Melville James L, Lovelock Kevin R J, Wilson Claire, Allbutt Bryan, Burke Edmund K, Lygo Barry, Hirst Jonathan D
School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, U.K.
J Chem Inf Model. 2005 Jul-Aug;45(4):971-81. doi: 10.1021/ci050051l.
Quantitative Structure-Selectivity Relationships (QSSR) are developed for a library of 40 phase-transfer asymmetric catalysts, based around quaternary ammonium salts, using Comparative Molecular Field Analysis (CoMFA) and closely related variants. Due to the flexibility of these catalysts, we use molecular dynamics (MD) with an implicit Generalized Born solvent model to explore their conformational space. Comparison with crystal data indicates that relevant conformations are obtained and that, furthermore, the correct biphenyl twist conformation is predicted, as illustrated by the superiority of the resulting model (leave-one-out q(2) = 0.78) compared to a random choice of low-energy conformations for each catalyst (average q(2) = 0.22). We extend this model by incorporating the MD trajectory directly into a 4D QSSR and by Boltzmann-weighting the contribution of selected minimized conformations, which we refer to as '3.5D' QSSR. The latter method improves on the predictive ability of the 3D QSSR (leave-one-out q(2) = 0.83), as confirmed by repeated training/test splits.
基于季铵盐构建了包含40种相转移不对称催化剂的库，利用比较分子场分析（CoMFA）及其密切相关的变体开发了定量结构-选择性关系（QSSR）。由于这些催化剂的灵活性，我们使用带有隐式广义玻恩溶剂模型的分子动力学（MD）来探索它们的构象空间。与晶体数据的比较表明，获得了相关构象，而且预测出了正确的联苯扭转构象，这由所得模型（留一法q(2)=0.78）相对于为每种催化剂随机选择低能构象（平均q(2)=0.22）的优越性所证明。我们通过将MD轨迹直接纳入四维QSSR并对选定的最小化构象的贡献进行玻尔兹曼加权来扩展此模型，我们将其称为“3.5D”QSSR。如重复训练/测试拆分所证实的那样，后一种方法提高了三维QSSR的预测能力（留一法q(2)=0.83）。
