In silico approaches supporting drug repurposing for Leishmaniasis: A scoping review

The shortage of treatment options for leishmaniasis, especially those easy to administer and viable for deployment in the world's poorest regions, highlights the importance of employing these strategies to cost-effectively investigate repurposing candidates. This scoping review aims to map the studies using in silico methodologies for drug repurposing against leishmaniasis. This study followed JBI recommendations for scoping reviews. Articles were searched on PubMed, Scopus, and Web of Science databases using keywords related to leishmaniasis and in silico methods for drug discovery, without publication date restrictions. The selection was based on primary studies involving computational methods for antileishmanial drug repurposing. Information about methodologies, obtained data, and outcomes were extracted. After the full-text appraisal, 34 studies were included in this review. Molecular docking was the preferred method for evaluating repurposing candidates (n=25). Studies reported 154 unique ligands and 72 different targets, sterol 14-alpha demethylase and trypanothione reductase being the most frequently reported. In silico screening was able to correctly pinpoint some known active pharmaceutical classes and propose previously untested drugs. Fifteen drugs investigated in silico exhibited low micromolar inhibition (IC50 < 10 µM) of Leishmania spp. in vitro. In conclusion, several in silico repurposing candidates are yet to be investigated in vitro and in vivo. Future research could expand the number of targets screened and employ advanced methods to optimize drug selection, offering new starting points for treatment development.

利什曼病（Leishmaniasis）的治疗方案匮乏，尤其是那些易于给药、可在全球最贫困地区推广使用的方案，凸显了采用此类策略以低成本高效能筛选药物重定位候选化合物的重要性。本范围综述旨在梳理针对利什曼病、采用计算机模拟（in silico）方法开展药物重定位研究的相关文献。本研究遵循JBI针对范围综述的指南开展。研究通过PubMed、Scopus及Web of Science数据库进行文献检索，使用与利什曼病、药物发现相关的计算机模拟方法相关的关键词，未设置发表日期限制。文献筛选基于涉及抗利什曼病药物重定位计算方法的原始研究。研究人员提取了涉及研究方法、所得数据与研究结果的相关信息。经全文评估后，本综述共纳入34项研究。分子对接（Molecular docking）是评估重定位候选化合物的首选方法（n=25）。研究共报道了154种独特配体与72种不同靶点，其中甾醇14-α脱甲基酶（sterol 14-alpha demethylase）与锥硫氧还蛋白还原酶（trypanothione reductase）的报道频次最高。计算机模拟筛选可准确识别部分已知活性药物类别，并提出此前未被测试过的药物候选。经计算机模拟研究的15种药物在体外实验中对利什曼原虫属（Leishmania spp.）表现出低微摩尔级抑制活性（半数抑制浓度IC50 < 10 µM）。综上，部分计算机模拟筛选得到的药物重定位候选化合物尚未开展体外与体内实验验证。未来研究可扩大筛选靶点范围，采用先进方法优化药物筛选流程，为抗利什曼病治疗药物的开发提供新的起点。