Automated design of ligands to polypharmacological profiles.
Automated design of ligands to polypharmacological profiles.
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药物的临床疗效和安全性取决于其在蛋白质组中多种蛋白质的活性谱。然而，设计具有特定多靶点分布的药物既复杂又困难。因此，根据多种蛋白质的谱来先验地合理设计药物的方法将在药物发现中具有巨大的价值。我们描述了一种新的方法，自动化设计的配体对多个药物靶点的配置文件。该方法通过将批准的乙酰胆碱酯酶抑制剂药物进化为具有特定的多药理学或对G蛋白偶联受体的精致选择性特征的脑可穿透配体来证明。总体而言，800配体靶预测的前瞻性设计的配体进行了实验测试，其中75%被证实是正确的。我们还证明了在体内的目标接合。该方法可以是一个有用的药物线索来源，其中需要多靶点配置文件来实现对其他药物靶点的选择性或所需的多药理学。
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.
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影响因子：
7.3
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