Leveraging enzyme structure-function relationships for functional inference and experimental design: The structure-function linkage database

Scott C.H. Pegg, Shoshana D. Brown, Sunil Ojha, Jennifer Seffernick, Elaine C. Meng, John H. Morris, Patricia J. Chang, Conrad C. Huang, Thomas E. Ferrin, Patricia C. Babbitt

Research output: Contribution to journalArticle

134 Scopus citations

Abstract

The study of mechanistically diverse enzyme superfamilies-collections of enzymes that perform different overall reactions but share both a common fold and a distinct mechanistic step performed by key conserved residues-helps elucidate the structure-function relationships of enzymes. We have developed a resource, the structure-function linkage database (SFLD), to analyze these structure-function relationships. Unique to the SFLD is its hierarchical classification scheme based on linking the specific partial reactions (or other chemical capabilities) that are conserved at the superfamily, subgroup, and family levels with the conserved structural elements that mediate them. We present the results of analyses using the SFLD in correcting misannotations, guiding protein engineering experiments, and elucidating the function of recently solved enzyme structures from the structural genomics initiative. The SFLD is freely accessible at http://sfld.rbvi.ucsf.edu.

Original languageEnglish (US)
Pages (from-to)2545-2555
Number of pages11
JournalBiochemistry
Volume45
Issue number8
DOIs
StatePublished - Feb 28 2006

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    Pegg, S. C. H., Brown, S. D., Ojha, S., Seffernick, J., Meng, E. C., Morris, J. H., Chang, P. J., Huang, C. C., Ferrin, T. E., & Babbitt, P. C. (2006). Leveraging enzyme structure-function relationships for functional inference and experimental design: The structure-function linkage database. Biochemistry, 45(8), 2545-2555. https://doi.org/10.1021/bi052101l