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利用遗传算法和针对链区域的扩展标准,从序列和二级结构中识别具有不同拓扑结构的小蛋白质的三级折叠。

Identifying the tertiary fold of small proteins with different topologies from sequence and secondary structure using the genetic algorithm and extended criteria specific for strand regions.

作者信息

Dandekar T, Argos P

机构信息

European Molecular Biology Laboratory, Heidelberg, Germany.

出版信息

J Mol Biol. 1996 Mar 1;256(3):645-60. doi: 10.1006/jmbi.1996.0115.

DOI:10.1006/jmbi.1996.0115
PMID:8604145
Abstract

Grid-free protein folding simulations based on sequence and secondary structure knowledge (using mostly experimentally determined secondary structure information but also analysing results from secondary structure predictions) were investigated using the genetic algorithm, a backbone representation, and standard dihedral angular conformations. Optimal structures are selected according to basic protein building principles. Having previously applied this approach to proteins with helical topology, we have now developed additional criteria and weights for beta-strand-containing proteins, validated them on four small beta-strand-rich proteins with different topologies, and tested the general performance of the method on many further examples from known protein structures with mixed secondary structural type and less than 100 amino acid residues. Topology predictions close to the observed experimental structures were obtained in four test cases together with fitness values that correlated with the similarity of the predicted topology to the observed structures. Root-mean-square deviation values of C alpha atoms in the superposed predicted and observed structures, the latter of which had different topologies, were between 4.5 and 5.5 A(2.9 to 5.1 A without loops). Including 15 further protein examples with unique folds, root-mean-square deviation values ranged between 1.8 and 6.9 A with loop regions and averaged 5.3 A and 4.3 A, including and excluding loop regions, respectively.

摘要

基于序列和二级结构知识(主要使用实验测定的二级结构信息,但也分析二级结构预测结果)的无网格蛋白质折叠模拟,采用遗传算法、主链表示法和标准二面角构象进行了研究。根据基本的蛋白质构建原则选择最优结构。此前我们已将此方法应用于具有螺旋拓扑结构的蛋白质,现在我们为含β链的蛋白质开发了额外的标准和权重,在四个具有不同拓扑结构的富含β链的小蛋白质上对其进行了验证,并在许多来自已知蛋白质结构的、具有混合二级结构类型且氨基酸残基少于100个的其他实例上测试了该方法的总体性能。在四个测试案例中获得了与观察到的实验结构接近的拓扑预测结果,以及与预测拓扑结构和观察到的结构的相似性相关的适应度值。叠加后的预测结构和观察到的结构(后者具有不同的拓扑结构)中Cα原子的均方根偏差值在4.5至5.5埃之间(不包括环时为2.9至5.1埃)。包括另外15个具有独特折叠的蛋白质实例,包括环区域时均方根偏差值在1.8至6.9埃之间,分别包括和排除环区域时的平均值分别为5.3埃和4.3埃。

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