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Toxicity profiling and prioritization of plant-derived antimalarial agents.
SAR and QSAR in Environmental Research ( IF 2.3 ) Pub Date : 2019-09-30 , DOI: 10.1080/1062936x.2019.1665844
J Devillers 1 , H Devillers 2
Affiliation  

Human malaria is the most widespread mosquito-borne life-threatening disease worldwide. In the absence of effective vaccines, prevention and treatment of malaria only depend on prophylaxis and drug-based therapy either in monotherapy or in combination. Unfortunately, the number of available antimalarial drugs presenting different mechanisms of action is rather limited. In addition, the appearance of drug-resistance in the parasite strains impacts the efficacy of the treatments. As a result, there is a crucial need to find new drugs to circumvent resistance problems. In the quest to identify new antimalarial agents a huge number of plant-derived compounds (PDCs) have been investigated. Surprisingly in the in silico PDC screening programs, toxicity filters are either never used or so simple that their interest is limited. In this context, the goal of this study was to show how to take advantage of validated toxicity QSAR models for refining the selection of PDCs. From an original data set of 507 PDCs collected from the literature, the use of toxicity filters for endocrine disruption, developmental toxicity, and hepatotoxicity in conjunction with classical pharmacokinetic filters allowed us to obtain a list of 31 compounds of potential interest. The pros and cons of such a strategy have been discussed.



中文翻译:

植物来源的抗疟药的毒性分析和优先级排序。

人类疟疾是全世界最广泛的蚊媒性威胁生命的疾病。在没有有效疫苗的情况下,疟疾的预防和治疗仅取决于单一疗法或联合疗法的预防和基于药物的疗法。不幸的是,呈现出不同作用机制的可用抗疟药的数量相当有限。另外,寄生虫菌株中耐药性的出现影响了治疗的效力。结果,迫切需要寻找新药来规避耐药性问题。为了寻找新的抗疟药,已经研究了大量植物来源的化合物(PDC)。令人惊讶的是,在计算机上的PDC筛选程序中,从未使用过毒性过滤器,或者如此简单,以至于对它们的兴趣受到限制。在这种情况下,这项研究的目的是展示如何利用经过验证的毒性QSAR模型来完善PDC的选择。从文献中收集的507个PDC的原始数据集中,将毒性过滤器用于内分泌破坏,发育毒性和肝毒性与经典药代动力学过滤器的结合使用,使我们获得了31种潜在感兴趣的化合物的清单。讨论了这种策略的利弊。肝毒性和经典药代动力学过滤器的结合使我们获得了31种潜在感兴趣的化合物的清单。讨论了这种策略的利弊。肝毒性和经典药代动力学过滤器的结合使我们获得了31种潜在感兴趣的化合物的清单。讨论了这种策略的利弊。

更新日期:2019-09-30
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