Prediction of potent therapeutic anticonvulsant ligands to N-methyl-d-aspartate receptors among substituted 4,6-dichloroindole-2-carboxylic acids: Molecular modeling approach

We performed two- and three-dimensional quantitative structure–activity relation (QSAR) pharmacophore studies with a series of substituted 4,6-dichloroindole-2-carboxylic acid analogs in order to elucidate the structural properties required for high affinity for the glycine binding site of the N-methyl-d-aspartate receptor. The partial least-squares method coupled with various feature selection methods (stepwise, genetic algorithm and simulated annealing) were used to derive QSAR models, which were validated for statistical significance and predictive ability by internal and external validation. The best two-dimensional QSAR model was selected, which had a correlation coefficient, r2 = 0.8577, a cross-validated squared correlation coefficient, q2 = 0.7118 and an external predictive ability pred_r2 = 0.7642. Molecular field analysis was used to construct the best three-dimensional QSAR model by the genetic algorithm–partial least-squares method, which showed good correlational and predictive capability: q2 = 0.7538, q2_se = 0.4833 and pred_r2 = 0.7019. In a series of 4,6-dichloroindole-2-carboxylic acid derivatives, the pharmacophore model based on the chemical feature with the lowest root mean square deviation (2.187 nm) consisted of one aromatic feature, one hydrogen bond donor, one hydrogen bond acceptor, one aliphatic and one positive coefficient feature. A representative set of 4,6-dichloroindole-2-carboxylic acid compounds with effective biological activity and a good glycine binding site on the N-methyl-d-aspartate receptor were identified, which may be potential leads for drugs with anticonvulsant activity.