Abstract
Protein domains are subunits of proteins that recur throughout the protein world. There are many definitions attempting to capture the essence of a protein domain, and several systems that identify protein domains and classify them into families. EVEREST, recently described in Portugaly et al. (2006) BMC Bioinformatics, 7, 277, is one such system that performs the task automatically, using protein sequence alone. Herein we describe EVEREST release 2.0, consisting of 20 029 families, each defined by one or more HMMs. The current EVEREST database was constructed by scanning UniProt 8.1 and all PDB sequences (total over 3 000 000 sequences) with each of the EVEREST families. EVEREST annotates 64% of all sequences, and covers 59% of all residues. EVEREST is available at http://www.everest.cs.huji.ac.il/. The website provides annotations given by SCOP, CATH, Pfam A and EVEREST. It allows for browsing through the families of each of those sources, graphically visualizing the domain organization of the proteins in the family. The website also provides access to analyzes of relationships between domain families, within and across domain definition systems. Users can upload sequences for analysis by the set of EVEREST families. Finally an advanced search form allows querying for families matching criteria regarding novelty, phylogenetic composition and more.
| Original language | English |
|---|---|
| Pages (from-to) | D241-D246 |
| Journal | Nucleic Acids Research |
| Volume | 35 |
| Issue number | SUPPL. 1 |
| DOIs | |
| State | Published - Jan 2007 |
Bibliographical note
Funding Information:The authors thank Alex Savenok for the design and much of the programming of the EVEREST website. The authors thank Reuven Abliyev and Menachem Fromer for their support. The authors also thank the system team in the Hebrew University School of Computer Science and Engineering. E.P. is supported by an Eshkol fellowship from the Israeli Ministry of Science and by the Sudarsky Center for Computational Biology. This work is partially funded by NoE (Framework VI) BioSapiens consortium. The Open Access publication charges for this article were waived by Oxford University Press.