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qFit-配体揭示了在 X 射线电子密度图中药物样分子的广泛构象异质性。

qFit-ligand Reveals Widespread Conformational Heterogeneity of Drug-Like Molecules in X-Ray Electron Density Maps.

机构信息

Schrödinger , New York , New York 10036 , United States.

Department of Bioengineering and Therapeutic Sciences , UCSF , San Francisco , California 94158 , United States.

出版信息

J Med Chem. 2018 Dec 27;61(24):11183-11198. doi: 10.1021/acs.jmedchem.8b01292. Epub 2018 Dec 6.

Abstract

Proteins and ligands sample a conformational ensemble that governs molecular recognition, activity, and dissociation. In structure-based drug design, access to this conformational ensemble is critical to understand the balance between entropy and enthalpy in lead optimization. However, ligand conformational heterogeneity is currently severely underreported in crystal structures in the Protein Data Bank, owing in part to a lack of automated and unbiased procedures to model an ensemble of protein-ligand states into X-ray data. Here, we designed a computational method, qFit-ligand, to automatically resolve conformationally averaged ligand heterogeneity in crystal structures, and applied it to a large set of protein receptor-ligand complexes. In an analysis of the cancer related BRD4 domain, we found that up to 29% of protein crystal structures bound with drug-like molecules present evidence of unmodeled, averaged, relatively isoenergetic conformations in ligand-receptor interactions. In many retrospective cases, these alternate conformations were adventitiously exploited to guide compound design, resulting in improved potency or selectivity. Combining qFit-ligand with high-throughput screening or multitemperature crystallography could therefore augment the structure-based drug design toolbox.

摘要

蛋白质和配体可采样构象组,该构象组可控制分子识别、活性和离解。在基于结构的药物设计中,要了解先导优化中熵和焓之间的平衡,访问该构象组至关重要。然而,由于缺乏将蛋白质-配体状态的整体模型自动转化为 X 射线数据的自动化和无偏程序,配体构象异质性在蛋白质数据库(PDB)中的晶体结构中目前严重报告不足。在这里,我们设计了一种计算方法 qFit-ligand,可自动解析晶体结构中配体构象的平均异质性,并将其应用于一组大型蛋白质受体-配体复合物。在对与癌症相关的 BRD4 结构域的分析中,我们发现,多达 29%的与药物样分子结合的蛋白质晶体结构在配体-受体相互作用中存在未建模、平均、相对等能量构象的证据。在许多回顾性案例中,这些替代构象被偶然利用来指导化合物设计,从而提高了效力或选择性。因此,将 qFit-ligand 与高通量筛选或多温度结晶学相结合,可以扩充基于结构的药物设计工具包。

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