Evidence map›Paper›PMID 38796627›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2024

Charting the Cannabis plant chemical space with computational metabolomics.

Akhona Myoli, Mpho Choene, Abidemi Paul Kappo, Ntakadzeni Edwin Madala, Justin J J van der Hooft, Fidele Tugizimana

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Article in Metabolomics : Official journal of the Metabolomic Society, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Akhona MyoliDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa.ORCID http://orcid.org/0000-0002-7198-5084
Mpho ChoeneDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa.ORCID http://orcid.org/0000-0001-5251-8010
Abidemi Paul KappoDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa.ORCID http://orcid.org/0000-0003-2521-8957
Ntakadzeni Edwin MadalaDepartment of Biochemistry and Microbiology, University of Venda, Thohoyandou, South Africa.ORCID http://orcid.org/0000-0001-7390-2118
Justin J J van der HooftDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa. justin.vanderhooft@wur.nl.ORCID http://orcid.org/0000-0002-9340-5511
Fidele TugizimanaDepartment of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, 2006, South Africa. ftugizimana@uj.ac.za.ORCID http://orcid.org/0000-0001-8172-6599

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe chemical classification of Cannabis is typically confined to the cannabinoid content, whilst Cannabis encompasses diverse chemical classes that vary in abundance among all its varieties. Hence, neglecting other chemical classes within Cannabis strains results in a restricted and biased comprehension of elements that may contribute to chemical intricacy and the resultant medicinal qualities of the plant.

objectivesThus, herein, we report a computational metabolomics study to elucidate the Cannabis metabolic map beyond the cannabinoids.

methodsMass spectrometry-based computational tools were used to mine and evaluate the methanolic leaf and flower extracts of two Cannabis cultivars: Amnesia haze (AMNH) and Royal dutch cheese (RDC).

resultsThe results revealed the presence of different chemical compound classes including cannabinoids, but extending it to flavonoids and phospholipids at varying distributions across the cultivar plant tissues, where the phenylpropnoid superclass was more abundant in the leaves than in the flowers. Therefore, the two cultivars were differentiated based on the overall chemical content of their plant tissues where AMNH was observed to be more dominant in the flavonoid content while RDC was more dominant in the lipid-like molecules. Additionally, in silico molecular docking studies in combination with biological assay studies indicated the potentially differing anti-cancer properties of the two cultivars resulting from the elucidated chemical profiles.

conclusionThese findings highlight distinctive chemical profiles beyond cannabinoids in Cannabis strains. This novel mapping of the metabolomic landscape of Cannabis provides actionable insights into plant biochemistry and justifies selecting certain varieties for medicinal use.

Indexed as

CannabisMetabolomicsPlant LeavesCannabinoidsFlavonoidsFlowersMass SpectrometryMolecular Docking SimulationPlant ExtractsCannabinoidsFlavonoidsPlant ExtractsCannabisChemovarsComputational toolsCultivarsLC-MS/MSMedicinalMetabolic map

Identifiers

PMID38796627
PMCPMC11127828

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.