V-ToCs (Venom Toxin Clustering): A tool for the investigation of sequence and structure similarities in snake venom toxins

Recently, there has been a major push toward the development of next-generation treatments against snakebite envenoming. However, unlike current antivenoms that rely on animal-derived polyclonal antibodies, most of these novel approaches are reliant on an in-depth understanding of the over 2000 known snake venom toxins. Indeed, by identifying similarities (i.e., conserved epitopes) across these different toxins, it is possible to design cross-reactive treatments, such as broadly-neutralising antibodies, that target these similarities. Therefore, in this project, we built an automated pipeline that generates sequence and structural distance matrices and homology trees across all available snake venom toxin sequences and structures. To facilitate analysis, we also developed a user-friendly and high-throughput visualisation tool, coined "Venom TOxin CluStering" (V-ToCs). This tool allows researchers to easily investigate sequence and structure patterns in snake venom toxins for a wide array of purposes, such as elucidating toxin evolution, and will also hopefully help guide the discovery and development of increasingly broadly-neutralising antivenoms in the near future.

Authors

Institutions

Publication Details

Journal
Toxicon
Published
2024-08-31
DOI
https://doi.org/10.1016/j.toxicon.2024.108088
Primary Topic
Venomous Animal Envenomation and Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

V-ToCs (Venom Toxin Clustering): A tool for the investigation of sequence and structure similarities in snake venom toxins

Thomas Fryer, Rahmat Grahadi, Carol O’Brien, Andreas H. Laustsen et al.
Toxicon
Venomous Animal Envenomation and Studies
article

V-ToCs (Venom Toxin Clustering): A tool for the investigation of sequence and structure similarities in snake venom toxins

Thomas Fryer, Rahmat Grahadi, Carol O’Brien, Andreas H. Laustsen, Christoffer V. Sørensen, Timothy P. Jenkins, David E. Jenkins, Konstantinos Kalogeropoulos, Ulrich auf dem Keller, Max D. Overath, Vlad Rosca, Diego Ruiz Espi, Charlotte Risager Christensen
article en

Abstract

Recently, there has been a major push toward the development of next-generation treatments against snakebite envenoming. However, unlike current antivenoms that rely on animal-derived polyclonal antibodies, most of these novel approaches are reliant on an in-depth understanding of the over 2000 known snake venom toxins. Indeed, by identifying similarities (i.e., conserved epitopes) across these different toxins, it is possible to design cross-reactive treatments, such as broadly-neutralising antibodies, that target these similarities. Therefore, in this project, we built an automated pipeline that generates sequence and structural distance matrices and homology trees across all available snake venom toxin sequences and structures. To facilitate analysis, we also developed a user-friendly and high-throughput visualisation tool, coined "Venom TOxin CluStering" (V-ToCs). This tool allows researchers to easily investigate sequence and structure patterns in snake venom toxins for a wide array of purposes, such as elucidating toxin evolution, and will also hopefully help guide the discovery and development of increasingly broadly-neutralising antivenoms in the near future.

ToxiconVol. 250
University of Brawijaya (ID), Schlumberger (Ireland) (IE), Technical University of Denmark (DK)
Villum Fonden, Wellcome Trust, European Commission, Novo Nordisk, Novo Nordisk Fonden, HORIZON EUROPE Framework Programme, European Research Council, Horizon 2020, H2020 European Research Council, H2020 Marie Skłodowska-Curie Actions
Openalex Percentile: Top 84%
Venomous Animal Envenomation and Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.