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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578090
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dc.contributor.authorSiti Nur Athirah Mohd Kaspi (Universiti Kebangsaan Malaysia)
dc.contributor.authorNisha Govender (Universiti Kebangsaan Malaysia)
dc.contributor.authorZeti-Azura Mohamed-Hussein (Universiti Kebangsaan Malaysia)
dc.date.accessioned2023-11-06T02:58:23Z-
dc.date.available2023-11-06T02:58:23Z-
dc.date.issued2022-02
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:131109
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578090-
dc.descriptionCat’s whiskers or the ‘misai kucing’ is an herbal plant native to the Southeast Asian region. The polyphenol enriched leaf extract contains numerous medicinal properties of major pharmaceutical interest. In this study, selected cat’s whiskers polyphenols were screened computationally to predict the minimum binding affinities with severe acute respiratory syndrome coronavirus (SARS-CoV) molecular targets. Molecular docking analysis showed that the caffeic acid derivatives and polymethoxylated flavonoids from cat’s whiskers bound stably to the binding pocket regions of SARS-CoV molecular targets at -4.2 to -7.1 kcal/mol. Furthermore, these cat’s whiskers polyphenol-bound SARS-CoV complexes were held fairly strongly by hydrophobic interactions, hydrogen bonds, and electrostatic interactions at various extents.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journal of Tropical Agricultural Science
dc.relation.urihttp://www.pertanika.upm.edu.my/pjtas/browse/regular-issue?decade=2030&year=2022&journal=JTAS-45-1-2
dc.rightsUniversiti Putra Malaysia Press
dc.subjectCoV-2
dc.subjectCOVID-19
dc.subjectMisai kucing
dc.subjectMolecular docking
dc.subjectMolecular target
dc.subjectPolyphenol
dc.subjectSARS- therapeutics
dc.titleBrief communication: caffeic acid derivatives and polymethoxylated flavonoids from cat’s whiskers (Orthosiphon stamineus) form stable complexes with SARS-CoV molecular targets: an in silico analysis
dc.typeJournal Article
dc.format.volume45
dc.format.pages235-244
dc.format.issue1
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