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Stereoselectivity of Burkholderia cepacia lipase towards secondary alcohols: molecular modelling and 3D QSAR approach

机译:洋葱伯克霍尔德菌脂肪酶对仲醇的立体选择性:分子建模和3D QSAR方法

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Lipase from Burkholderia cepacia (BCL, previously Pseudomonas cepacia) has proven to be a useful biocatalyst for obtaining enantiomerically pure compounds, in particular primary and secondary alcohols and their esters. Previously we derived 3D quantitative structure-activity relationships (QSARs) for predicting the enantioselectivity of BCL towards 3-(aryloxy)-1,2-propanediol derivatives. Herein we used these models to predict the stereo selectivity for a new set of diverse secondary alcohols. Despite significant differences in the data sets and the molecular modelling procedure utilised, the stereoselectivity was predicted in agreement with the results of kinetic resolution. We have combined the lipase-substrate complexes that we analysed earlier with those presented herein and derived a new model. Since this model is derived for the chemically diverse set of secondary alcohols, it is more general than those obtained previously for the 12 BCL-3-(aryloxy)-1,2-propanediols complexes and should be able to predict the stereoselectivity of BCL towards a wide range of secondary alcohols. This is demonstrated for two alpha-methylene-beta-hydroxy esters. Additionally, we modelled a mutant BCL and, using the COMparative BINding Energy (COMBINE) analysis, predicted its stereoselectivity towards a few randomly selected secondary alcohols. The Monte Carlo based conformational search, used herein, turned out to be faster and more convenient for investigating the binding modes of secondary alcohols in the BCL active site than the systematic search used in our previous work. (C) 2004 Elsevier Ltd. All rights reserved.
机译:来自洋葱伯克霍尔德氏菌的脂肪酶(BCL,先前为洋葱假单胞菌)已被证明是用于获得对映体纯的化合物,特别是伯醇和仲醇及其酯的有用的生物催化剂。以前,我们获得了3D定量结构-活性关系(QSAR),用于预测BCL对3-(芳氧基)-1,2-丙二醇衍生物的对映选择性。本文中,我们使用这些模型预测了一组新的多元仲醇的立体选择性。尽管数据集和使用的分子建模程序存在显着差异,但预测的立体选择性与动力学拆分结果一致。我们将我们之前分析的脂肪酶-底物复合物与本文介绍的那些结合起来,并得出了一个新模型。由于此模型是针对化学上多样化的仲醇衍生的,因此它比以前针对12种BCL-3-(芳氧基)-1,2-丙二醇复合物获得的模型更通用,并且应该能够预测BCL对各种仲醇。对于两种α-亚甲基-β-羟基酯证明了这一点。此外,我们对突变型BCL进行了建模,并使用比较结合能(COMBINE)分析预测了其对几种随机选择的仲醇的立体选择性。与我们以前的工作中使用的系统搜索相比,本文中使用的基于蒙特卡洛的构象搜索方法在研究BCL活性位点中仲醇的结合模式方面更快,更方便。 (C)2004 Elsevier Ltd.保留所有权利。

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