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Bioinformatics. 2017 Jun 1;33(11):1664-1671. doi: 10.1093/bioinformatics/btx053.
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Distance-Guided Forward and Backward Chain-Growth Monte Carlo Method for Conformational Sampling and Structural Prediction of Antibody CDR-H3 Loops.用于抗体互补决定区H3环构象采样和结构预测的距离引导的前向和反向链增长蒙特卡罗方法
J Chem Theory Comput. 2017 Jan 10;13(1):380-388. doi: 10.1021/acs.jctc.6b00845. Epub 2016 Dec 20.
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The accommodation index measures the perturbation associated with insertions and deletions in coiled-coils: Application to understand signaling in histidine kinases.适应性指数衡量与卷曲螺旋中插入和缺失相关的扰动:用于理解组氨酸激酶中的信号传导。
Protein Sci. 2017 Mar;26(3):414-435. doi: 10.1002/pro.3095. Epub 2017 Feb 23.
4
Outer Membrane Protein Folding and Topology from a Computational Transfer Free Energy Scale.基于计算转移自由能标度的外膜蛋白折叠与拓扑结构
J Am Chem Soc. 2016 Mar 2;138(8):2592-601. doi: 10.1021/jacs.5b10307. Epub 2016 Feb 19.
5
Inclusion of dyad-repeat pattern improves topology prediction of transmembrane β-barrel proteins.二联体重复模式的纳入提高了跨膜β桶蛋白的拓扑预测。
Bioinformatics. 2016 May 15;32(10):1571-3. doi: 10.1093/bioinformatics/btw025. Epub 2016 Jan 21.
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β-桶膜蛋白的高分辨率结构预测。

High-resolution structure prediction of -barrel membrane proteins.

机构信息

Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607.

Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607;

出版信息

Proc Natl Acad Sci U S A. 2018 Feb 13;115(7):1511-1516. doi: 10.1073/pnas.1716817115. Epub 2018 Jan 29.

DOI:10.1073/pnas.1716817115
PMID:29378944
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5816179/
Abstract

[Formula: see text]-Barrel membrane proteins ([Formula: see text]MPs) play important roles, but knowledge of their structures is limited. We have developed a method to predict their 3D structures. We predict strand registers and construct transmembrane (TM) domains of [Formula: see text]MPs accurately, including proteins for which no prediction has been attempted before. Our method also accurately predicts structures from protein families with a limited number of sequences and proteins with novel folds. An average main-chain rmsd of 3.48 Å is achieved between predicted and experimentally resolved structures of TM domains, which is a significant improvement ([Formula: see text]3 Å) over a recent study. For [Formula: see text]MPs with NMR structures, the deviation between predictions and experimentally solved structures is similar to the difference among the NMR structures, indicating excellent prediction accuracy. Moreover, we can now accurately model the extended [Formula: see text]-barrels and loops in non-TM domains, increasing the overall coverage of structure prediction by [Formula: see text]%. Our method is general and can be applied to genome-wide structural prediction of [Formula: see text]MPs.

摘要

β-桶膜蛋白(β-MPs)发挥着重要作用,但人们对其结构的了解有限。我们已经开发出一种预测其 3D 结构的方法。我们能够准确地预测 β-MPs 的链寄存器和跨膜(TM)结构,包括以前从未尝试过预测的蛋白质。我们的方法还能准确预测具有有限序列和新颖折叠的蛋白质家族的结构。预测的 TM 结构域与实验解析结构之间的主链均方根偏差(rmsd)平均为 3.48Å,与最近的一项研究相比([Formula: see text]3Å)有显著提高。对于具有 NMR 结构的 β-MPs,预测与实验解决结构之间的偏差与 NMR 结构之间的差异相似,表明预测精度很高。此外,我们现在可以准确地对非 TM 结构域中的扩展β-桶和环进行建模,从而使结构预测的整体覆盖率提高了[Formula: see text]%。我们的方法是通用的,可以应用于β-MPs 的全基因组结构预测。