| Literature DB >> 15759641 |
Scott C H Pegg1, Shoshana Brown, Sunil Ojha, Conrad C Huang, Thomas E Ferrin, Patricia C Babbitt.
Abstract
The prediction of protein function from structure or sequence data remains a problem best addressed by leveraging information available from previously determined structure-function relationships. In the case of enzymes, the study of mechanistically diverse superfamilies can provide a rich source of structure-function information useful in functional determination and enzyme engineering. To access these relationships using a computational resource, several issues must be addressed regarding the representation of enzyme function, the organization of structure-function relationships in the superfamily context, the handling of misannotations, and reliability of classifications and evidence. We discuss here our approaches to solving these problems in the development of a Structure-Function Linkage Database (SFLD) (online at http://sfld.rbvi.ucsf.edu).Mesh:
Substances:
Year: 2005 PMID: 15759641
Source DB: PubMed Journal: Pac Symp Biocomput ISSN: 2335-6928