Molecular Docking and QSAR Studies for Modeling the Inhibitory Activity of Pyrazole-benzimidazolone Hybrids as Novel Inhibitors of Human 4-hydroxyphenylpyruvate dioxygenase Against Type I Tyrosinemia Disease

Abstract

Pyrazole-benzimidazolone is a novel inhibitor of human 4-Hydroxyphenylpyruvate dioxygenase of the HPPD receptor. To analyze this inhibitory activity, a QSAR study was performed using 33 compounds. The MLR multiple linear regression method and the NN neural network were used to establish the predicted model. This model was validated by the external validation method. The molecular electronic descriptors were calculated by the DFT method. This study shows that the activity of the compounds is strongly correlated with the five descriptors selected by the MLR method. The correlation coefficients calculated by MLR and then by NN are R =0.878 and R =0.978; they allow us to evaluate the proposed quantitative model. The latter allowed us to predict the activity of new HPPD receptor inhibitors and to show the good predictive competence of the established QSAR model. Based on these results, we performed docking in the active site of HPPD protein with the most active compound (12), and we deduced that this compound specifically interacts with are GLN 307, ASN 423, and PHE 392 at the HPPD protein binding pocket; thus, it showed additional interactions with VAL 228, PRO 280, SER 267, LEU 265, LYS 421, GLN 379, GLY 420, and LEU 368, This interaction is similar to that of NTBC with the active site.