Determination of the active molecule as a potential drug against covid-19 virus using molecular docking and hybrid AHP-GRA method

Abstract

In this study, it is aimed to determine the most effective molecule to be used as an active ingredient against the covid-19 virus among the 15 molecules proposed by adding some elec-tronegative groups to some molecules used in the ebola virus. In the first stage of the study, the proposed molecules are optimized in DFT / B3LYP method and 6-311G ++ (d, p) basis set, dipole moment, entropy, energy of HOMO and LUMO orbitals and band gap energies are calculated. In addition, the interactions of these molecules with the Covid-19 main protease enzyme (PDB no = 6LU7) are examined with the Autodock vina program. Correlation anal-ysis is performed using the IBM SPSS Statistics 23 program with the values obtained from molecular docking and DFT calculations, and it is determined that there is no statistically significant relationship between the band gap factor and free docking energy. In the second stage of the study, the importance weights of the parameters belonging to the molecules are determined by the Analytical Hierarchy Process (AHP) method. Then, the mol-ecules are ranked by preference using the Gray Relational Analysis (GRA) method. According to the results of the sensitivity analysis performed at the end of the study, it is determined that the 1D6-CN molecule is the most effective molecule to be used as an active ingredient against the covid-19 virus.