QSAR and molecular docking based design of some n-benzylacetamide as ?-aminobutyrate-aminotransferase inhibitors
Palavras-chave:γ-aminobutyrate-aminotransferase, Ligand-based design, Quantitative structure activity relationship, Kennard-Stone algorithm, Molecular docking, Genetic function algorithm
Quantitative structure activity relationship study (QSAR) and molecular docking were used to design and virtually screen some new N-benzylacetamide derivatives for their ability to inhibit ?-amino butyrate-aminotransferase. Ninety compounds with anticonvulsant activity against maximal electroshock induced seizures were used for QSAR study. B3LYP/6-31G** quantum mechanical method was employed to optimize/minimize the molecular structure of these compounds. Genetic Function Algorithm (GFA) method was used to develop the QSAR models. Each model gave an octa-parametric equation with good statistical qualities (R2 ranged from 0.823 to 0.893, Q2 from 0.772 to 0.854, F from 36.53 to 37.10, R2pred(test) from 0.768 to 0.893). Information obtained from the parameter contained in the model suggested that increasing the molecular mass and linearity of molecule would lead to increase in anticonvulsant activity of studied compounds. These informed the design and virtual screening of 118 new N-benzylacetamide derivatives using 2-acetamido-N-benzyl-2-(5-methylfuran-2-yl)acetamides as the template. The designed molecules were docked with ?-amino butyrate-aminotransferase (GABA_AT; PDB: 1OHV) using Internal Coordinate Mechanics Program (ICM-pro 3.8-3). The binding affinity of the designed compounds with GABA_AT were comparable to that of 4-aminohex-5-enoic acid (vigabatrin) and 3, 3-diphenylpyrrolidine-2, 5-dione (phenytoin) and 5H-dibenzo [b,f]azepine-5-carboxamide (carbamazepine), which are known inhibitors of GABA_AT. Therefore, the designed molecules have potential as inhibitors of GABA_AT and consequently as anticonvulsant agent.
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