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元动力学在药物设计中的应用:基于计算的 EphA2 受体靶向新型蛋白-蛋白相互作用抑制剂的合成。

Metadynamics for Perspective Drug Design: Computationally Driven Synthesis of New Protein-Protein Interaction Inhibitors Targeting the EphA2 Receptor.

机构信息

Dipartimento di Farmacia, Università degli Studi di Parma , Parco Area delle Scienze 27/A, 43124 Parma, Italy.

Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University , Newcastle upon Tyne NE1 8ST, United Kingdom.

出版信息

J Med Chem. 2017 Jan 26;60(2):787-796. doi: 10.1021/acs.jmedchem.6b01642. Epub 2017 Jan 5.

Abstract

Metadynamics (META-D) is emerging as a powerful method for the computation of the multidimensional free-energy surface (FES) describing the protein-ligand binding process. Herein, the FES of unbinding of the antagonist N-(3α-hydroxy-5β-cholan-24-oyl)-l-β-homotryptophan (UniPR129) from its EphA2 receptor was reconstructed by META-D simulations. The characterization of the free-energy minima identified on this FES proposes a binding mode fully consistent with previously reported and new structure-activity relationship data. To validate this binding mode, new N-(3α-hydroxy-5β-cholan-24-oyl)-l-β-homotryptophan derivatives were designed, synthesized, and tested for their ability to displace ephrin-A1 from the EphA2 receptor. Among them, two antagonists, namely compounds 21 and 22, displayed high affinity versus the EphA2 receptor and resulted endowed with better physicochemical and pharmacokinetic properties than the parent compound. These findings highlight the importance of free-energy calculations in drug design, confirming that META-D simulations can be used to successfully design novel bioactive compounds.

摘要

元动力学(META-D)正在成为一种强大的方法,用于计算描述蛋白配体结合过程的多维自由能表面(FES)。在此,通过 META-D 模拟重建了拮抗剂 N-(3α-羟基-5β-胆烷-24-酰基)-l-β-同型色氨酸(UniPR129)与其 EphA2 受体解联的 FES。对该 FES 上鉴定的自由能极小值的特征描述提出了一种与先前报道的和新的结构活性关系数据完全一致的结合模式。为了验证这种结合模式,设计、合成了新的 N-(3α-羟基-5β-胆烷-24-酰基)-l-β-同型色氨酸衍生物,并测试了它们从 EphA2 受体上置换 Ephrin-A1 的能力。其中,两种拮抗剂,即化合物 21 和 22,对 EphA2 受体表现出高亲和力,并且具有比母体化合物更好的物理化学和药代动力学性质。这些发现强调了自由能计算在药物设计中的重要性,证实了 META-D 模拟可用于成功设计新型生物活性化合物。

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