Toxicology is a domain imbricating biology, chemistry, pharmacology, and
medicine that involves observing and analyzing inauspicious consequences of chemical
exposure on living beings thus identifying and manifesting toxins and toxicants.
Progress in computer sciences and hardware in combination with equally remarkable
growth in molecular biology and chemistry are providing toxicology with a reigning
new tool case. This tool case of computational models assures to enhance the efficacy
by which the hazards and risks of environmental chemicals are driven. In this study, we
investigated two compounds namely: Phenylgloxylic acid (PGA) and 4-ethynyl anisole
(MOPA) experimentally as well as quantum chemically. Density functional theory was
employed to investigate the tilted compounds theoretically. All the Quantum chemical
calculations were performed by implying the Density functional theory technique,
B3LYP method and 6-311++G (d, p) basis set. The reactive areas of the molecule were
obtained by Fukui functions. The ADME properties and drug-likeness nature of the
derivatives were obtained by SwissADME Tool [1]. Molecular docking studies were
also performed with different receptor proteins to study the best ligand-protein
interactions. The biological study-drug-likeness was also performed to check the druglike nature of the molecule.
Keywords: ADME, AutoDock, Bayesian, B3LYP method, Computational toxicology, Chimera, DFT, Drug, Drug-likeness, Docking, Electrophilicity index, Fukui, Machine learning, Orca, 6-311++G (d, p) basis set.
