首页> 美国卫生研究院文献>PLoS Clinical Trials >The integration of pharmacophore-based 3D QSAR modeling and virtual screening in safety profiling: A case study to identify antagonistic activities against adenosine receptor, A2A, using 1,897 known drugs
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The integration of pharmacophore-based 3D QSAR modeling and virtual screening in safety profiling: A case study to identify antagonistic activities against adenosine receptor, A2A, using 1,897 known drugs

机译:基于药效团的3D QSAR建模和虚拟筛选在安全性分析中的集成:使用1897种已知药物鉴定针对腺苷受体A2A拮抗活性的案例研究

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摘要

Safety pharmacology screening against a wide range of unintended vital targets using in vitro assays is crucial to understand off-target interactions with drug candidates. With the increasing demand for in vitro assays, ligand- and structure-based virtual screening approaches have been evaluated for potential utilization in safety profiling. Although ligand based approaches have been actively applied in retrospective analysis or prospectively within well-defined chemical space during the early discovery stage (i.e., HTS screening and lead optimization), virtual screening is rarely implemented in later stage of drug discovery (i.e., safety). Here we present a case study to evaluate ligand-based 3D QSAR models built based on in vitro antagonistic activity data against adenosine receptor 2A (A2A). The resulting models, obtained from 268 chemically diverse compounds, were used to test a set of 1,897 chemically distinct drugs, simulating the real-world challenge of safety screening when presented with novel chemistry and a limited training set. Due to the unique requirements of safety screening versus discovery screening, the limitations of 3D QSAR methods (i.e., chemotypes, dependence on large training set, and prone to false positives) are less critical than early discovery screen. We demonstrated that 3D QSAR modeling can be effectively applied in safety assessment prior to in vitro assays, even with chemotypes that are drastically different from training compounds. It is also worth noting that our model is able to adequately make the mechanistic distinction between agonists and antagonists, which is important to inform subsequent in vivo studies. Overall, we present an in-depth analysis of the appropriate utilization and interpretation of pharmacophore-based 3D QSAR models for safety screening.
机译:使用体外测定针对大量意外生命目标进行安全药理学筛选,对于了解脱靶药物与候选药物的相互作用至关重要。随着对体外测定的需求的增加,已经评估了基于配体和基于结构的虚拟筛选方法在安全性分析中的潜在用途。尽管在早期发现阶段(即HTS筛选和前导优化)期间,基于配体的方法已积极地应用于回顾性分析或明确定义的化学空间内(例如,HTS筛选和前导优化),但在药物发现的后期阶段(即安全性)很少进行虚拟筛选。在这里,我们提出了一个案例研究,以评估基于对腺苷受体2A(A2A)的体外拮抗活性数据建立的基于配体的3D QSAR模型。从268种化学上不同的化合物中获得的模型被用来测试一组1,897种化学上不同的药物,以新颖的化学方法和有限的培训来模拟现实世界中安全筛选的挑战。由于安全筛选与发现筛选的独特要求,与早期发现筛选相比,3D QSAR方法的局限性(即化学型,对大型训练集的依赖以及容易出现假阳性)没有那么关键。我们证明了3D QSAR建模可以有效地应用于体外分析之前的安全评估,即使化学类型与训练化合物完全不同也是如此。还值得注意的是,我们的模型能够充分区分激动剂和拮抗剂之间的机制,这对于后续的体内研究非常重要。总体而言,我们对基于药效团的3D QSAR模型进行安全筛选的适当利用和解释进行了深入分析。

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