CysView: protein classification based on cysteine pairing patterns
1 Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore, 2 School of Molecular and Microbial Biosciences, Building G08, University of Sydney, NSW 2006, Australia, 3 IUP Génie Physiologique et Informatique, Bâtiment botanique, 40 av. Recteur Pineau-86022, Poitiers Cedex, France and 4 Department of Biochemistry and 5 Department of Microbiology, Faculty of Medicine, National University of Singapore, 8 Medical Drive, 117597 Singapore
* To whom correspondence should be addressed at 21 Heng Mui Keng Terrace, 119613 Singapore. Tel: +65 6874 7920; Fax: +65 6774 8056; Email: vladimir{at}i2r.a-star.edu.sg
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors
Received February 15, 2004; Revised April 20, 2004; Accepted May 3, 2004
CysView is a web-based application tool that identifies and classifies proteins according to their disulfide connectivity patterns. It accepts a dataset of annotated protein sequences in various formats and returns a graphical representation of cysteine pairing patterns. CysView displays cysteine patterns for those records in the data with disulfide annotations. It allows the viewing of records grouped by connectivity patterns. CysView's utility as an analysis tool was demonstrated by the rapid and correct classification of scorpion toxin entries from GenPept on the basis of their disulfide pairing patterns. It has proved useful for rapid detection of irrelevant and partial records, or those with incomplete annotations. CysView can be used to support distant homology between proteins. CysView is publicly available at http://research.i2r.a-star.edu.sg/CysView/.
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