期刊
NUCLEIC ACIDS RESEARCH
卷 45, 期 W1, 页码 W315-W319出版社
OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx337
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资金
- Medical Research Council (MRC) Newton Fund RCUK-CONFAP Grant
- Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG) [APQ-00828-15]
- Centro de Pesquisas Rene Rachou (CPqRR/FIOCRUZ Minas), Brazil
- CAPES
- CNPq
- Fundacao de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG)
- MRC Newton Fund RCUK-CONFAP Grant
- FAPEMIG
Enzyme active sites are important and conserved functional regions of proteins whose identification can be an invaluable step toward protein function prediction. Most of the existing methods for this task are based on active site similarity and present limitations including performing only exact matches on template residues, template size restraints, despite not being capable of finding inter-domain active sites. To fill this gap, we proposed GASS-WEB, a user-friendly web server that uses GASS (Genetic Active Site Search), a method based on an evolutionary algorithm to search for similar active sites in proteins. GASS-WEB can be used under two different scenarios: (i) given a protein of interest, to match a set of specific active site templates; or (ii) given an active site template, looking for it in a database of protein structures. The method has shown to be very effective on a range of experiments andwas able to correctly identify >90% of the catalogued active sites from the Catalytic Site Atlas. It also managed to achieve a Matthew correlation coefficient of 0.63 using the Critical Assessment of protein Structure Prediction (CASP 10) dataset. In our analysis, GASS was ranking fourth among 18 methods. GASS-WEB is freely available at http://gass.unifei.edu.br/.
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