E1DS: catalytic site prediction based on 1D signatures of concurrent conservation.

Ting Ying Chien, Darby Tien Hao Chang, Chien Yu Chen, Yi Zhong Weng, Chen Ming Hsu

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Large-scale automatic annotation of protein sequences remains challenging in postgenomics era. E1DS is designed for annotating enzyme sequences based on a repository of 1D signatures. The employed sequence signatures are derived using a novel pattern mining approach that discovers long motifs consisted of several sequential blocks (conserved segments). Each of the sequential blocks is considerably conserved among the protein members of an EC group. Moreover, a signature includes at least three sequential blocks that are concurrently conserved, i.e. frequently observed together in sequences. In other words, a sequence signature is consisted of residues from multiple regions of the protein sequence, which echoes the observation that an enzyme catalytic site is usually constituted of residues that are largely separated in the sequence. E1DS currently contains 5421 sequence signatures that in total cover 932 4-digital EC numbers. E1DS is evaluated based on a collection of enzymes with catalytic sites annotated in Catalytic Site Atlas. When compared to the famous pattern database PROSITE, predictions based on E1DS signatures are considered more sensitive in identifying catalytic sites and the involved residues. E1DS is available at http://e1ds.ee.ncku.edu.tw/ and a mirror site can be found at http://e1ds.csbb.ntu.edu.tw/.

Original languageEnglish
Pages (from-to)W291-296
JournalNucleic acids research
Issue numberWeb Server issue
Publication statusPublished - 2008 Jul 1

All Science Journal Classification (ASJC) codes

  • Genetics


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