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一种酶中反应势垒系统筛选的计算方法:寻找对合成底物具有更高活性的解淀粉芽孢杆菌木聚糖酶突变体。

A computational method for the systematic screening of reaction barriers in enzymes: searching for Bacillus circulans xylanase mutants with greater activity towards a synthetic substrate.

机构信息

Department of Chemistry, University of Copenhagen , Copenhagen , Denmark.

出版信息

PeerJ. 2013 Jul 23;1:e111. doi: 10.7717/peerj.111. Print 2013.

DOI:10.7717/peerj.111
PMID:23904990
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3728886/
Abstract

We present a semi-empirical (PM6-based) computational method for systematically estimating the effect of all possible single mutants, within a certain radius of the active site, on the barrier height of an enzymatic reaction. The intent of this method is not a quantitative prediction of the barrier heights, but rather to identify promising mutants for further computational or experimental study. The method is applied to identify promising single and double mutants of Bacillus circulans xylanase (BCX) with increased hydrolytic activity for the artificial substrate ortho-nitrophenyl β-xylobioside (ONPX2). The estimated reaction barrier for wild-type (WT) BCX is 18.5 kcal/mol, which is in good agreement with the experimental activation free energy value of 17.0 kcal/mol extracted from the observed k cat using transition state theory (Joshi et al., 2001). The PM6 reaction profiles for eight single point mutations are recomputed using FMO-MP2/PCM/6-31G(d) single points. PM6 predicts an increase in barrier height for all eight mutants while FMO predicts an increase for six of the eight mutants. Both methods predict that the largest change in barrier occurs for N35F, where PM6 and FMO predict a 9.0 and 15.8 kcal/mol increase, respectively. We thus conclude that PM6 is sufficiently accurate to identify promising mutants for further study. We prepared a set of all theoretically possible (342) single mutants in which every amino acid of the active site (except for the catalytically active residues E78 and E172) was mutated to every other amino acid. Based on results from the single mutants we construct a set of 111 double mutants consisting of all possible pairs of single mutants with the lowest barrier for a particular position and compute their reaction profile. None of the mutants have, to our knowledge, been prepared experimentally and therefore present experimentally testable predictions.

摘要

我们提出了一种半经验(基于 PM6)的计算方法,用于系统地估计活性位点一定半径内所有可能的单点突变对酶反应势垒高度的影响。该方法的目的不是对势垒高度进行定量预测,而是确定具有更高水解活性的潜在突变体,以便进一步进行计算或实验研究。该方法应用于鉴定具有更高水解活性的人工底物邻硝基苯-β-木二糖苷(ONPX2)的潜在突变体,包括芽孢杆菌环糊精酶(BCX)的单点和双点突变。野生型(WT)BCX 的估计反应势垒为 18.5 kcal/mol,与从观察到的 k cat 使用过渡态理论(Joshi 等人,2001)提取的实验活化自由能值 17.0 kcal/mol 非常吻合。使用 FMO-MP2/PCM/6-31G(d)单点重新计算了八个单点突变的 PM6 反应轮廓。PM6 预测所有八个突变体的势垒高度都会增加,而 FMO 预测其中六个突变体的势垒高度会增加。两种方法都预测 N35F 的势垒变化最大,其中 PM6 和 FMO 分别预测增加 9.0 和 15.8 kcal/mol。因此,我们得出结论,PM6 足够准确,可以识别具有进一步研究潜力的潜在突变体。我们制备了一套理论上可能的(342)单点突变体,其中活性位点的每个氨基酸(除了催化活性残基 E78 和 E172 外)都突变为其他氨基酸。基于单点突变的结果,我们构建了一组由具有特定位置最低势垒的所有可能的双点突变体组成的 111 个双点突变体,并计算了它们的反应轮廓。据我们所知,这些突变体都没有进行过实验制备,因此提出了可进行实验验证的预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/8aa65f45f297/peerj-01-111-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/465256cab66d/peerj-01-111-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/dbf7c6679537/peerj-01-111-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/a1d5520a8886/peerj-01-111-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/1fd94ddb62f5/peerj-01-111-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/e5fd7b444a31/peerj-01-111-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/980340a927be/peerj-01-111-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/b4b0e9e01b24/peerj-01-111-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/36bbd79cb82b/peerj-01-111-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/aa10ddae90ad/peerj-01-111-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/8aa65f45f297/peerj-01-111-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/465256cab66d/peerj-01-111-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/dbf7c6679537/peerj-01-111-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/a1d5520a8886/peerj-01-111-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/1fd94ddb62f5/peerj-01-111-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/e5fd7b444a31/peerj-01-111-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/980340a927be/peerj-01-111-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/b4b0e9e01b24/peerj-01-111-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/36bbd79cb82b/peerj-01-111-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/aa10ddae90ad/peerj-01-111-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef1c/3728886/8aa65f45f297/peerj-01-111-g010.jpg

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