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Analytical methods for honeybee venom characterization

2022Journal article Open access
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dc.contributor.authorMehdi, Iouraouine El
dc.contributor.authorFalcão, Soraia
dc.contributor.authorBoujraf, Saïd
dc.contributor.authorMustapha, Harandou
dc.contributor.authorCampos, Maria G.
dc.contributor.authorVilas-Boas, Miguel
dc.date.accessioned2023-02-08T14:04:15Z
dc.date.available2023-02-08T14:04:15Z
dc.date.issued2022
dc.description.abstractThe discovery of new drugs has benefited significantly from the development of research in venomics, increasing our understanding of the envenomation processes. It has been previously reported that honeybee venom (HBV) exhibits several pharmacological activities such as anti‑inflammatory, antibacterial, antimutagenic, radioprotective, and anticancer activity and may inclusively act as a complementary treatment for SARS‑CoV‑2. It composition consists mainly on melittin, phospholipase A2, and apamin but other constituents such as hyaluronidase, mast cell degranulating peptide and secapin are also relevant for its bioactivity. However, and because HBV is not officially recognized as a drug, until now, the international community did not establish quality standards for it. To uncover its exact composition, and boost the discovery of HBV‑derived drugs, a significant number of techniques were developed. In this review, a relevant overview of the so far published analytical methods for HBV characterization is organized with the aim to accelerate its future standardization. The literature search was performed within PubMed, Google Scholar, and Science Direct by selecting specific documents and exploring HBV evaluation.pt_PT
dc.description.sponsorshipThanks to the Foundation Science and Technology (FCT, Portugal) for support by national funds to CIMO (UIDB/00690/2020). The project PDR2020‑1.0.1‑FEADER‑031734: “DivInA‑Diversification and Innovation on Beekeeping Production” and to the European Regional Development Fund through the Regional Operational Program North 2020, within the scope of Project GreenHealth, Norte‑01‑0145‑FEDER‑000042. This research was also funded by (UI0204): UIDB/00313/2020, Center of Chemistry from Faculty of Sciences and Technology of University of Coimbra, Portugal.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMehdi, Iouraouine El; Falcão, Soraia; Boujraf, Saïd; Mustapha, Harandou; Campos, Maria G.; Vilas-Boas, Miguel (2022). Analytical methods for honeybee venom characterization. Journal of Advanced Pharmaceutical Technology & Research. ISSN 2231-4040. 13:3, p. 154-160pt_PT
dc.identifier.doi10.4103/japtr.japtr_166_21pt_PT
dc.identifier.issn2231-4040
dc.identifier.issn0976-2094
dc.identifier.urihttp://hdl.handle.net/10198/26816
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWolters Kluwerpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectAnalytical methodspt_PT
dc.subjectApaminpt_PT
dc.subjectEnzymespt_PT
dc.subjectMast cell degranulating peptidept_PT
dc.subjectPeptidespt_PT
dc.subjectVenomicspt_PT
dc.titleAnalytical methods for honeybee venom characterizationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage160pt_PT
oaire.citation.issue3pt_PT
oaire.citation.startPage154pt_PT
oaire.citation.titleJournal of Advanced Pharmaceutical Technology & Researchpt_PT
oaire.citation.volume13pt_PT
person.familyNameFalcão
person.familyNameVilas-Boas
person.givenNameSoraia
person.givenNameMiguel
person.identifier711432
person.identifier1693134
person.identifier.ciencia-idD41A-6BED-4CBB
person.identifier.ciencia-idA918-C6FF-81A4
person.identifier.orcid0000-0003-3735-6951
person.identifier.orcid0000-0002-8665-5280
person.identifier.ridI-5949-2013
person.identifier.scopus-author-id14832459200
person.identifier.scopus-author-id6602648497
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication5746ab3e-8ffe-4e26-9a41-8392cf031f28
relation.isAuthorOfPublicationf58280c8-298b-4e4c-9f7c-4517300d3382
relation.isAuthorOfPublication.latestForDiscoveryf58280c8-298b-4e4c-9f7c-4517300d3382

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