Volume 5 Supplement 1

8th German Conference on Chemoinformatics: 26 CIC-Workshop

Open Access

Efficient mining of protein kinase structural data

  • Stephen Maginn1Email author,
  • Andrew Henry1,
  • Paul Labute2,
  • Johannes Maier2 and
  • Nels Thorsteinson2
Journal of Cheminformatics20135(Suppl 1):P16

https://doi.org/10.1186/1758-2946-5-S1-P16

Published: 22 March 2013

Here, we introduce an aligned database of protein kinase structures that can be efficiently explored by sequence, structure, or by ATP pocket ligand (type or similarity). We also discuss an automated protocol for kinase identification, classification and superposition that relies on a curated reference set of structures and sequences covering the wide variety of human protein kinases.

Authors’ Affiliations

(1)
Chemical Computing Group, St Johns Innovation Centre
(2)
Chemical Computing Group

Copyright

© Maginn et al.; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.