Cheminformatic approaches to hit-prioritization and target prediction of potential anti-mrsa natural products

dc.contributor.advisorEgieyeh, Samuel
dc.contributor.advisorChristoffels, Alan
dc.contributor.authorOselusi, Samson Olaitan
dc.date.accessioned2021-04-19T11:10:00Z
dc.date.accessioned2024-05-15T07:42:49Z
dc.date.available2021-04-19T11:10:00Z
dc.date.available2024-05-15T07:42:49Z
dc.date.issued2020
dc.descriptionMagister Pharmaceuticae - MPharmen_US
dc.description.abstractThe growing resistance of Methicillin-Resistant Staphylococcus aureus (MRSA) to currently prescribed drugs has resulted in the failure of prevention and treatment of different infections caused by the superbug. Therefore, to keep pace with the resistance, there is a pressing need for novel antimicrobial agents, especially from non-conventional sources. Several natural products (NPs) have displayed varying in vitro activities against the pathogen but few of these natural compounds have been studied for their prospects to be potential antimicrobial drug candidates. This may be due to the high cost, tedious, and time-consuming process of conducting the important preclinical tests on these compounds. Hence, there is a need for cost-effective strategies for mining the available data on these natural compounds. This would help to get the knowledge that may guide rational prioritization of “likely to succeed” natural compounds to be developed into potential antimicrobial drug candidates.en_US
dc.identifier.urihttps://hdl.handle.net/10566/15144
dc.language.isoenen_US
dc.publisherUniversity of Western Capeen_US
dc.rights.holderUniversity of Western Capeen_US
dc.subjectCheminformaticen_US
dc.subjectNatural productsen_US
dc.subjectProfilingen_US
dc.subjectPharmacokineticsen_US
dc.subjectDrug-likenessen_US
dc.titleCheminformatic approaches to hit-prioritization and target prediction of potential anti-mrsa natural productsen_US

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