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Database (Oxford). 2014 Nov 19;2014:bau104. doi: 10.1093/database/bau104. Print 2014.

Kin-Driver: a database of driver mutations in protein kinases.

Author information

1
Fundación Instituto Leloir, Av. Patricias Argentinas 435. C1405BWE, Buenos Aires, Argentina, Pompeu Fabra University (UPF), Dept. de Tecnologies de la Informació i les Comunicacions. Tanger 122-140 08018, Barcelona, Spain, Computational Genomics Laboratory, Genetics Department, Institut de Biologia Universitat de Barcelona (IBUB), Facultat de Biologia, Av Diagonal 645 and Breakthrough Cancer Research Unit, Dexeus University Hospital, Sabino Arana 5-19, Barcelona, Spain.
2
Fundación Instituto Leloir, Av. Patricias Argentinas 435. C1405BWE, Buenos Aires, Argentina, Pompeu Fabra University (UPF), Dept. de Tecnologies de la Informació i les Comunicacions. Tanger 122-140 08018, Barcelona, Spain, Computational Genomics Laboratory, Genetics Department, Institut de Biologia Universitat de Barcelona (IBUB), Facultat de Biologia, Av Diagonal 645 and Breakthrough Cancer Research Unit, Dexeus University Hospital, Sabino Arana 5-19, Barcelona, Spain. cmb@leloir.org.ar.

Abstract

Somatic mutations in protein kinases (PKs) are frequent driver events in many human tumors, while germ-line mutations are associated with hereditary diseases. Here we present Kin-driver, the first database that compiles driver mutations in PKs with experimental evidence demonstrating their functional role. Kin-driver is a manual expert-curated database that pays special attention to activating mutations (AMs) and can serve as a validation set to develop new generation tools focused on the prediction of gain-of-function driver mutations. It also offers an easy and intuitive environment to facilitate the visualization and analysis of mutations in PKs. Because all mutations are mapped onto a multiple sequence alignment, analogue positions between kinases can be identified and tentative new mutations can be proposed for studying by transferring annotation. Finally, our database can also be of use to clinical and translational laboratories, helping them to identify uncommon AMs that can correlate with response to new antitumor drugs. The website was developed using PHP and JavaScript, which are supported by all major browsers; the database was built using MySQL server. Kin-driver is available at: http://kin-driver.leloir.org.ar/.

PMID:
25414382
PMCID:
PMC4237945
DOI:
10.1093/database/bau104
[Indexed for MEDLINE]
Free PMC Article

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