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Nucleic Acids Research 2006 34(Web Server issue):W310-W314; doi:10.1093/nar/gkl206
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© The Author 2006. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

Article

GRAMM-X public web server for protein–protein docking

Andrey Tovchigrechko1,* and Ilya A. Vakser1,2,*

1 Center for Bioinformatics, The University of Kansas 2030 Becker Drive, Lawrence, KS 66047, USA 2 Department of Molecular Biosciences, The University of Kansas 2030 Becker Drive, Lawrence, KS 66047, USA

*To whom correspondence should be addressed. Tel: 785 864 1057; Fax: 785 864 5558; Email: andrey{at}ku.edu

Received February 15, 2006. Revised March 22, 2006. Accepted March 22, 2006.

Protein docking software GRAMM-X and its web interface (http://vakser.bioinformatics.ku.edu/resources/gramm/grammx) extend the original GRAMM Fast Fourier Transformation methodology by employing smoothed potentials, refinement stage, and knowledge-based scoring. The web server frees users from complex installation of database-dependent parallel software and maintaining large hardware resources needed for protein docking simulations. Docking problems submitted to GRAMM-X server are processed by a 320 processor Linux cluster. The server was extensively tested by benchmarking, several months of public use, and participation in the CAPRI server track.

*Correspondence may also be addressed to Ilya A. Vakser. Tel: 785 864 1057; Fax: 785 864 5558; Email: vakser{at}ku.edu


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