Computational Strategies for Broad Spectrum Venom Phospholipase A<sub>2</sub> Inhibitors

Snakebite envenoming is a persistent cause of mortality and morbidity worldwide due to the logistical challenges and costs of current antibody-based treatments. Their persistence motivates a broad interest in the discovery of inhibitors against multispecies venom phospholipase A<sub>2</sub> (PLA<sub>2</sub>), which are underway as an alternative or supplemental treatment to improve health outcomes. Here, we present new computational strategies for improved inhibitor classification for challenging metalloenzyme targets across many species, including both a new method to utilize existing molecular docking, and subsequent data normalization. These methods were improved to support experimental screening efforts estimating the broader efficacy of candidate PLA<sub>2</sub> inhibitors against diverse viper and elapid venoms.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-04-22
DOI
https://doi.org/10.1021/acs.jcim.5c00045
Citations
1
Primary Topic
Venomous Animal Envenomation and Studies
Type
article
Field-Weighted Citation Impact
1.82

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article

Computational Strategies for Broad Spectrum Venom Phospholipase A2 Inhibitors

Daan P. Geerke, Jeroen Kool, Laura-Oana Albulescu, Nicholas R. Casewell et al.
1 citations
Journal of Chemical Information and Modeling
Venomous Animal Envenomation and Studies
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article

Computational Strategies for Broad Spectrum Venom Phospholipase A2 Inhibitors

Daan P. Geerke, Jeroen Kool, Laura-Oana Albulescu, Nicholas R. Casewell, David A. Poole
article en
1 citations

Abstract

Snakebite envenoming is a persistent cause of mortality and morbidity worldwide due to the logistical challenges and costs of current antibody-based treatments. Their persistence motivates a broad interest in the discovery of inhibitors against multispecies venom phospholipase A<sub>2</sub> (PLA<sub>2</sub>), which are underway as an alternative or supplemental treatment to improve health outcomes. Here, we present new computational strategies for improved inhibitor classification for challenging metalloenzyme targets across many species, including both a new method to utilize existing molecular docking, and subsequent data normalization. These methods were improved to support experimental screening efforts estimating the broader efficacy of candidate PLA<sub>2</sub> inhibitors against diverse viper and elapid venoms.

Journal of Chemical Information and ModelingVol. 65(9)
Liverpool School of Tropical Medicine (GB), Vrije Universiteit Amsterdam (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek
Openalex Percentile: Top 17%
Venomous Animal Envenomation and Studies
1.82
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