Representing Structure-Function Relationships in Mechanistically Diverse Enzyme Superfamilies

Pac Symp Biocomput. 2005;358-69.

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).

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Catalysis
  • Computational Biology / methods
  • Conserved Sequence
  • Enzymes / chemistry*
  • Enzymes / classification
  • Enzymes / metabolism*
  • Kinetics
  • Protein Engineering / methods
  • Software
  • Structure-Activity Relationship

Substances

  • Enzymes