Soni Mohini, Pratap J Venkatesh
Biochemistry and Structural Biology Division, CSIR-Central Drug Research Institute, Sector-10, Jankipuram Extension, Sitapur Road, Lucknow 226031, India.
Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
Pathogens. 2022 Aug 22;11(8):950. doi: 10.3390/pathogens11080950.
The neglected tropical disease (NTD) leishmaniasis is the collective name given to a diverse group of illnesses caused by ~20 species belonging to the genus , a majority of which are vector borne and associated with complex life cycles that cause immense health, social, and economic burdens locally, but individually are not a major global health priority. Therapeutic approaches against leishmaniasis have various inadequacies including drug resistance and a lack of effective control and eradication of the disease spread. Therefore, the development of a rationale-driven, target based approaches towards novel therapeutics against leishmaniasis is an emergent need. The utilization of Artificial Intelligence/Machine Learning methods, which have made significant advances in drug discovery applications, would benefit the discovery process. In this review, following a summary of the disease epidemiology and available therapies, we consider three important leishmanial metabolic pathways that can be attractive targets for a structure-based drug discovery approach towards the development of novel anti-leishmanials. The folate biosynthesis pathway is critical, as is auxotrophic for folates that are essential in many metabolic pathways. can not synthesize purines , and salvage them from the host, making the purine salvage pathway an attractive target for novel therapeutics. also possesses an organelle glycosome, evolutionarily related to peroxisomes of higher eukaryotes, which is essential for the survival of the parasite. Research towards therapeutics is underway against enzymes from the first two pathways, while the third is as yet unexplored.
被忽视的热带病利什曼病是由利什曼原虫属约20个物种引起的多种疾病的统称，其中大多数是通过媒介传播的，并且具有复杂的生命周期，在当地造成了巨大的健康、社会和经济负担，但单个来看并非全球主要的卫生重点。针对利什曼病的治疗方法存在各种不足，包括耐药性以及缺乏对疾病传播的有效控制和根除手段。因此，迫切需要开发一种基于合理依据、以靶点为基础的新型利什曼病治疗方法。在药物发现应用方面取得重大进展的人工智能/机器学习方法的运用，将有利于发现过程。在本综述中，在总结疾病流行病学和现有治疗方法之后，我们考虑了三种重要的利什曼原虫代谢途径，它们可能成为基于结构的药物发现方法开发新型抗利什曼病药物的有吸引力的靶点。叶酸生物合成途径至关重要，因为利什曼原虫对许多代谢途径中必需的叶酸是营养缺陷型。利什曼原虫无法合成嘌呤，而是从宿主中挽救嘌呤，这使得嘌呤补救途径成为新型治疗药物的一个有吸引力的靶点。利什曼原虫还拥有一种细胞器糖体，在进化上与高等真核生物的过氧化物酶体相关，这对寄生虫的生存至关重要。针对前两种途径中的酶的治疗研究正在进行中，而第三种途径尚未得到探索。
