Computer Modeling of N-Acetylglutamate Synthase: From Primary Structure to Elemental Stages of Catalysis

Three-dimensional full-atom model of the enzyme complex with acetyl-CoA and substrate was constructed on the basis of the primary sequence of amino acid residues of N-acetyl glutamate synthase. Bioinformatics approaches of computer modeling were applied, including multiple sequence alignment, prediction of co-evolutionary contacts, and ab initio folding. On the basis of the results of calculations by classical molecular dynamics and combined quantum and molecular mechanics (QM/MM) methods, the structure of the active site and the reaction mechanism of N-acetylglutamate formation are described. Agreement of the structures of the enzyme-product complexes obtained in computer modeling and in the X-ray studies validates the reliability of modeling predictions.

Kinetic Modeling of the Blood Oxygenation Level Dependent (BOLD) Signals and Biocatalytic Reactions Observed in the Human Brain Using MRI: An Analysis of Normal and Pathological Conditions

A kinetic model describing the pulse of increased oxygen concentrations and the subsequent changes in the concentration of N-acetylaspartate in the excited nervous tissue of the human brain in response to an external signal is presented. The model is based on biochemical data, a multistage and nonlinear dynamic process the BOLD signal and N-acetylaspartate. The existence of multiple steady states explains the triggering effect of the system. The inhibitory effect of the substrate is a necessary factor for the autostabilization of N-acetylaspartate. The kinetic model allows the dynamic behavior of previously unmeasurable metabolites, namely, products of the hydrolysis of N-acetylaspartate, such as acetic and aspartic acid, and glutamic acid to be predicted. Kinetic modeling of the BOLD signal and the subsequent hydrolysis of N-acetylaspartate provides information about the biochemical and dynamic characteristics of some pathological conditions (schizophrenia, Canavan disease, and the superexcitation of the neural network).