In silico prediction of enzymatic reactions catalyzed by acid phosphatases.

In present work, we describe a methodology for prediction of an enzymatic reaction for which no experimental data are available except for a gene sequence. As a challenging case, we have developed the method for identifying the putative substrates of monoester phosphatases, commonly known as acid phosphatase enzymes, which have no strong substrate specificity. Finding a preferable substrate for each one is an important task to unravel pathways involved in plant phosphate metabolism. Having used an Arabidopsis thaliana haloacid dehalogenase (HAD)-related acid phosphatases, HRP9, with an experimentally known structure and preferred substrate as an instance, we firstly predicted the 3 D-structure of HRP1 for subsequent analysis. Then, molecular docking was used to find the best protein interaction with a ligand existing in a set of possible substrates compiled from genome scale metabolic networks of A. thaliana based on binding energy, binding mode as well as the distance between phosphoric ester and cofactor, Mg2+, localized in the active site of HRP1. Molecular dynamics simulation ratified stable protein-ligand complex model. Our analysis predicted HRP1 preferably bind to pyridoxamine-5'-phosphate (PMP). Thus, it is deduced that the conversion of PMP to pyridoxamine must be catalyzed by HRP1. This procedure is expected to make a reliable pipeline to predict the enzymatic reactions catalyzed by acid phosphatases. Taken as a whole, it could be applicable for discovery of the interacting ligands, inhibitors as well as interacting proteins which limits lab works or used for gap filling in biosystems.Communicated by Ramaswamy H. Sarma.