Mimicking the folding pathway to improve homology-free protein structure prediction
Mimicking the folding pathway to improve homology-free protein structure prediction
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DOI：
10.1073/pnas.0811363106
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发表时间：
2009-03-10
影响因子：
11.1
通讯作者：
Sosnick, Tobin R.
中科院分区：
文献类型：
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作者：
DeBartolo, Joe;Colubri, Andres;Sosnick, Tobin R.
自从证明蛋白质的序列编码其结构以来，从序列预测结构仍然是影响许多科学学科的突出问题，包括许多基因组计划。通过在折叠的蒙特卡罗模拟过程中迭代地固定残基的二级结构分配，我们的粗粒度模型没有关于同源性或明确的侧链的信息，可以优于目前许多蛋白质的基于同源性的二级结构预测方法。计算快速算法，只使用单一的（φ，psi）二面角移动也产生三级结构的准确性与现有的所有原子的方法相比，许多小的蛋白质，特别是那些具有低同源性。因此，给定适当的搜索策略和评分函数，简化表示可以用于准确预测二级结构并提供3D结构，从而增加可通过无同源性方法接近的蛋白质的大小和依赖于高质量输入二级结构的模板方法的准确性。
Since the demonstration that the sequence of a protein encodes its structure, the prediction of structure from sequence remains an outstanding problem that impacts numerous scientific disciplines, including many genome projects. By iteratively fixing secondary structure assignments of residues during Monte Carlo simulations of folding, our coarse-grained model without information concerning homology or explicit side chains can outperform current homology-based secondary structure prediction methods for many proteins. The computationally rapid algorithm using only single (phi,psi) dihedral angle moves also generates tertiary structures of accuracy comparable with existing all-atom methods for many small proteins, particularly those with low homology. Hence, given appropriate search strategies and scoring functions, reduced representations can be used for accurately predicting secondary structure and providing 3D structures, thereby increasing the size of proteins approachable by homology-free methods and the accuracy of template methods that depend on a high-quality input secondary structure.