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
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
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DOI：
10.1021/jp065380a
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发表时间：
2007-01-11
影响因子：
3.3
通讯作者：
Scheraga, Harold A.
中科院分区：
文献类型：
--
作者：
Liwo, Adam;Khalili, Mey;Scheraga, Harold A.
我们报告了联合残基（UNRES）力场的修改和参数化，用于基于能量的蛋白质结构预测和蛋白质折叠模拟。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）。迄今为止，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表面的全局最小值，这在很大程度上忽略了构象熵，因为仅由最低能量构象组成的诱饵被用来优化力场。最近，我们开发了 UNRES 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，力场很大程度上偏向α螺旋结构，因为参数化中忽略了构象熵。我们应用了早期工作中开发的分层优化方法来优化力场；在该方法中，训练蛋白质的构象空间被分为多个级别，每个级别对应于一定程度的天然相似性。级别根据与母语相似度的增加而排序；级别 0 对应于没有类似本机的元素的结构，最高级别对应于完全类似本机的结构。优化的目的是实现能级自由能的有序性，随着其原生相似性的增加而减少。该过程是迭代的，并且使用先前迭代的能量函数参数生成的训练蛋白质的诱饵用于优化当前迭代中的力场。我们应用最近在 UNRES 中实施的多重复制交换分子动力学 (MREMD) 方法来生成诱饵；通过这种修改，构象熵被考虑在内。此外，我们优化了与折叠或展开结构的优势相对应的温度下的能级之间的自由能间隙，以及假定的折叠转变温度下的结构，改变了转变温度下间隙的符号。这使我们能够获得以转变温度下热容单峰为特征的力场。此外，我们引入了 UNRES 力场的温度依赖性；这与它是自由能函数而不是势能函数这一事实是一致的。
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 alpha-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.