Nucleic Acids Research Advance Access published online on May 5, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp312
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Web Server Issue |
SePreSA: a server for the prediction of populations susceptible to serious adverse drug reactions implementing the methodology of a chemical–protein interactome
1Bio-X Center, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai 200030, 2Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032 and 3Institute for Nutritional Sciences, Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, PR China
*To whom correspondence should be addressed. Tel: +86 21 6293 3338, ext. 8108; Fax: +86 21 6293 2059; Email: lunyang{at}gmail.com. Correspondence may also be addressed to Lin He. Tel: 0086-(0)21-62833148; Fax: 0086-(0)21-32260640; Email: helinhelin{at}gmail.com
Received January 28, 2009. Revised April 6, 2009. Accepted April 18, 2009.
Serious adverse drug reactions (SADRs) are caused by unexpected drug–human protein interactions, and some polymorphisms within binding pockets make the population carrying these polymorphisms susceptible to SADR. Predicting which populations are likely to be susceptible to SADR will not only strengthen drug safety, but will also assist enterprises to adjust R&D and marketing strategies. Making such predictions has recently been facilitated by the introduction of a web server named SePreSA. The server has a comprehensive collection of the structural models of nearly all the well known SADR targets. Once a drug molecule is submitted, the scale of its potential interaction with multi-SADR targets is calculated using the DOCK program. The server utilizes a 2-directional Z-transformation scoring algorithm, which computes the relative drug–protein interaction strength based on the docking-score matrix of a chemical–protein interactome, thus achieve greater accuracy in prioritizing SADR targets than simply using dock scoring functions. The server also suggests the binding pattern of the lowest docking score through 3D visualization, by highlighting and visualizing amino acid residues involved in the binding on the customer's browser. Polymorphism information for different populations for each of the interactive residues will be displayed, helping users to deduce the population-specific susceptibility of their drug molecule. The server is freely available at http://SePreSA.Bio-X.cn/.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.