Dataset Information

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

ABSTRACT: The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular protein's structure, its function, and its relationships with other proteins. SGD can be accessed through the World Wide Web at http://genome-www.stanford.edu/Saccharomyces/

SUBMITTER: Chervitz SA

PROVIDER: S-EPMC148101 | biostudies-other | 1999 Jan

REPOSITORIES: biostudies-other

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Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

Chervitz S A SA Hester E T ET Ball C A CA Dolinski K K Dwight S S SS Harris M A MA Juvik G G Malekian A A Roberts S S Roe T T Scafe C C Schroeder M M Sherlock G G Weng S S Zhu Y Y Cherry J M JM Botstein D D

Nucleic acids research 19990101 1

The Saccharomyces Genome Database (SGD) collects and organizes information about the molecular biology and genetics of the yeast Saccharomyces cerevisiae. The latest protein structure and comparison tools available at SGD are presented here. With the completion of the yeast sequence and the Caenorhabditis elegans sequence soon to follow, comparison of proteins from complete eukaryotic proteomes will be an extremely powerful way to learn more about a particular protein's structure, its function, ...[more]

PMID: 9847146

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Project description: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 Comparison of Protein Active-Site Structures (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 Functional Annotation Screening Technology 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 C? 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.

Dataset Information

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

Publications

Using the Saccharomyces Genome Database (SGD) for analysis of protein similarities and structure.

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