Ensemble docking to difficult targets in early‐stage drug discovery: Methodology and application to fibroblast growth factor 23,Chemical Biology & Drug Design

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Ensemble docking to difficult targets in early‐stage drug discovery: Methodology and application to fibroblast growth factor 23
Chemical Biology & Drug Design ( IF 3.2 ) Pub Date : 2017-11-03 , DOI: 10.1111/cbdd.13110
Hector A Velazquez _{1,

2} , Demian Riccardi _{1,

2} , Zhousheng Xiao ₃ , Leigh Darryl Quarles ₃ , Charless Ryan Yates ₄ , Jerome Baudry _{1,

2} , Jeremy C Smith _{1,

2}

Affiliation

Ensemble docking is now commonly used in early‐stage in silico drug discovery and can be used to attack difficult problems such as finding lead compounds which can disrupt protein–protein interactions. We give an example of this methodology here, as applied to fibroblast growth factor 23 (FGF23), a protein hormone that is responsible for regulating phosphate homeostasis. The first small‐molecule antagonists of FGF23 were recently discovered by combining ensemble docking with extensive experimental target validation data (Science Signaling, 9, 2016, ra113). Here, we provide a detailed account of how ensemble‐based high‐throughput virtual screening was used to identify the antagonist compounds discovered in reference (Science Signaling, 9, 2016, ra113). Moreover, we perform further calculations, redocking those antagonist compounds identified in reference (Science Signaling, 9, 2016, ra113) that performed well on drug‐likeness filters, to predict possible binding regions. These predicted binding modes are rescored with the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) approach to calculate the most likely binding site. Our findings suggest that the antagonist compounds antagonize FGF23 through the disruption of protein–protein interactions between FGF23 and fibroblast growth factor receptor (FGFR).

中文翻译：

早期药物发现中困难靶点的整体对接：成纤维细胞生长因子 23 的方法和应用

整体对接现在普遍用于计算机药物发现的早期阶段，可用于解决难题，例如寻找可以破坏蛋白质-蛋白质相互作用的先导化合物。我们在此给出了这种方法的示例，该方法应用于成纤维细胞生长因子 23 (FGF23)，这是一种负责调节磷酸盐稳态的蛋白质激素。最近，通过将整体对接与大量实验靶标验证数据相结合，发现了第一个 FGF23 小分子拮抗剂（Science Signaling，9，2016，ra113）。在这里，我们详细介绍了如何使用基于集合的高通量虚拟筛选来识别参考文献中发现的拮抗剂化合物（Science Signaling，9，2016，ra113）。此外，我们进行了进一步的计算，重新对接了参考文献（Science Signaling，9，2016，ra113）中鉴定的那些在药物相似过滤器上表现良好的拮抗剂化合物，以预测可能的结合区域。这些预测的结合模式使用分子力学泊松-玻尔兹曼表面积 (MM/PBSA) 方法重新评分，以计算最可能的结合位点。我们的研究结果表明，拮抗剂化合物通过破坏 FGF23 和成纤维细胞生长因子受体 (FGFR) 之间的蛋白质-蛋白质相互作用来拮抗 FGF23。

更新日期：2017-11-03

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