Kothiwale Sandeepkumar, Mendenhall Jeffrey L, Meiler Jens
Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN 37232 USA.
Department of Chemistry, Center for Structural Biology, Vanderbilt University, Nashville, TN 37232 USA ; Department of Pharmacology and Biomedical Informatics, Vanderbilt University, Nashville, TN 37212 USA.
J Cheminform. 2015 Sep 30;7:47. doi: 10.1186/s13321-015-0095-1. eCollection 2015.
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 Å 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.Graphical abstract:Conformation sampling is carried out using explicit fragment conformations derived from crystallographic structure databases. Molecules from the database are decomposed into fragments and most likely conformations/rotamers are used to sample correspondng sub-structure of a molecule of interest.
小分子与蛋白质靶点的相互作用取决于其形成互补三维结构的能力。因此,对于基于结构和配体的药物发现算法(如小分子对接或三维定量构效关系)而言,完整且快速地预测小分子能够采样的构象空间至关重要。在此,我们从剑桥结构数据库和蛋白质数据库中实验结构中频繁采样的小分子片段推导出了一个数据库。这些片段的可能构象以“旋转异构体”的形式存储,类似于用于快速采样蛋白质构象空间的氨基酸侧链旋转异构体文库。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。然后可以通过蒙特卡罗搜索策略重组片段旋转异构体来生成小分子的构象集合。在恢复小分子的实验测定的蛋白质结合构象的能力、构象集合的多样性和采样率方面,将BCL::Conf与其他构象生成方法(包括Confgen、Moe、Omega和RDKit)进行了基准测试。对于Vernalis基准数据集中99%的小分子,BCL::Conf恢复了至少一种与实验结构的均方根偏差为2 Å或更小的构象。“旋转异构体”方法将允许把BCL::Conf集成到各自的计算生物学程序中,如Rosetta。
使用从晶体学结构数据库中导出的显式片段构象进行构象采样。数据库中的分子被分解为片段,最可能的构象/旋转异构体用于对感兴趣分子的相应子结构进行采样。