Emmanuel Israel Edache; Hadiza Adamu Dawi; Fabian Audu Ugbe
Abstract
3D-QSAR, comparative molecular field analysis- smart region description (SRD) and fractional factorial design (FFD) (CoMFA-FFD), and comparative molecular field analysis-uninformative ...
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3D-QSAR, comparative molecular field analysis- smart region description (SRD) and fractional factorial design (FFD) (CoMFA-FFD), and comparative molecular field analysis-uninformative variable elimination-partial least square (CoMFA-UVEPLS) were conducted on 44 compounds. CoMFA-FFD and CoMFA-UVEPLS models give dependable complementary and prescient capacities; however, the CoMFA-FFD model did was to a little degree or degree better than CoMFA-UVEPLS. From the contour maps generated from the CoMFA-FFD and CoMFA-UVEPLS models, more important features were identified to boast the chemical structures that were responsible for inhibitors of the glycoprotein (GPC) of Lassa (LASV) Arenavirus. Secondly, docking was performed between the compounds and protein to predict their binding affinity. Based on the docking simulation approach, two compounds have chosen for further evaluation. The MD simulation approach was used to confirm the stability of the selected drug candidate to the target protein, which confirmed the stability of the selected lead drugs. Docking and MD simulations present comparative associations between the protein and the ligands. The MD simulations further described hydrogen bond, steric, and hydrophobic interactions on the ligand. The standard free binding energy calculation revealed that the two selected drug candidates have a significant binding affinity for GPC of LASV. The discussion points out positions on the ligands and their suggestions on protein interactions. The computational methodology utilized in this paper gives solid insights for an additional plan of molecules for inhibitors of the glycoprotein (GPC) of Lassa infection (LASV) Arenavirus.
