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Hierarchical energy-based approach to protein-structure prediction: Blind-test evaluation with CASP3 targets

机译:基于层次能量的蛋白质结构预测方法:使用CASP3目标进行盲测评估

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A hierarchical approach based exclusively on finding the global minimum of an appropriate potential energy function, without the aid of secondary structure prediction, multiple-sequence alignment, or threading, is proposed. The procedure starts from an extensive search of the conformational space of a protein, using our recently developed united-residue off-lattice UNRES force field and the conformational space annealing (CSA) method. The structures obtained in the search are clustered into families and ranked according to their UNRES energy Structures within a preassigned energy cutoff are gradually converted into an all-atom representation, followed by a limited conformational search at the all-atom level, using the electrostatically driven Monte Carlo (EDMC) method and the ECEPP/3 force field including hydration. The approach was tested (in the CASP3 experiment) in blind predictions on seven targets, five of which were globular proteins with sizes ranging from 89 to 140 amino acid residues. Comparison of the computed lowest-energy structures, with the experimental structures, made available after the predictions were submitted, shows that large fragments (similar to 60 residues, representing 45-80% of the proteins) of those five globular proteins were predicted with the root mean square deviations (RMSDs) ranging from 4 to 7 Angstrom for the C-alpha atoms, with correct secondary structure and topology. These results constitute an important step toward the prediction of protein structure based solely on global optimization of a potential energy function for a given amino acid sequence. (C) 2000 John Wiley & Sons, Inc. [References: 95]
机译:提出了一种仅基于找到合适的势能函数的全局最小值而无需二级结构预测,多序列比对或线程化的分层方法。该过程从使用我们最近开发的统一残基非网格UNRES力场和构象空间退火(CSA)方法广泛搜索蛋白质的构象空间开始。在搜索中获得的结构被聚类,并根据其UNRES能量进行排序。在预先分配的能量截止范围内,结构逐渐转换为全原子表示,然后使用静电驱动在全原子级别进行有限的构象搜索。蒙特卡洛(EDMC)方法和ECEPP / 3力场(包括水合作用)。在7个靶标上进行了盲目预测(在CASP3实验中),对该方法进行了测试,其中五个是球形蛋白质,大小从89到140个氨基酸残基不等。将计算得出的最低能量结构与实验结构进行比较,这些结构在提交预测后便可以使用,表明用该蛋白预测了这五个球状蛋白的大片段(约60个残基,占蛋白质的45-80%)。 C-alpha原子的均方根偏差(RMSD)为4至7埃,并具有正确的二级结构和拓扑。这些结果构成了仅基于给定氨基酸序列的势能函数的全局最优化来预测蛋白质结构的重要步骤。 (C)2000 John Wiley&Sons,Inc. [参考:95]

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