首页> 外文期刊>The journal of physical chemistry, B. Condensed matter, materials, surfaces, interfaces & biophysical >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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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

机译:典范模拟的联合残基(UNRES)势能函数的修改和优化。一,有效能量函数的温度依赖性及单一训练蛋白的优化方法测试

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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.
机译:我们报告了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(beta),1GAB(alpha)和1E0G(alpha + beta)。迄今为止,已经设计并参数化了UNRES力场,以将蛋白质的天然结构定位为其有效势能面的整体最小值,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于优化力领域。最近,我们为UNRES开发了介观动力学程序,并将其成功应用于模拟蛋白质折叠途径。但是,在规范化的模拟中,力场被证明主要偏向于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,将训练蛋白的构象空间划分为多个级别,每个级别对应于一定程度的自然相似性。这些级别是根据增加的本地风格排序的;级别0对应于没有类似自然元素的结构,最高级别对应于完全像原生的结构。优化的目的是获得能级的自由能的阶次,并随着其本机态的增加而降低。该过程是迭代的,并且利用先前迭代的能量函数参数生成的训练蛋白的诱饵被用于优化当前迭代中的力场。我们应用了最近在UNRES实施的多路复本-交换分子动力学(MREMD)方法来产生诱饵。通过这种修改,可以考虑构象熵。此外,我们优化了与折叠或未折叠结构的优势相对应的温度水平之间的自由能隙,以及推定的折叠转变温度下的结构的自由能隙,从而改变了转变温度下的能隙符号。这使我们能够获得以转变温度下热容的一个峰值为特征的力场。此外,我们将温度依赖性引入了UNRES力场。这符合以下事实:它是自由能而不是势能函数。

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