Evidence map›Paper›PMID 39760869›Full record

ReviewArchives of toxicology2025

Metabolomics and proteomics: synergistic tools for understanding snake venom inhibition.

Sana S Hussain, J Danie Kingsley

Abstract readReview
PubMed Publisher
In one paragraph

Review in Archives of toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Toxins · 2026
    Article
  3. Article
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.

Sana S HussainDepartment of Integrative Biology, School of Bioscience and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India.ORCID 0009-0007-5254-8026
J Danie KingsleyDepartment of Integrative Biology, School of Bioscience and Technology, Vellore Institute of Technology (VIT), Vellore, 632014, Tamil Nadu, India. daniekingsleybio@gmail.com.ORCID 0000-0001-7838-5017

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Snake envenomation presents a significant global health challenge, especially in rural areas of tropical and subtropical regions. Traditional antivenom therapies face limitations related to efficacy, availability, and specificity, prompting a need for novel approaches. Recent advancements in omics technologies, particularly metabolomics and proteomics, have enhanced our understanding of snake venom composition, toxicity, and potential therapeutic strategies. Metabolomics allows for the study of metabolic changes induced by venom, providing insights into disrupted pathways and possible inhibitors. Proteomics facilitates the identification and characterization of venom proteins, unveiling their interactions with therapeutic agents. Integrative databases such as the Snake Venom Database (SVDB) and STAB Profiles enhance this research by cataloging venom components and aiding in the analysis of venom-antivenom interactions. The combined application of metabolomics and proteomics has led to the identification of crucial metabolic pathways and protein targets essential for effective venom inhibition. This review explores current advances in these fields, emphasizing the role of omics in identifying novel inhibitors and developing next-generation antivenoms. The integrated approach of metabolomics and proteomics offers a comprehensive understanding of snake venom biology, paving the way for more effective and tailored therapeutic solutions for envenomation.

Indexed as

AntiveninsMetabolomicsProteomicsSnake BitesSnake VenomsAnimalsHumansAntiveninsSnake VenomsDatabasesMetabolomicsProteomicsSnake envenomationVenom proteins

Identifiers

What OpenQuestion holds

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Registered trials

None linked

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.