A novel approach to decoy set generation: Designing a physical energy function having local minima with native structure characteristics
A novel approach to decoy set generation: Designing a physical energy function having local minima with native structure characteristics
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DOI：
10.1016/s0022-2836(03)00323-1
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发表时间：
2003-05-23
影响因子：
5.6
通讯作者：
Levitt, M
中科院分区：
文献类型：
--
作者：
Keasar, C;Levitt, M
我们提出了一种新的方法来产生的候选结构（诱饵）从头预测，蛋白质结构。我们的方法是基于构象空间的随机采样和随后的局部能量最小化。这种方法的核心在于设计一种新型的能量函数。该能量函数具有局部极小值，具有天然结构特征和广泛的吸引盆地。目前的工作提出了我们的动机，推导这样的能量函数，并测试了推导的能量function.We的方法是新颖的，它利用了固有的粗糙的能量景观的蛋白质，这通常被认为是一个主要的障碍，蛋白质结构预测。当局部最小值具有广泛的吸引盆地时，蛋白质的构象空间可以通过将空间的大区域收敛为单点（即与这些漏斗对应的局部最小值）而大大缩小。我们通过一个迭代过程实现了这一概念。首先利用势函数生成诱饵集，然后对诱饵集进行研究，以指导势函数的进一步开发。我们的潜力的一个关键特征是使用合作的多体相互作用，模仿的作用熵和溶剂的贡献的自由energy.The的有效性和价值，我们的方法是通过将其应用到14个不同的，小的蛋白质证明。我们表明，对于这些蛋白质，构象空间的大小大大减少了新的能量函数。事实上，减少是如此之大，以允许有效的构象采样。因此，我们能够找到一个显着数量的近天然构象在随机搜索进行有限的计算资源。(C)2003爱思唯尔科技有限公司版权所有。
We suggest a new approach to the generation of candidate structures (decoys) for ab initio prediction, of protein structures. Our method is based on random sampling of conformation space and subsequent local energy minimization. At the core of this approach lies the design of a novel type of energy function. This energy function has local minima with native structure characteristics and wide basins of attraction. The current work presents our motivation for deriving such an energy function and also tests the derived energy function.Our approach is novel in that it takes advantage of the inherently rough energy landscape of proteins, which is generally considered a major obstacle for protein structure prediction. When local minima have wide basins of attraction, the protein's conformation space can be greatly reduced by the convergence of large regions of the space into single points, namely the local minima corresponding to these funnels. We have implemented this concept by an iterative process. The potential is first used to generate decoy sets and then we study these sets of decoys to guide further development of the potential. A key feature of our potential is the use of cooperative multi-body interactions that mimic the role of the entropic and solvent contributions to the free energy.The validity and value of our approach is demonstrated by applying it to 14 diverse, small proteins. We show that, for these proteins, the size of conformation space is considerably reduced by the new energy function. In fact, the reduction is so substantial as to allow efficient conformational sampling. As a result we are able to find a significant number of near-native conformations in random searches performed with limited computational resources. (C) 2003 Elsevier Science Ltd. All rights reserved.