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本文引用的文献

1
Protein Structure Prediction:  The Next Generation.蛋白质结构预测:下一代技术
J Chem Theory Comput. 2006 May;2(3):705-16. doi: 10.1021/ct0600058.
2
Replica Exchange and Multicanonical Algorithms with the coarse-grained UNRES force field.采用粗粒度UNRES力场的副本交换和多正则算法。
J Chem Theory Comput. 2006;2(3):513-528. doi: 10.1021/ct050253o.
3
Molecular dynamics with the united-residue model of polypeptide chains. II. Langevin and Berendsen-bath dynamics and tests on model alpha-helical systems.多肽链联合残基模型的分子动力学。II. 朗之万动力学和贝伦德森热浴动力学以及对模型α-螺旋系统的测试。
J Phys Chem B. 2005 Jul 21;109(28):13798-810. doi: 10.1021/jp058007w.
4
Molecular dynamics with the united-residue model of polypeptide chains. I. Lagrange equations of motion and tests of numerical stability in the microcanonical mode.多肽链联合残基模型的分子动力学。I. 微正则模式下的拉格朗日运动方程及数值稳定性测试
J Phys Chem B. 2005 Jul 21;109(28):13785-97. doi: 10.1021/jp058008o.
5
An evolutionary strategy for all-atom folding of the 60-amino-acid bacterial ribosomal protein l20.60个氨基酸的细菌核糖体蛋白L20全原子折叠的进化策略。
Biophys J. 2006 Jun 15;90(12):4273-80. doi: 10.1529/biophysj.105.070409. Epub 2006 Mar 24.
6
Prediction and design of macromolecular structures and interactions.大分子结构与相互作用的预测和设计。
Philos Trans R Soc Lond B Biol Sci. 2006 Mar 29;361(1467):459-63. doi: 10.1098/rstb.2005.1803.
7
Exploring protein energy landscapes with hierarchical clustering.利用层次聚类探索蛋白质能量景观。
Int J Quantum Chem. 2005;105(6):826-830. doi: 10.1002/qua.20741.
8
Protein structure prediction: inroads to biology.蛋白质结构预测:通往生物学的途径。
Mol Cell. 2005 Dec 22;20(6):811-9. doi: 10.1016/j.molcel.2005.12.005.
9
Free energy surfaces of miniproteins with a betabetaalpha motif: replica exchange molecular dynamics simulation with an implicit solvation model.具有ββα模体的小蛋白的自由能表面:使用隐式溶剂化模型的副本交换分子动力学模拟
Proteins. 2006 Mar 15;62(3):663-71. doi: 10.1002/prot.20771.
10
Kinetic studies of folding of the B-domain of staphylococcal protein A with molecular dynamics and a united-residue (UNRES) model of polypeptide chains.利用分子动力学和多肽链统一残基(UNRES)模型对葡萄球菌蛋白A B结构域折叠的动力学研究。
J Mol Biol. 2006 Jan 20;355(3):536-47. doi: 10.1016/j.jmb.2005.10.056. Epub 2005 Nov 10.

用于正则模拟的联合残基(UNRES)势能函数的修改与优化。I. 有效能量函数的温度依赖性及对单一训练蛋白优化方法的测试

Modification and optimization of the united-residue (UNRES) potential energy function for canonical simulations. I. Temperature dependence of the effective energy function and tests of the optimization method with single training proteins.

作者信息

Liwo Adam, Khalili Mey, Czaplewski Cezary, Kalinowski Sebastian, Ołdziej Staniłsaw, Wachucik Katarzyna, Scheraga Harold A

机构信息

Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, USA.

出版信息

J Phys Chem B. 2007 Jan 11;111(1):260-85. doi: 10.1021/jp065380a.

DOI:10.1021/jp065380a
PMID:17201450
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3236617/
Abstract

We report the modification and parametrization of the united-residue (UNRES) force field for energy-based protein structure prediction and protein folding simulations. We tested the approach on three training proteins separately: 1E0L (beta), 1GAB (alpha), and 1E0G (alpha + beta). Heretofore, the UNRES force field had been designed and parametrized to locate native-like structures of proteins as global minima of their effective potential energy surfaces, which largely neglected the conformational entropy because decoys composed of only lowest-energy conformations were used to optimize the force field. Recently, we developed a mesoscopic dynamics procedure for UNRES and applied it with success to simulate protein folding pathways. However, the force field turned out to be largely biased toward -helical structures in canonical simulations because the conformational entropy had been neglected in the parametrization. We applied the hierarchical optimization method, developed in our earlier work, to optimize the force field; in this method, the conformational space of a training protein is divided into levels, each corresponding to a certain degree of native-likeness. The levels are ordered according to increasing native-likeness; level 0 corresponds to structures with no native-like elements, and the highest level corresponds to the fully native-like structures. The aim of optimization is to achieve the order of the free energies of levels, decreasing as their native-likeness increases. The procedure is iterative, and decoys of the training protein(s) generated with the energy function parameters of the preceding iteration are used to optimize the force field in a current iteration. We applied the multiplexing replica-exchange molecular dynamics (MREMD) method, recently implemented in UNRES, to generate decoys; with this modification, conformational entropy is taken into account. Moreover, we optimized the free-energy gaps between levels at temperatures corresponding to a predominance of folded or unfolded structures, as well as to structures at the putative folding-transition temperature, changing the sign of the gaps at the transition temperature. This enabled us to obtain force fields characterized by a single peak in the heat capacity at the transition temperature. Furthermore, we introduced temperature dependence to the UNRES force field; this is consistent with the fact that it is a free-energy and not a potential energy function. beta

摘要

我们报告了用于基于能量的蛋白质结构预测和蛋白质折叠模拟的联合残基(UNRES)力场的修改和参数化。我们分别在三种训练蛋白上测试了该方法:1E0L(β)、1GAB(α)和1E0G(α + β)。在此之前,UNRES力场已被设计和参数化,以将蛋白质的类天然结构定位为其有效势能面的全局最小值,这在很大程度上忽略了构象熵,因为仅使用由最低能量构象组成的诱饵来优化力场。最近,我们为UNRES开发了一种介观动力学程序,并成功地将其应用于模拟蛋白质折叠途径。然而,在规范模拟中,力场在很大程度上偏向于α - 螺旋结构,因为在参数化过程中忽略了构象熵。我们应用了在早期工作中开发的分层优化方法来优化力场;在这种方法中,训练蛋白的构象空间被划分为多个层次,每个层次对应一定程度的类天然性。这些层次根据类天然性的增加进行排序;第0层对应于没有类天然元素的结构,最高层对应于完全类天然的结构。优化的目的是实现层次自由能的顺序,随着它们的类天然性增加而降低。该过程是迭代的,并且使用前一次迭代的能量函数参数生成的训练蛋白诱饵来在当前迭代中优化力场。我们应用了最近在UNRES中实现的多路复用副本交换分子动力学(MREMD)方法来生成诱饵;通过这种修改,构象熵被考虑在内。此外,我们在对应于折叠或未折叠结构占主导的温度以及假定的折叠转变温度下的结构的温度下优化了层次之间的自由能间隙,在转变温度处改变间隙的符号。这使我们能够获得在转变温度下热容量具有单个峰值的力场。此外,我们将温度依赖性引入到UNRES力场中;这与它是一个自由能而不是势能函数这一事实是一致的。β