Molecular modeling study for the design of novel acetyl-CoA carboxylase inhibitors using 3D QSAR, molecular docking and dynamic simulations

Abstract

Acetyl-CoA carboxylase (ACC) enzyme plays an important role in the regulation of biosynthesis and oxidation of fatty acids. ACC is a recognized drug target for the treatment of obesity and diabetes. Combination of ligand and structure-based in silico methods along with activity and toxicity prediction provides best lead compounds in the drug discovery process. In this study, a data-set of 100 ACC inhibitors were used for the development of comparative molecular field analysis (CoMFA) and comparative molecular similarity index matrix analysis (CoMSIA) models. The generated contour maps were used for the design of novel ACC inhibitors. CoMFA and CoMSIA models were used for the predication of activity of designed compounds. In silico toxicity risk prediction study was carried out for the designed compounds. Molecular docking and dynamic simulations studies were performed to know the binding mode of designed compounds with the ACC enzyme. The designed compounds showed interactions with key amino acid residues important for catalysis, and good correlation was observed between binding free energy and inhibition of ACC.

Synthesis of an oleic acid based pH-responsive lipid and its application in nanodelivery of vancomycin

“…At room temperature, the kinetic energy was reduced from 685.88 kcal/mol to 386.34 kcal/mol, while at 4C it was reduced from 633.64 kcal/mol to 370.61 kcal/mol. The kinetic energy is known to be reduced at lower temperatures, resulting in reduced free energy and hence a more stable complex (Vyas et al 2017). These results were in line with those obtained from the stability study, which showed that the VCM_NMEO SLNs were more stable when stored at 4 °C in terms of PS, PDI and ZP (Table 4).…”