Leveraging structure for enzyme function prediction: methods, opportunities, and challenges.
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.
['Jacobson|Matthew P|MP|', 'Kalyanaraman|Chakrapani|C|', 'Zhao|Suwen|S|', 'Tian|Boxue|B|']
D000818:Animals D003198:Computer Simulation D006801:Humans D008958:Models, Molecular D011487:Protein Conformation D011506:Proteins D013329:Structure-Activity Relationship D013379:Substrate Specificity
enzyme function prediction protein structures docking homology modeling metabolic pathways