Konstantinos Kalogeropoulos, Vlad Rosca, Carol O'Brien, Charlotte Risager Christensen, Rahmat Grahadi, Christoffer Vinther Sørensen, Max D. Overath, Diego Ruiz Espi, David E. Jenkins, Ulrich auf dem Keller, Andreas H. Laustsen, Thomas J. Fryer, Timothy P. Jenkins
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. © 2024 The Authors
Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark; Department of Biology, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, Malang, Indonesia; BettercallPaul, Munich, Germany
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