Details

Autor(en) / Beteiligte

• Bradley, David
• Viéitez, Cristina
• Rajeeve, Vinothini
• Selkrig, Joel
• Cutillas, Pedro R.
• Beltrao, Pedro

Titel

Sequence and Structure-Based Analysis of Specificity Determinants in Eukaryotic Protein Kinases

Ist Teil von

• Cell reports (Cambridge), 2021-01, Vol.34 (2), p.108602-108602, Article 108602

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2021

Quelle

Free E-Journal (出版社公開部分のみ）

Beschreibungen/Notizen

• Protein kinases lie at the heart of cell-signaling processes and are often mutated in disease. Kinase target recognition at the active site is in part determined by a few amino acids around the phosphoacceptor residue. However, relatively little is known about how most preferences are encoded in the kinase sequence or how these preferences evolved. Here, we used alignment-based approaches to predict 30 specificity-determining residues (SDRs) for 16 preferences. These were studied with structural models and were validated by activity assays of mutant kinases. Cancer mutation data revealed that kinase SDRs are mutated more frequently than catalytic residues. We have observed that, throughout evolution, kinase specificity has been strongly conserved across orthologs but can diverge after gene duplication, as illustrated by the G protein-coupled receptor kinase family. The identified SDRs can be used to predict kinase specificity from sequence and aid in the interpretation of evolutionary or disease-related genomic variants. [Display omitted] •30 kinase specificity-determining residues (SDRs) predicted across 16 specificities•SDRs structurally rationalized and experimentally validated•SDRs often mutated in cancer, with different SDRs targeted in different specificities•Specificity conserved between orthologs, but SDRs can diverge between paralogs Kinase substrate preferences are partly determined by specificity determinants in the kinase domain. However, for many specificities, the determinant residues are unknown. Bradley et al. used a sequence-based approach to predict specificity determinants across many kinases. The residues studied will aid in the interpretation of disease and evolutionary variants.