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Metabolome-Based Classification of Snake Venoms by Bioinformatic Tools

Alonso, Luis L., Slagboom, Julien, Casewell, Nicholas ORCID:, Samanipour, Saer and Kool, Jeroen (2023) 'Metabolome-Based Classification of Snake Venoms by Bioinformatic Tools'. Toxins, Vol 15, Issue 2, e161.

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Snakebite is considered a neglected tropical disease, and it is one of the most intricate ones. The variability found in snake venom is what makes it immensely complex to study. These variations are present both in the big and the small molecules found in snake venom. This study focused on examining the variability found in the venom’s small molecules (i.e., mass range of 100–1000 Da) between two main families of venomous snakes—Elapidae and Viperidae—managing to create a model able to classify unknown samples by means of specific features, which can be extracted from their LC–MS data and output in a comprehensive list. The developed model also allowed further insight into the composition of snake venom by highlighting the most relevant metabolites of each group by clustering similarly composed venoms. The model was created by means of support vector machines and used 20 features, which were merged into 10 principal components. All samples from the first and second validation data subsets were correctly classified. Biological hypotheses relevant to the variation regarding the metabolites that were identified are also given.

Item Type: Article
Subjects: QV Pharmacology > Toxicology > General Toxicology > QV 600 General works
WC Communicable Diseases > Tropical and Parasitic Diseases > WC 680 Tropical diseases (General)
WD Disorders of Systemic, Metabolic or Environmental Origin, etc > Animal Poisons > WD 410 Reptiles
Faculty: Department: Biological Sciences > Department of Tropical Disease Biology
Digital Object Identifer (DOI):
SWORD Depositor: JISC Pubrouter
Depositing User: JISC Pubrouter
Date Deposited: 27 Feb 2023 15:41
Last Modified: 27 Feb 2023 15:41


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