The AnnoLite and AnnoLyze programs for comparative annotation of protein structures

TitleThe AnnoLite and AnnoLyze programs for comparative annotation of protein structures
Publication TypeJournal Article
Year of Publication2007
AuthorsMarti-Renom, MA, Rossi, A, Al-Shahrour, F, Davis, FP, Pieper, U, Dopazo, J, Sali, A
JournalBMC Bioinformatics
Volume8 Suppl 4
PaginationS4
Keywords*Algorithms Amino Acid Sequence Confidence Intervals Data Interpretation; Amino Acid *Software Structure-Activity Relationship; Protein Information Storage and Retrieval/methods Molecular Sequence Data Proteins/*chemistry/classification/*metabolism Sensitivity and Specificity Sequence Alignment/*methods Sequence Analysis; Protein/*methods Sequence Homology; Statistical *Databases
Abstract

BACKGROUND: Advances in structural biology, including structural genomics, have resulted in a rapid increase in the number of experimentally determined protein structures. However, about half of the structures deposited by the structural genomics consortia have little or no information about their biological function. Therefore, there is a need for tools for automatically and comprehensively annotating the function of protein structures. We aim to provide such tools by applying comparative protein structure annotation that relies on detectable relationships between protein structures to transfer functional annotations. Here we introduce two programs, AnnoLite and AnnoLyze, which use the structural alignments deposited in the DBAli database. DESCRIPTION: AnnoLite predicts the SCOP, CATH, EC, InterPro, PfamA, and GO terms with an average sensitivity of 90% and average precision of 80%. AnnoLyze predicts ligand binding site and domain interaction patches with an average sensitivity of 70% and average precision of 30%, correctly localizing binding sites for small molecules in 95% of its predictions. CONCLUSION: The AnnoLite and AnnoLyze programs for comparative annotation of protein structures can reliably and automatically annotate new protein structures. The programs are fully accessible via the Internet as part of the DBAli suite of tools at http://salilab.org/DBAli/.

Notes

Marti-Renom, Marc A Rossi, Andrea Al-Shahrour, Fatima Davis, Fred P Pieper, Ursula Dopazo, Joaquin Sali, Andrej Research Support, Non-U.S. Gov’t England BMC bioinformatics BMC Bioinformatics. 2007 May 22;8 Suppl 4:S4.

URLhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=17570147