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首页> 外文期刊>Journal of Cheminformatics >BCL::Conf: small molecule conformational sampling using a knowledge based rotamer library
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BCL::Conf: small molecule conformational sampling using a knowledge based rotamer library

机译:BCL :: Conf:使用基于知识的旋转异构体库进行小分子构象采样

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The interaction of a small molecule with a protein target depends on its ability to adopt a three-dimensional structure that is complementary. Therefore, complete and rapid prediction of the conformational space a small molecule can sample is critical for both structure- and ligand-based drug discovery algorithms such as small molecule docking or three-dimensional quantitative structure–activity relationships. Here we have derived a database of small molecule fragments frequently sampled in experimental structures within the Cambridge Structure Database and the Protein Data Bank. Likely conformations of these fragments are stored as ‘rotamers’ in analogy to amino acid side chain rotamer libraries used for rapid sampling of protein conformational space. Explicit fragments take into account correlations between multiple torsion bonds and effect of substituents on torsional profiles. A conformational ensemble for small molecules can then be generated by recombining fragment rotamers with a Monte Carlo search strategy. BCL::CONF was benchmarked against other conformer generator methods including CONFGEN, MOE, OMEGA and RDKIT in its ability to recover experimentally determined protein bound conformations of small molecules, diversity of conformational ensembles, and sampling rate. BCL::CONF recovers at least one conformation with a root mean square deviation of 2 ? or better to the experimental structure for 99 % of the small molecules in the VERNALIS benchmark dataset. The ‘rotamer’ approach will allow integration of BCL::CONF into respective computational biology programs such as ROSETTA.
机译:小分子与蛋白质靶标的相互作用取决于其采用互补的三维结构的能力。因此,对小分子可以采样的构象空间的完整和快速预测对于基于结构和配体的药物发现算法(例如小分子对接或三维定量结构-活性关系)都是至关重要的。在这里,我们得到了一个小分子片段数据库,该数据库经常在剑桥结构数据库和蛋白质数据库中的实验结构中采样。这些片段的构象可能以“旋转子”形式存储,类似于用于蛋白质构象空间快速采样的氨基酸侧链旋转异构体库。显式片段考虑了多个扭转键之间的相关性以及取代基对扭转轮廓的影响。然后可以通过将片段旋转异构体与Monte Carlo搜索策略重组来生成小分子的构象集合。 BCL :: CONF与其他构象生成器方法(包括CONFGEN,MOE,OMEGA和RDKIT)相比,具有恢复实验确定的小分子蛋白结合构象,构象多样性和采样率的能力。 BCL :: CONF恢复均方根偏差为2?的至少一种构象。或优于VERNALIS基准数据集中99%的小分子的实验结构。 “旋转器”方法将允许将BCL :: CONF集成到相应的计算生物学程序中,例如ROSETTA。

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