KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units.
KinFams: De-Novo Classification of Protein Kinases Using CATH Functional Units.
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Kinfams:使用CATH功能单元对蛋白激酶进行脱离蛋白质激酶的分类。
DOI:
10.3390/biom13020277
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发表时间:
2023-02-02
期刊:
影响因子:
5.5
通讯作者:
中科院分区:
文献类型:
--
作者:
Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence homology); however, very few systematically classify functional families (FunFams) comprising evolutionary relatives that share similar functional properties. We have developed the FunFam-MARC (Multidomain ARchitecture-based Clustering) protocol, which uses multi-domain architectures of protein kinases and specificity-determining residues for functional family classification. FunFam-MARC predicts 2210 kinase functional families (KinFams), which have increased functional coherence, in terms of EC annotations, compared to the widely used KinBase classification. Our protocol provides a comprehensive classification for kinase sequences from >10,000 organisms. We associate human KinFams with diseases and drugs and identify 28 druggable human KinFams, i.e., enriched in clinically approved drugs. Since relatives in the same druggable KinFam tend to be structurally conserved, including the drug-binding site, these KinFams may be valuable for shortlisting therapeutic targets. Information on the human KinFams and associated 3D structures from AlphaFold2 are provided via our CATH FTP website and Zenodo. This gives the domain structure representative of each KinFam together with information on any drug compounds available. For 32% of the KinFams, we provide information on highly conserved residue sites that may be associated with specificity.
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影响因子:
3.7
作者:
Gosal G;Kochut KJ;Kannan N
通讯作者:
Kannan N
影响因子:
64.8
作者:
Jumper J;Evans R;Pritzel A;Green T;Figurnov M;Ronneberger O;Tunyasuvunakool K;Bates R;Žídek A;Potapenko A;Bridgland A;Meyer C;Kohl SAA;Ballard AJ;Cowie A;Romera-Paredes B;Nikolov S;Jain R;Adler J;Back T;Petersen S;Reiman D;Clancy E;Zielinski M;Steinegger M;Pacholska M;Berghammer T;Bodenstein S;Silver D;Vinyals O;Senior AW;Kavukcuoglu K;Kohli P;Hassabis D
通讯作者:
Hassabis D
DOI:
10.1093/bioinformatics/bts565
发表时间:
2012-12-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者:
Li W
DOI:
10.1093/bioinformatics/btn214
发表时间:
2008-07-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Capra JA;Singh M
通讯作者:
Singh M
影响因子:
16.6
作者:
Kaltheuner IH;Anand K;Moecking J;Düster R;Wang J;Gray NS;Geyer M
通讯作者:
Geyer M