Liwo Adam, Khalili Mey, Czaplewski Cezary, Kalinowski Sebastian, Ołdziej Staniłsaw, Wachucik Katarzyna, Scheraga Harold A
Baker Laboratory of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853-1301, USA.
J Phys Chem B. 2007 Jan 11;111(1):260-85. doi: 10.1021/jp065380a.
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
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