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通过基于配体的虚拟筛选和生物学评估鉴定新型利什曼原虫二肽羧肽酶抑制剂。

Identification of novel inhibitors of dipeptidylcarboxypeptidase of Leishmania donovani via ligand-based virtual screening and biological evaluation.

机构信息

Division of Biochemistry, CSIR-Central Drug Research Institute, Council of Scientific and Industrial Research, Chattar Manzil Palace, PO Box 173, Lucknow 22600, India.

出版信息

Chem Biol Drug Des. 2012 Feb;79(2):149-56. doi: 10.1111/j.1747-0285.2011.01262.x. Epub 2011 Nov 28.

Abstract

Current treatment of leishmaniasis is based on chemotherapy, which relies on a handful of drugs with serious limitations, such as high cost, toxicity, and lack of efficacy in endemic regions. Therefore, development of new, effective, and affordable anti-leishmanial drugs is a global health priority. Dipeptidylcarboxypeptidase has been characterized and established as a drug target for antileishmanial drug discovery. We virtually screened a large chemical library of 15 452 compounds against a 3D model of dipeptidylcarboxypeptidase to identify novel inhibitors. The initial virtual screening using a ligand-based pharmacophore model identified 103 compounds. Forty-six compounds were shortlisted based on the docking scores and other scoring functions. Further, these compounds were subjected to biological assay, and four of them belonging to two chemical classes were identified as the lead compounds. Identification of these novel and chemically diverse inhibitors should provide leads to be optimized into candidates to treat these protozoan infections.

摘要

目前的利什曼病治疗方法基于化疗,而化疗依赖于少数几种具有严重局限性的药物,如成本高、毒性大以及在流行地区疗效不佳。因此,开发新的、有效且负担得起的抗利什曼病药物是全球卫生的重点。二肽基羧肽酶已被表征并确立为抗利什曼病药物发现的药物靶点。我们针对二肽基羧肽酶的三维模型虚拟筛选了一个包含 15452 种化合物的大型化学库,以鉴定新型抑制剂。最初使用基于配体的药效团模型的虚拟筛选鉴定出 103 种化合物。根据对接评分和其他评分函数,有 46 种化合物被列入候选名单。进一步对这些化合物进行了生物测定,其中属于两个化学类别的 4 种化合物被鉴定为先导化合物。这些新型且化学多样性的抑制剂的鉴定应提供先导化合物,以优化为治疗这些原生动物感染的候选药物。

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