Evidence map›Paper›PMID 40591646›Full record

ArticlePloS one2025

Network pharmacognosy of Galphimia glauca: Mapping the molecular landscape of a traditional Mexican medicinal plant.

María José Cambero Acosta, Guillermo de Anda-Jáuregui

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

2 authors.

María José Cambero AcostaComputational Genomics Department, Instituto Nacional de Medicina Genómica, Ciudad de México, México.
Guillermo de Anda-JáureguiComputational Genomics Department, Instituto Nacional de Medicina Genómica, Ciudad de México, México.ORCID https://orcid.org/0000-0002-7749-0365

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study explores the pharmacological landscape of Galphimia glauca, a traditional Mexican medicinal plant known for its sedative and anti-inflammatory effects. Using network pharmacognosy, we analyzed the interactions of G. glauca's bioactive compounds, Galphimines A-I, with human protein targets. SwissTargetPrediction identified 214 unique protein targets across the galphimines, revealing a core-periphery structure in a bipartite network where 41 targets are shared among all compounds. Further interaction analysis using STRING-DB generated a dense protein-protein interaction network comprising 1,386 connections. Centrality analysis highlighted proteins such as SRC, MTOR, and MAPK3 as key nodes involved in cell growth, proliferation, and immune regulation pathways, suggesting these as pivotal mediators of G. glauca's pharmacological effects. Community detection with the Walktrap algorithm further segmented the network into functionally relevant modules linked to cell survival, immune response, and inflammation, reflecting the therapeutic effects historically attributed to G. glauca. Our findings underscore the plant's multi-target therapeutic potential and highlight the value of network-based approaches in understanding traditional medicine. This work lays the groundwork for further studies aimed at refining therapeutic strategies based on G. glauca's bioactive compounds and suggests network pharmacognosy as a promising tool for assessing other traditional medicinal plants.

Indexed as

GalphimiaNetwork PharmacologyPharmacognosyPlant ExtractsPlants, MedicinalAlgorithmsAnti-Inflammatory AgentsCell SurvivalHumansImmunity, CellularMexicoProtein Interaction MappingProtein Interaction MapsAnti-Inflammatory AgentsGalphimia glauca extractPlant Extracts

Identifiers

PMID40591646
PMCPMC12212526

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

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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 Socratic graph.