De novo prediction of protein folding pathways and structure using the principle of sequential stabilization
De novo prediction of protein folding pathways and structure using the principle of sequential stabilization
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DOI：
10.1073/pnas.1209000109
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发表时间：
2012-10-23
影响因子：
11.1
通讯作者：
Sosnick, Tobin R.
中科院分区：
文献类型：
--
作者：
Adhikari, Aashish N.;Freed, Karl F.;Sosnick, Tobin R.
受折叠机制和天然结构之间关系的启发，我们开发了一种统一的方法，仅使用一级序列作为输入来预测折叠途径和三级结构。模拟从没有二级结构的真实展开状态开始，并使用缺乏明确侧链的链表示，使模拟比分子动力学模拟快多个数量级。该算法的多轮性质模仿了真实的折叠过程，并测试了顺序稳定（SS）作为搜索策略的有效性，其中在渐进学习和前几轮折叠中发现的结构稳定的过程中，将 2 个结构元素添加到现有结构上。由于不使用先验知识，我们可以识别动力学上显着的非天然相互作用和中间体，有时仅由两个突变产生，而接触矩阵的演化通常与实验一致。此外，通过合并前几轮的信息，结构预测得到了显着改善。我们简单的、无同源性方法的成功证实了我们对折叠途径和结构的主要决定因素的描述的有效性，以及 SS 作为搜索策略的有效性。
Motivated by the relationship between the folding mechanism and the native structure, we develop a unified approach for predicting folding pathways and tertiary structure using only the primary sequence as input. Simulations begin from a realistic unfolded state devoid of secondary structure and use a chain representation lacking explicit side chains, rendering the simulations many orders of magnitude faster than molecular dynamics simulations. The multiple round nature of the algorithm mimics the authentic folding process and tests the effectiveness of sequential stabilization (SS) as a search strategy wherein 2 structural elements add onto existing structures in a process of progressive learning and stabilization of structure found in prior rounds of folding. Because no a priori knowledge is used, we can identify kinetically significant non-native interactions and intermediates, sometimes generated by only two mutations, while the evolution of contact matrices is often consistent with experiments. Moreover, structure prediction improves substantially by incorporating information from prior rounds. The success of our simple, homology-free approach affirms the validity of our description of the primary determinants of folding pathways and structure, and the effectiveness of SS as a search strategy.