Nucleic Acids Research Advance Access originally published online on November 5, 2008
Nucleic Acids Research 2009 37(Database issue):D824-D831; doi:10.1093/nar/gkn832
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Nucleic Acids Research, 2009, Vol. 37, Database issue D824-D831
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This article appears in the following Nucleic Acids Research issue: Database issue [View the issue table of contents]
Articles |
MoKCa database—mutations of kinases in cancer
1Section of Structural Biology and 2The Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, Chester Beatty Laboratories, 237 Fulham Road, London SW3 6JB, UK
*To whom correspondence should be addressed. Tel: +44 (0)20 7153 5443; Fax: +44 (0)20 7153 5457; Email: frances.pearl{at}icr.ac.uk
Received August 14, 2008. Revised October 3, 2008. Accepted October 14, 2008.
Members of the protein kinase family are amongst the most commonly mutated genes in human cancer, and both mutated and activated protein kinases have proved to be tractable targets for the development of new anticancer therapies The MoKCa database (Mutations of Kinases in Cancer, http://strubiol.icr.ac.uk/extra/mokca) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer. Somatic mutation data from tumours and tumour cell lines have been mapped onto the crystal structures of the affected protein domains. Positions of the mutated amino-acids are highlighted on a sequence-based domain pictogram, as well as a 3D-image of the protein structure, and in a molecular graphics package, integrated for interactive viewing. The data associated with each mutation is presented in the Web interface, along with expert annotation of the detailed molecular functional implications of the mutation. Proteins are linked to functional annotation resources and are annotated with structural and functional features such as domains and phosphorylation sites. MoKCa aims to provide assessments available from multiple sources and algorithms for each potential cancer-associated mutation, and present these together in a consistent and coherent fashion to facilitate authoritative annotation by cancer biologists and structural biologists, directly involved in the generation and analysis of new mutational data.