Prediction and assignment of function for a divergent N-succinyl amino acid racemase

Ling Song, Chakrapani Kalyanaraman, Alexander A. Fedorov, Elena V. Fedorov, Margaret E. Glasner, Shoshana Brown, Heidi J. Imker, Patricia C. Babbitt, Steven C. Almo, Matthew P. Jacobson, John A. Gerlt

Research output: Contribution to journalArticlepeer-review

88 Scopus citations

Abstract

The protein databases contain many proteins with unknown function. A computational approach for predicting ligand specificity that requires only the sequence of the unknown protein would be valuable for directing experiment-based assignment of function. We focused on a family of unknown proteins in the mechanistically diverse enolase superfamily and used two approaches to assign function: (i) enzymatic assays using libraries of potential substrates, and (ii) in silico docking of the same libraries using a homology model based on the most similar (35% sequence identity) characterized protein. The results matched closely; an experimentally determined structure confirmed the predicted structure of the substrate-liganded complex. We assigned the N-succinyl arginine/lysine racemase function to the family, correcting the annotation (L-Ala-D/L-Glu epimerase) based on the function of the most similar characterized homolog. These studies establish that ligand docking to a homology model can facilitate functional assignment of unknown proteins by restricting the identities of the possible substrates that must be experimentally tested.

Original languageEnglish (US)
Pages (from-to)486-491
Number of pages6
JournalNature Chemical Biology
Volume3
Issue number8
DOIs
StatePublished - Aug 2007

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology

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