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首页> 外文期刊>Proteins: Structure, Function, and Genetics >Exploratory studies of ab initio protein structure prediction: multiple copy simulated annealing, AMBER energy functions, and a generalized born/solvent accessibility solvation model.
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Exploratory studies of ab initio protein structure prediction: multiple copy simulated annealing, AMBER energy functions, and a generalized born/solvent accessibility solvation model.

机译:从头算蛋白质结构预测的探索性研究:多拷贝模拟退火,AMBER能量函数和广义的生/溶剂可及性溶剂化模型。

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A theoretical and computational approach to ab initio structure prediction for polypeptides in water is described and applied to selected amino acid sequences for testing and preliminary validation. The method builds systematically on the extensive efforts applied to parameterization of molecular dynamics (MD) force fields, employs an empirically well-validated continuum dielectric model for solvation, and an eminently parallelizable approach to conformational search. The effective free energy of polypeptide chains is estimated from AMBER united atom potential functions, with internal degrees of freedom for both backbone and amino acid side chains explicitly treated. The hydration free energy of each structure is determined using the Generalized Born/Solvent Accessibility (GBSA) method, modified and reparameterized to include atom types consistent with the AMBER force field. The conformational search procedure employs a multiple copy, Monte Carlo simulated annealing (MCSA) protocol in full torsion angle space, applied iteratively on sets of structures of progressively lower free energy until a prediction of a structure with lowest effective free energy is obtained. Calibration tests for the effective energy function and search algorithm are performed on the alanine dipeptide, selected protein crystal structures, and united atom decoys on barnase, crambin, and six examples from the Rosetta set. Specific demonstration cases of the method are provided for the 8-mer sequence of Ala residues, a 12-residue peptide with longer side chains QLLKKLLQQLKQ, a de novo designed 16 residue peptide of sequence (AAQAA)3Y, a 15-residue sequence with a beta sheet motif, GEWTWDATKTFTVTE, and a 36 residue small protein, Villin headpiece. The Ala 8-mer readily formed an alpha-helix. An alpha-helix structure was predicted for the 16-mer, consistent with observed results from IR and CD spectroscopy and with the pattern in psi/straight phi angles of known protein structures. The predicted structure for the 12-mer, composed of a mix of helix and less regular elements of secondary structure, lies 2.65 A RMS from the observed crystal structure. Structure prediction for the 8-mer beta-motif resulted in form 4.50 A RMS from the crystal geometry. For Villin, the predicted native form is very close to the crystal structure, RMS values of 3.5 A (including sidechains), and 1.01 A (main chain only). The methodology permits a detailed analysis of the molecular forces which dominate various segments of the predicted folding trajectory. Analysis of the results in terms of internal torsional, electrostatic and van der Waals and the electrostatic and non-electrostatic contributions to hydration, including the hydrophobic effect, is presented. Copyright 2001 Wiley-Liss, Inc.
机译:描述了一种理论和计算方法来预测水中多肽的从头算结构,并将其应用于选定的氨基酸序列以进行测试和初步验证。该方法系统地建立在广泛应用于分子动力学(MD)力场参数化的工作上,采用了经过实验验证的连续介质模型进行溶剂化,并采用了可并行进行构象搜索的方法。多肽链的有效自由能由AMBER单元原子势函数估计,主链和氨基酸侧链的内部自由度均得到明确处理。每个结构的水合自由能均使用通用玻恩/溶剂可及性(GBSA)方法确定,并进行了修改和重新参数化以包含与AMBER力场一致的原子类型。构象搜索过程在完整的扭转角空间中采用多副本蒙特卡罗模拟退火(MCSA)协议,将其迭代地应用于逐渐降低的自由能的结构集上,直到获得具有最低有效自由能的结构的预测为止。在丙氨酸二肽,选定的蛋白质晶体结构以及在芽孢杆菌酶,补体脂和来自Rosetta系列的六个实例上的联合原子诱饵上,进行了有效能量函数和搜索算法的校准测试。针对Ala残基的8-mer序列,具有较长侧链的12个残基的肽QLLKKLLQQLKQ,从头设计的16个残基的序列(AAQAA)3Y,具有15个残基的序列提供了该方法的具体例证β片基序GEWTWDATKTFTVTE和36个残基的小蛋白Villin头盔。丙氨酸8聚体容易形成α-螺旋。预测了16聚体的α-螺旋结构,这与从IR和CD光谱学观察到的结果以及已知蛋白质结构的psi /直phi角度的模式一致。 12-mer的预测结构由螺旋和二级结构的较不规则元素组成,位于所观察到的晶体结构中,为2.65 A RMS。对8-merβ-基序的结构预测从晶体几何结构中得出4.50 A RMS的形式。对于Villin,预测的天然形式非常接近晶体结构,RMS值为3.5 A(包括侧链)和1.01 A(仅主链)。该方法允许对支配预测折叠轨迹的各个片段的分子力进行详细分析。提出了对结果的内部扭转,静电和范德华分析以及对水合作用的静电和非静电作用(包括疏水作用)的分析。版权所有2001 Wiley-Liss,Inc.

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