Theoretical QSAR modelling and molecular docking studies of some 4-hydroxyphenylpyruvate dioxygenase (HPPD) enzyme inhibitors potentially used as herbicides

• Published in: Heliyon 2019-11, Vol.5 (11), p.e02859-e02859, Article e02859
• Main Authors: Tukur, Saidu, Shallangwa, Gideon Adamu, Ibrahim, Abdulkadir
• Format: Article
• Language: English
• Subjects: 4-hydroxyphenylpyruvate dioxygenase; agrochemicals; amino acids; Applicability domain; Binding affinity(BA); Genetic function algorithm (GFA); Herbicide; hydrogen; hydrophobicity; Inorganic chemistry; Molecular docking; Multiple linear regression (MLR); Quantitative structure-activity relationship (QSAR)
• ISSN: 2405-8440; 2405-8440
• DOI: 10.1016/j.heliyon.2019.e02859

Computational QSAR studies together with molecular docking calculations have been performed on 118 different derivatives of organic molecules potentially used as herbicides. The Becke's three parameter exchange functional (B3) hybrid with Lee, Yang and Parr correlation functional (LYP), termed as B3LYP hybrid function and 6-31G* basis set (B3LYP/6-31G*) were used to develop five models of QSAR using the GFA technique. Models 1, was preferred as the best model because it possesses certain statistical implications (Friedman LOF = 0.52567, R2 = 0.9034, Radjst2= 0.8943, QCV2= 0.87 98 and Rpred.2= 0.8403).” The prepared model was validated internally and externally using training and test inhibitors. The molecular docking studies conducted in this study has actually outline the binding affinities of the 10 selected compounds (5, 25, 26, 27, 29, 35, 52, 55, 98 and 114) which were all in good correlation with their pIC50 values. The binding affinities of the 10 selected compounds range between -5.9 kcal/mol to -10.1 kcal/mol. The compounds 25 and 27 with binding affinities of -10.1 kcal/mol and -9.7 kcal/mol formed the most stable complexes with the receptor (HPPD) as compared to other inhibitors. The complexes of these inhibitors show two most important types of bonding; Hydrogen bonding and hydrophobic bond interaction with the target amino acid residues. The computational QSAR study together with the molecular docking has actually provided a valuable approach for agrochemical researchers in synthesizing and developing new herbicides with high potency against the target enzyme. Inorganic chemistry, Herbicide; Quantitative structure-activity relationship (QSAR); Multiple linear regression (MLR); Genetic function algorithm (GFA); Applicability domain; Molecular docking; Binding affinity(BA).