms widely used kinase activity tools, such as IKAP and KSEA, in terms of the number of kinases and the computational speed. The JUMPsem program is scalable and publicly available as an open-source R package and user-friendly web-based R/Shiny app. Collectively, JUMPsem provides an improved tool for inferring protein enzyme activities, potentially facilitating targeted drug development.https://doi.org/10.1038/s42003-025-07548-4 |
| spellingShingle | Dehui Kong Aijun Zhang Ling Li Zuo-Fei Yuan Yingxue Fu Long Wu Ashutosh Mishra Anthony A. High Junmin Peng Xusheng Wang A computational tool to infer enzyme activity using post-translational modification profiling data Communications Biology |
| title | A computational tool to infer enzyme activity using post-translational modification profiling data |
| title_full | A computational tool to infer enzyme activity using post-translational modification profiling data |
| title_fullStr | A computational tool to infer enzyme activity using post-translational modification profiling data |
| title_full_unstemmed | A computational tool to infer enzyme activity using post-translational modification profiling data |
| title_short | A computational tool to infer enzyme activity using post-translational modification profiling data |
| title_sort | computational tool to infer enzyme activity using post translational modification profiling data |
| url | https://doi.org/10.1038/s42003-025-07548-4 |
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