3D Quantitative structure–activity relationship to predict the anti-malarial activity in a set of Cycloguanil Analogs

dc.contributor.authorAgede, Olalekan Ayodele
dc.contributor.authorBojuwoye, Matthew Olumuyiwa
dc.contributor.authorAdenike, Adeniyi F
dc.contributor.authorMokuolu, Olugbenga A
dc.contributor.authorFalade, Catherine O
dc.date.accessioned2024-05-21T08:54:01Z
dc.date.available2024-05-21T08:54:01Z
dc.date.issued2022
dc.description.abstractAnti-malarial drugs such as chloroquine, Sulphadoxine-pyrimethamine and mefloquine have become ineffective in the treatment of malaria due to development of resistance by the malaria parasite. Consequently, the rise in defiance to older drugs initiated an emergency and a continuing need for the invention and development of novel antimalarial agents to treat vulnerable and drug-resistant burdens of malaria. A significant problem of malaria treatment and control is drug resistance procured by malaria parasites. one of the majorly examined enzymes in antimalarial drug composition due to its prospective role in Deoxyribonucleic acid (DNA) synthesis is Dihydrofolate Reductase (DHFR) in Plasmodium falciparum (PfDHFR- Thymidylate synthase (TS); TS refers to DHFR-linked thymidylate synthase in Plasmodium falciparum), which prompted the depletion of dihydrofolate to tetrahydrofolate. Hence, the purpose of this research aims to recognize prospective hits inhibiting DHFR and optimize them to the highest effectiveness and harmlessness in malaria treatment with a design strategy approach from the Chembl database, we procured Cycloguanil derivatives with biological activity data (pKi). The three-dimensional physicochemical captions of the compounds were computed. Quantitative structure activity relationship (QSAR) model was constructed and a molecular mechanism was deduced by docking assay. Appertaining to the analysis, eleven (11) 3D descriptors were found to be accountable for pharmacological result related with Cycloguanil derivatives while hydrogen bonds were found to be ascribed to their strong binding affinities. The generated QSAR model was attested and found to be strong, which can be used to predict the action of novel compounds to the design of new antimalarials.
dc.identifier.citationAgede, O.A., Bojuwoye, M.O., Adenike, A.F., Mokuolu, O.A., Falade, C.O. (2022). 3D Quantitative structure–activity relationship to predict the anti-malarial activity in a set of Cycloguanil Analogs. Discovery, 58(322), 1097-1108, Published by Discovery Scientific Society. Available online at https://www.discoveryjournals.org/discovery/current_issue/v58/n322
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/123456789/14409
dc.language.isoen
dc.publisherDiscovery Scientific Society
dc.subjectMalaria
dc.subjectLipophilic
dc.subjectQSAR model
dc.subjectDHFR
dc.subjectCycloguanil
dc.title3D Quantitative structure–activity relationship to predict the anti-malarial activity in a set of Cycloguanil Analogs
dc.typeArticle

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