Phosphoproteomics Data-Driven Integrative Analysis of Autophosphorylation Sites in the Human Kinome

Many kinases are known to homo- or hetero-merize and phosphorylate themselves or each other. Phosphorylation by itself (autophosphorylation) is mechanistically perceived as either cis- or trans-interactions. Identification of autophosphorylation sites in kinases provides an opportunity to assess the activity of the kinome in phosphoproteome datasets as an efficient indicator of kinase activity. In order to predict kinase activity-associated autophosphorylation sites, we first encompassed the currently reported homodimeric interactions between kinases from various sources. Subsequently, we accounted for the autophosphorylation sites in kinases that are predicted by phosphomotif screening approaches, in vitro kinase assays, and those perceived based on phosphomotif mutant analysis. Together, we identified 4184 autophosphorylation sites in 386 kinases, and among them, 315 kinases were reported with homodimeric protein–protein interactions. Furthermore, we analysed 361 kinases that harbor multiple autophosphorylation sites and 25 kinases with a single autophosphosite based on contemporary kinase–substrate interactions. Among the 386 kinases, autophosphosites for 17 kinases were derived through high-throughput or low-throughput approaches, and for 80 kinases, they were predicted based on their phosphomotif analysis. The remaining 289 were based on predictions by multiple tools or were reported in more than one dataset. There were many instances in which, although one auto-phosphorylation site was reported, multiple other sites were also predicted. In this regard, we analysed the instances of phosphosites in kinases that are already associated with the induction or inhibition of kinase activity and identified 223 kinases with one or more sites with functional association. To evaluate their potential as auto-phosphorylation sites, we systematically assembled 1572 profiles and 978 differential cellular phosphoproteome datasets. Subsequently, we accounted for the frequency of co-detection or co-differential regulation of these autophosphosites with multiple kinase activity-associated sites within each kinase and further accounted for their known/predicted substrate phosphorylation sites. Together, we provide a reference compendium of autophosphorylation sites secluded in the human kinome and their co-regulation with substrates based on global phosphoproteome datasets, AutoPhosDb. As indicators of kinase activity, these phosphosites in kinases would serve as a surrogate to enrich the active kinases and their potential substrate-specificity in phosphoproteome datasets.

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Journal
International Journal of Molecular Sciences
Published
2026-07-28
DOI
https://doi.org/10.3390/ijms27156745
Primary Topic
Bioinformatics and Genomic Networks
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article
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article

Phosphoproteomics Data-Driven Integrative Analysis of Autophosphorylation Sites in the Human Kinome

Rajesh Raju, Mahammad Nisar, Prashant Kumar Modi, Radul R Dev et al.
International Journal of Molecular Sciences
Bioinformatics and Genomic Networks
article

Phosphoproteomics Data-Driven Integrative Analysis of Autophosphorylation Sites in the Human Kinome

Rajesh Raju, Mahammad Nisar, Prashant Kumar Modi, Radul R Dev, Alimath Sambreena, Athira Perunelly Gopalakrishnan, Sowmya Soman
article en

Abstract

Many kinases are known to homo- or hetero-merize and phosphorylate themselves or each other. Phosphorylation by itself (autophosphorylation) is mechanistically perceived as either cis- or trans-interactions. Identification of autophosphorylation sites in kinases provides an opportunity to assess the activity of the kinome in phosphoproteome datasets as an efficient indicator of kinase activity. In order to predict kinase activity-associated autophosphorylation sites, we first encompassed the currently reported homodimeric interactions between kinases from various sources. Subsequently, we accounted for the autophosphorylation sites in kinases that are predicted by phosphomotif screening approaches, in vitro kinase assays, and those perceived based on phosphomotif mutant analysis. Together, we identified 4184 autophosphorylation sites in 386 kinases, and among them, 315 kinases were reported with homodimeric protein–protein interactions. Furthermore, we analysed 361 kinases that harbor multiple autophosphorylation sites and 25 kinases with a single autophosphosite based on contemporary kinase–substrate interactions. Among the 386 kinases, autophosphosites for 17 kinases were derived through high-throughput or low-throughput approaches, and for 80 kinases, they were predicted based on their phosphomotif analysis. The remaining 289 were based on predictions by multiple tools or were reported in more than one dataset. There were many instances in which, although one auto-phosphorylation site was reported, multiple other sites were also predicted. In this regard, we analysed the instances of phosphosites in kinases that are already associated with the induction or inhibition of kinase activity and identified 223 kinases with one or more sites with functional association. To evaluate their potential as auto-phosphorylation sites, we systematically assembled 1572 profiles and 978 differential cellular phosphoproteome datasets. Subsequently, we accounted for the frequency of co-detection or co-differential regulation of these autophosphosites with multiple kinase activity-associated sites within each kinase and further accounted for their known/predicted substrate phosphorylation sites. Together, we provide a reference compendium of autophosphorylation sites secluded in the human kinome and their co-regulation with substrates based on global phosphoproteome datasets, AutoPhosDb. As indicators of kinase activity, these phosphosites in kinases would serve as a surrogate to enrich the active kinases and their potential substrate-specificity in phosphoproteome datasets.

International Journal of Molecular SciencesVol. 27(15)
Yenepoya University (IN)
Openalex Percentile: Top 14%
Bioinformatics and Genomic Networks
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