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

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dc.contributor.authorKaya, Yunus
dc.contributor.authorYildiz, Aytac
dc.date.accessioned2026-02-12T21:05:41Z
dc.date.available2026-02-12T21:05:41Z
dc.date.issued2023
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractIn 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.
dc.identifier.doi10.14744/sigma.2023.00052
dc.identifier.endpage468
dc.identifier.issn1304-7205
dc.identifier.issn1304-7191
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85162894136
dc.identifier.scopusqualityQ4
dc.identifier.startpage457
dc.identifier.urihttps://doi.org/10.14744/sigma.2023.00052
dc.identifier.urihttps://hdl.handle.net/20.500.12885/7076
dc.identifier.volume41
dc.identifier.wosWOS:001006530200004
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherYildiz Technical Univ
dc.relation.ispartofSigma Journal of Engineering and Natural Sciences-Sigma Muhendislik Ve Fen Bilimleri Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260212
dc.subjectCovid-19
dc.subjectFavirapiravir
dc.subjectGaussian
dc.subjectAutodock Vina
dc.subjectAHP
dc.subjectGRA
dc.titleDetermination of the active molecule as a potential drug against covid-19 virus using molecular docking and hybrid AHP-GRA method
dc.typeArticle

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