Critical assessment of genome-scale metabolic models of Arabidopsis thaliana.

Genome-scale metabolic models (GEMs) have enabled researchers to perform systems-level studies of living organisms. Flux balance analysis (FBA), as a constraint-based technique, enables computation of reaction fluxes and prediction of the metabolic phenotypes of a cell under a set of specified conditions. The quality of a GEM is important for obtaining accurate predictions. In this study, we evaluated the quality of five available GEMs for Arabidopsis thaliana from various points of views. To do this, we inspected some of their important features, including the number of reactions with well-defined gene-protein-reaction rules, number of blocked reactions, mass-unbalanced reactions, prediction accuracy in the simulation of key metabolic functions and existence of erroneous energy generating cycles (EGCs). All of the models were found to include some mass-unbalanced reactions. Moreover, four out of five models were found to include EGCs. However, Aracell includes the maximum number of blocked reactions, which suggests the presence of several incomplete pathways. These results clearly show that simulation by using these models may result in erroneous predictions and all of the publicly available GEMs for A. thaliana require extensive curations before being applied in practice.

Structure and activity of a novel robust peroxidase from Alkanna frigida cell culture.

Demands for peroxidases (POX)s with diverse physicochemical properties have steadily grown as more applications of POXs are demonstrated. Plants are among the best sources of versatile POXs, and plant biotechnology, as an agricultural hassle-free technology, promises to circumvent the limitations of natural resource exploitation and to address the demands. Following this trend, it was shown that POX production steadily increased during the 31-day subculture of Alkanna frigida (from Boraginaceae) callus on Murashige-Skoog medium containing 2,4-dichlorophenoxyacetic acid (10-6 M) and kinetin (10-5 M). The purified cationic enzyme (POXalf) maintained its optimal activity over pH 4-7 for 2 years. It was resistant to H2O2 high concentrations (IC50 = 543.7 mM) and showed high specific activity in the reaction with phenol (4320.5 AU mg-1 > 20-fold of HRP AU). Furthermore, the specificity constant ratio of guaiacol to phenol indicated a 100 times faster reaction of POXalf with guaiacol. However, in contrast to HRP, it had little effect on diazo derivatives of aniline and meta-diaminobenzene. Based on the resulting primary structure from the tandem mass analysis, the POXalf 3D structure was constructed via homology modelling. Despite the high topological similarity between the HRP and POXalf structures, there were important differences between the active site pockets that could explain the observed differences in the corresponding substrate spectra and the specific activities. Considering the dynamics of POXalf production, its inactivity towards IAA and its high affinity for guaiacol, POXalf may have associated roles with A. frigida cell wall construction and monolignol metabolism.

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.