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基于结构的可购买批准药物和天然化合物在线筛选:癌症靶点药物重新定位的回顾性实例

Online structure-based screening of purchasable approved drugs and natural compounds: retrospective examples of drug repositioning on cancer targets.

作者信息

Lagarde Nathalie, Rey Julien, Gyulkhandanyan Aram, Tufféry Pierre, Miteva Maria A, Villoutreix Bruno O

机构信息

Université Paris Diderot, Sorbonne Paris Cité, Molécules Thérapeutiques In Silico, INSERM UMR-S 973, Paris, France.

INSERM, U973, Paris, France.

出版信息

Oncotarget. 2018 Aug 17;9(64):32346-32361. doi: 10.18632/oncotarget.25966.

Abstract

Drug discovery is a long and difficult process that benefits from the integration of virtual screening methods in experimental screening campaigns such as to generate testable hypotheses, accelerate and/or reduce the cost of drug development. Current drug attrition rate is still a major issue in all therapeutic areas and especially in the field of cancer. Drug repositioning as well as the screening of natural compounds constitute promising approaches to accelerate and improve the success rate of drug discovery. We developed three compounds libraries of purchasable compounds: Drugs-lib, FOOD-lib and NP-lib that contain approved drugs, food constituents and natural products, respectively, that are optimized for structure-based virtual screening studies. The three compounds libraries are implemented in the MTiOpenScreen web server that allows users to perform structure-based virtual screening computations on their selected protein targets. The server outputs a list of 1,500 molecules with predicted binding scores that can then be processed further by the users and purchased for experimental validation. To illustrate the potential of our service for drug repositioning endeavours, we selected five recently published drugs that have been repositioned and/or on cancer targets. For each drug, we used the MTiOpenScreen service to screen the Drugs-lib collection against the corresponding anti-cancer target and we show that our protocol is able to rank these drugs within the top ranked compounds. This web server should assist the discovery of promising molecules that could benefit patients, with faster development times, and reduced costs and risk.

摘要

药物发现是一个漫长而艰难的过程,虚拟筛选方法与实验筛选活动的整合有助于该过程,例如生成可测试的假设、加速和/或降低药物开发成本。目前,药物损耗率在所有治疗领域,尤其是癌症领域,仍然是一个主要问题。药物重新定位以及天然化合物的筛选是加速和提高药物发现成功率的有前景的方法。我们开发了三个可购买化合物的文库:药物文库(Drugs-lib)、食品文库(FOOD-lib)和天然产物文库(NP-lib),分别包含经批准的药物、食品成分和天然产物,这些文库针对基于结构的虚拟筛选研究进行了优化。这三个化合物文库在MTiOpenScreen网络服务器中实现,该服务器允许用户对其选定的蛋白质靶点进行基于结构的虚拟筛选计算。服务器输出一份包含1500个分子的列表,以及预测的结合分数,然后用户可以进一步处理这些信息并购买这些分子用于实验验证。为了说明我们的服务在药物重新定位工作中的潜力,我们选择了五种最近发表的已重新定位和/或针对癌症靶点的药物。对于每种药物,我们使用MTiOpenScreen服务针对相应的抗癌靶点筛选药物文库(Drugs-lib),结果表明我们的方案能够将这些药物排在排名靠前的化合物之中。这个网络服务器应该有助于发现有前景的分子,从而使患者受益,同时缩短开发时间,降低成本和风险。

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