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Automated design of ligands to polypharmacological profiles

机译:配体的自动化设计polypharmacological型材

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摘要

The clinical efficacy and safety of a drug is determined by its activity profile across multiple proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to rationally design drugs a priori against profiles of multiple proteins would have immense value in drug discovery. We describe a new approach for the automated design of ligands against profiles of multiple drug targets. The method is demonstrated by the evolution of an approved acetylcholinesterase inhibitor drug into brain penetrable ligands with either specific polypharmacology or exquisite selectivity profiles for G-protein coupled receptors. Overall, 800 ligand-target predictions of prospectively designed ligands were tested experimentally, of which 75% were confirmed correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads where multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.
机译:药物的临床功效和安全性取决于蛋白质组中多种蛋白质的活性曲线。但是,设计具有特定多目标特征的药物既复杂又困难。因此,合理设计针对多种蛋白质特征的先验药物的方法将在药物开发中具有巨大价值。我们描述了针对多种药物靶标的配体自动设计的新方法。该方法通过将批准的乙酰胆碱酯酶抑制剂药物演变为对G蛋白偶联受体具有特定的多药理学或精湛的选择性特征的脑可穿透的配体来证明。总体上,通过实验测试了800个预期设计的配体对配体目标的预测,其中75%被证实是正确的。我们还演示了体内目标参与。该方法可能是有用的药物线索来源,其中需要多目标配置文件以实现对其他药物目标的选择性或所需的多药理学。

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