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新型基于物理的组合建模方法,利用 3D 分子构象和堆积来获取水相热力学溶解度:口服可利用的溴结构域和末端结构域抑制剂先导优化系列的案例研究。

Novel Physics-Based Ensemble Modeling Approach That Utilizes 3D Molecular Conformation and Packing to Access Aqueous Thermodynamic Solubility: A Case Study of Orally Available Bromodomain and Extraterminal Domain Inhibitor Lead Optimization Series.

机构信息

Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States.

XtalPi, Inc., 245 Main Street, Cambridge, Massachusetts 02142, United States.

出版信息

J Chem Inf Model. 2021 Mar 22;61(3):1412-1426. doi: 10.1021/acs.jcim.0c01410. Epub 2021 Mar 4.

DOI:10.1021/acs.jcim.0c01410
PMID:33661005
Abstract

Drug design with patient centricity for ease of administration and pill burden requires robust understanding of the impact of chemical modifications on relevant physicochemical properties early in lead optimization. To this end, we have developed a physics-based ensemble approach to predict aqueous thermodynamic crystalline solubility, with a 2D chemical structure as the input. Predictions for the bromodomain and extraterminal domain (BET) inhibitor series show very close match (0.5 log unit) with measured thermodynamic solubility for cases with low crystal anisotropy and good match (1 log unit) for high anisotropy structures. The importance of thermodynamic solubility is clearly demonstrated by up to a 4 log unit drop in solubility compared to kinetic (amorphous) solubility in some cases and implications thereof, for instance on human dose. We have also demonstrated that incorporating predicted crystal structures in thermodynamic solubility prediction is necessary to differentiate (up to 4 log unit) between solubility of molecules within the series. Finally, our physics-based ensemble approach provides valuable structural insights into the origins of 3-D conformational landscapes, crystal polymorphism, and anisotropy that can be leveraged for both drug design and development.

摘要

以患者为中心进行药物设计,以方便给药和减少用药负担,这需要在先导化合物优化早期就对化学修饰对相关物理化学性质的影响有深入的了解。为此,我们开发了一种基于物理的集合方法,可预测水相热力学结晶溶解度,输入为二维化学结构。BET 抑制剂系列的预测结果与低各向异性晶体的实测热力学溶解度非常吻合(相差 0.5 个对数单位),而对于各向异性结构好的情况,吻合度(1 个对数单位)更好。在某些情况下,与动力学(无定形)溶解度相比,热力学溶解度的重要性显而易见,溶解度相差可达 4 个对数单位,这对人体剂量有重要影响。我们还证明了在热力学溶解度预测中纳入预测的晶体结构对于区分该系列分子的溶解度(相差可达 4 个对数单位)是必要的。最后,我们基于物理的集合方法提供了对 3D 构象景观、晶体多态性和各向异性起源的有价值的结构见解,可用于药物设计和开发。

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