The Cytochrome P450 Engineering Database: a navigation and prediction tool for the cytochrome P450 protein family
Source: Bioinformatics, Volume 23, Number 15, 31 August 2007 , pp. 2015-2017(3)
Publisher: Oxford University Press
Abstract:Summary: The Cytochrome P450 Engineering Database (CYPED) has been designed to serve as a tool for a comprehensive and systematic comparison of protein sequences and structures within the vast and diverse family of cytochrome P450 monooxygenases (CYPs). The CYPED currently integrates sequence and structure data of 3911 and 25 proteins, respectively. Proteins are grouped into homologous families and superfamilies according to Nelson's classification. Nonclassified CYP sequences are assigned by similarity. Functionally relevant residues are annotated. The web accessible version contains multisequence alignments, phylogenetic trees and HMM profiles. The CYPED is regularly updated and supplies all data for download. Thus, it provides a valuable data source for phylogenetic analysis, investigation of sequence-function relationships and the design of CYPs with improved biochemical properties.Abbreviations: Cytochrome P450 Engineering Database, CYPED; cytochrome P450 monooxygenase, CYP; Hidden Markov Model, HMM.Availability: <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="www.cyped.uni-stuttgart.de">www.cyped.uni-stuttgart.de</ext-link>Contact: Juergen.Pleiss@itb.uni-stuttgart.de
Document Type: Research article
Affiliations: 1: Department of Biochemistry & Molecular Biophysics, Columbia University, 1130 St. Nicholas Ave, New York, NY 10032, USA and , 2: Institute of Technical Biochemistry, University of Stuttgart, Allmandring 31, 70569 Stuttgart, Germany,
Publication date: 2007-08-31
- The leading journal in its field, Bioinformatics publishes the highest quality scientific papers and review articles of interest to academic and industrial researchers. Its main focus is on new developments in genome bioinformatics and computational biology. Two distinct sections within the journal - Discovery Notes and Application Notes- focus on shorter papers; the former reporting biologically interesting discoveries using computational methods, the latter exploring the applications used for experiments.