title: Leveraging structure for enzyme function prediction: methods, opportunities, and challenges.
abstract: The rapid growth of the number of protein sequences that can be inferred from sequenced genomes presents challenges for function assignment, because only a small fraction (currently <1%) has been experimentally characterized. Bioinformatics tools are commonly used to predict functions of uncharacterized proteins. Recently, there has been significant progress in using protein structures as an additional source of information to infer aspects of enzyme function, which is the focus of this review. Successful application of these approaches has led to the identification of novel metabolites, enzyme activities, and biochemical pathways. We discuss opportunities to elucidate systematically protein domains of unknown function, orphan enzyme activities, dead-end metabolites, and pathways in secondary metabolism.
authors.affiliation: Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, CA 94158, USA; California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158, USA. Electronic address: matt.jacobson@ucsf.edu.
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Jacobson
authors.affiliation: Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, CA 94158, USA; California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158, USA.
authors.forename: Chakrapani
authors.initials: C
authors.lastname: Kalyanaraman
authors.affiliation: Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, CA 94158, USA; California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158, USA.
authors.forename: Suwen
authors.initials: S
authors.lastname: Zhao
authors.affiliation: Department of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco, CA 94158, USA; California Institute for Quantitative Biomedical Research, University of California, San Francisco, CA 94158, USA.
authors.forename: Boxue
authors.initials: B
authors.lastname: Tian
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008958:Models, Molecular; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D013329:Structure-Activity Relationship; D013379:Substrate Specificity
chemical_list: D011506:Proteins
keywords: docking; enzyme function prediction; homology modeling; metabolic pathways; protein structures