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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >De novo prediction of protein folding pathways and structure using the principle of sequential stabilization
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De novo prediction of protein folding pathways and structure using the principle of sequential stabilization

机译：使用顺序稳定原理从头预测蛋白质折叠途径和结构

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摘要

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.
机译：受折叠机制和天然结构之间关系的影响，我们开发了一种仅使用一级序列作为输入来预测折叠途径和三级结构的统一方法。模拟从没有二级结构的实际展开状态开始，并使用缺少显式侧链的链表示，这使模拟比分子动力学模拟快许多个数量级。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2°结构元素在逐步学习和结构稳定的过程中添加到现有结构中折叠。因为没有使用先验知识，所以我们可以确定动力学上重要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，通过合并来自先前回合的信息，结构预测将大大改善。我们简单，无同源性的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正确性，以及SS作为搜索策略的有效性。

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  • 作者

    Aashish N. Adhikari; Karl F. Freed; Tobin R. Sosnick;

  • 作者单位

    Department of Chemistry, University of Chicago, Chicago, IL 60637,The James Franck Institute, University of Chicago, Chicago, IL 60637;

    Department of Chemistry, University of Chicago, Chicago, IL 60637,The James Franck Institute, University of Chicago, Chicago, IL 60637,Computation Institute, University of Chicago, Chicago, IL 60637;

    Computation Institute, University of Chicago, Chicago, IL 60637,Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL 60637,Institute for Biophysical Dynamics, University of Chicago, Chicago, IL 60637;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    terltfix; foldons; kinetic traps; monte carlo simulation;

    机译：terltfix;褶皱;动力陷阱蒙特卡洛模拟;

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