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计算方法在针对利什曼原虫和锥虫引起的疾病的药物发现中的应用。

Computational approaches for drug discovery against trypanosomatid-caused diseases.

机构信息

Universidad de Buenos Aires, Facultad de Medicina, Instituto de Investigaciones Médicas A. Lanari, Buenos Aires, Argentina.

Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Instituto de Investigaciones Médicas, Laboratorio de Parasitología Molecular, Buenos Aires, Argentina.

出版信息

Parasitology. 2020 May;147(6):611-633. doi: 10.1017/S0031182020000207. Epub 2020 Feb 12.

Abstract

During three decades, only about 20 new drugs have been developed for malaria, tuberculosis and all neglected tropical diseases (NTDs). This critical situation was reached because NTDs represent only 10% of health research investments; however, they comprise about 90% of the global disease burden. Computational simulations applied in virtual screening (VS) strategies are very efficient tools to identify pharmacologically active compounds or new indications for drugs already administered for other diseases. One of the advantages of this approach is the low time-consuming and low-budget first stage, which filters for testing experimentally a group of candidate compounds with high chances of binding to the target and present trypanocidal activity. In this work, we review the most common VS strategies that have been used for the identification of new drugs with special emphasis on those applied to trypanosomiasis and leishmaniasis. Computational simulations based on the selected protein targets or their ligands are explained, including the method selection criteria, examples of successful VS campaigns applied to NTDs, a list of validated molecular targets for drug development and repositioned drugs for trypanosomatid-caused diseases. Thereby, here we present the state-of-the-art of VS and drug repurposing to conclude pointing out the future perspectives in the field.

摘要

三十年来,仅针对疟疾、结核病和所有被忽视的热带病(NTDs)开发了约 20 种新药。之所以出现这种严峻局面,是因为 NTDs 在健康研究投资中仅占 10%,但其占全球疾病负担的 90%左右。在虚拟筛选(VS)策略中应用的计算模拟是识别具有药理活性的化合物或已用于治疗其他疾病的药物的新适应症的非常有效的工具。这种方法的一个优点是低耗时和低预算的第一阶段,它可以筛选出一组候选化合物,这些化合物有很大的可能与目标结合并具有杀锥虫活性。在这项工作中,我们回顾了最常用于鉴定新药物的最常见的 VS 策略,特别强调了那些应用于锥虫病和利什曼病的策略。解释了基于所选蛋白靶标或其配体的计算模拟,包括方法选择标准、成功应用于 NTDs 的 VS 活动的示例、用于药物开发的验证分子靶标的列表以及针对锥虫引起的疾病的重新定位药物。因此,在这里我们介绍了 VS 和药物重定位的最新进展,以指出该领域的未来展望。

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