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Open Access Technical Note

Searching the protein structure database for ligand-binding site similarities using CPASS v.2

Robert Powers1*, Jennifer C Copeland1, Jaime L Stark1, Adam Caprez2, Ashu Guru2 and David Swanson2

Author Affiliations

1 Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304 USA

2 Holland Computing Center, University of Nebraska-Lincoln, Lincoln, NE 68588-0150 USA

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BMC Research Notes 2011, 4:17  doi:10.1186/1756-0500-4-17

Published: 26 January 2011

Abstract

Background

A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our

    C
omparison of
    P
rotein
    A
ctive-
    S
ite
    S
tructures (CPASS v.2) database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our
    F
unctional
    A
nnotation
    S
creening
    T
echnology by NMR (FAST-NMR) protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function.

Findings

We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG) to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated.

Conclusions

CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores for false positives by ~30%, while leaving true positives unaffected. Importantly, receiver operating characteristics (ROC) curves demonstrate the high correlation between CPASS similarity scores and an accurate functional assignment. As indicated by distribution curves, scores ≥ 30% infer a functional similarity. Software URL: http://cpass.unl.edu webcite.