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Bioinformatics Advance Access published online on May 19, 2005
Bioinformatics, doi:10.1093/bioinformatics/bti498
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oupjournals.org
Received February 17, 2005
Revised April 20, 2005
Accepted May 11, 2005

Article

Computational approaches for identification of conserved/unique binding pockets in the A chain of ricin

Carol L. Ecale Zhou 1*, Adam T. Zemla 1, Diana Roe 2, Malin Young 2, Marisa Lam 1, Joseph S. Schoeniger 2, and Rod Balhorn 1

1 Lawrence Livermore National Laboratory
2 Sandia National Laboratory

* To whom correspondence should be addressed.
Carol L. Ecale Zhou, E-mail: zhou4{at}llnl.gov


  Abstract

Motivation: Specific and sensitive ligand-based protein detection assays that employ antibodies or small molecules such as peptides, aptamers, or other small molecules require that the corresponding surface region of the protein be accessible and that there be minimal cross-reactivity with non-target proteins. To reduce the time and cost of laboratory screening efforts for diagnostic reagents, we developed new methods for evaluating and selecting protein surface regions for ligand targeting.

Results: We devised combined structure- and sequence-based methods for identifying 3D epitopes and binding pockets on the surface of the A chain of ricin that are conserved with respect to a set of ricin A chains and unique with respect to other proteins. We 1) used structure alignment software to detect structural deviations and extracted from this analysis the residue-residue correspondence, 2) devised a method to compare corresponding residues across sets of ricin structures and structures of closely related proteins, 3) devised a sequence-based approach to determine residue infrequency in local sequence context, and 4) modified a pocket-finding algorithm to identify surface crevices in close proximity to residues determined to be conserved/unique based on our structure- and sequence-based methods. In applying this combined informatics approach to ricin A we identified a conserved/unique pocket in close proximity (but not overlapping) the active site that is suitable for bi-dentate ligand development. These methods are generally applicable to identification of surface epitopes and binding pockets for development of diagnostic reagents, therapeutics, and vaccines.


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