Poole David A, Albulescu Laura-Oana, Kool Jeroen, Casewell Nicholas R, Geerke Daan P
Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute for Molecular and Life Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV, the Netherlands.
Centre for Snakebite Research & Interventions, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, U.K.
J Chem Inf Model. 2025 May 12;65(9):4593-4601. doi: 10.1021/acs.jcim.5c00045. Epub 2025 Apr 22.
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 (PLA), 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 inhibitors against diverse viper and elapid venoms.
由于目前基于抗体的治疗方法存在后勤保障方面的挑战和成本问题,蛇咬伤中毒仍是全球范围内导致死亡和发病的一个持续原因。这些问题促使人们广泛关注发现针对多种蛇毒磷脂酶A(PLA)的抑制剂,目前正在进行相关研究,将其作为一种替代或补充治疗方法以改善健康结果。在此,我们提出了新的计算策略,用于改进对多种物种中具有挑战性的金属酶靶点的抑制剂分类,包括一种利用现有分子对接的新方法以及后续的数据归一化。这些方法得到了改进,以支持实验筛选工作,评估候选PLA抑制剂对不同蝰蛇和眼镜蛇科蛇毒的更广泛疗效。