Structure-based activity prediction for an enzyme of unknown function

With many genomes sequenced, a pressing challenge in biology is predicting the function of the proteins that the genes encode. When proteins are unrelated to others of known activity, bioinformatics inference for function becomes problematic. It would thus be useful to interrogate protein structures for function directly. Here, we predict the function of an enzyme of unknown activity, Tm0936 from Thermotoga maritima, by docking high-energy intermediate forms of thousands of candidate metabolites. The docking hit list was dominated by adenine analogues, which appeared to undergo C6-deamination. Four of these, including 5-methylthioadenosine and S-adenosylhomocysteine (SAH), were tested as substrates, and three had substantial catalytic rate constants (105 M-1s-1). The X-ray crystal structure of the complex between Tm0936 and the product resulting from the deamination of SAH, S-inosylhomocysteine, was determined, and it corresponded closely to the predicted structure. The deaminated products can be further metabolized by T. maritima in a previously uncharacterized SAH degradation pathway. Structure-based docking with high-energy forms of potential substrates may be a useful tool to annotate enzymes for function. Though it is often possible to infer the function of a newly discovered protein by comparing its sequence to those of other characterized proteins, it can be extremely difficult to predict the function of an enzyme that is unrelated to other studied proteins. Hermann et al. now show that it is possible to use a computational approach to predict the function of an enzyme of unknown activity. They 'docked' high-energy intermediate forms of thousands of candidate metabolites to the X-ray crystal structure of Tm0936, a member of the amidohydrolase superfamily. These experiments predicted that the enzyme would deaminate 5-methylthioadenosine and S-adenosylhomocysteine; this was borne out biochemically, and the X-ray crystal structure of one of the products bound to Tm0936 corresponded closely to the predicted structure. These results suggest that structure-based docking using high-energy forms of potential substrates may be a useful tool to annotate enzymes for function. A computational approach is used to predict the function of an uncharacterized enzyme by docking high-energy intermediate forms of candidate metabolites into its purported binding site. The docking experiments predicted that the enzyme would be able to deaminate intermediates of 5-methylthioadenosine and S-adenosylhomocysteine, a prediction confirmed by biochemical experiments and examination of the X-ray crystal structure of the protein.