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用于预测蛋白质表面环结构的溶剂化参数:转移性和熵效应。

Solvation parameters for predicting the structure of surface loops in proteins: transferability and entropic effects.

作者信息

Das Bedamati, Meirovitch Hagai

机构信息

Center for Computational Biology and Bioinformatics and Department of Molecular Genetics and Biochemistry, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA.

出版信息

Proteins. 2003 May 15;51(3):470-83. doi: 10.1002/prot.10356.

Abstract

A new procedure for optimizing parameters of implicit solvation models introduced by us has been applied successfully first to cyclic peptides and more recently to three surface loops of ribonuclease A (Das and Meirovitch, Proteins 2001;43:303-314) using the simplified model E(tot) = E(FF)(epsilon = nr) + Sigma(i) sigma(i)A(i), where sigma(i) are atomic solvation parameters (ASPs) to be optimized, A(i) is the solvent accessible surface area of atom i, E(FF)(epsilon = nr) is the AMBER force-field energy of the loop-loop and loop-template interactions with a distance-dependent dielectric constant, epsilon = nr, where n is a parameter. The loop is free to move while the protein template is held fixed in its X-ray structure; an extensive conformational search for energy minimized loop structures is carried out with our local torsional deformation method. The optimal ASPs and n are those for which the structure with the lowest minimized energy [E(tot)(n,sigma(i))] becomes the experimental X-ray structure, or less strictly, the energy gap between these structures is within 2-3 kcal/mol. To check if a set of ASPs can be defined, which is transferable to a large number of loops, we optimize individual sets of ASPs (based on n = 2) for 12 surface loops from which an "averaged" best-fit set is defined. This set is then applied to the 12 loops and an independent "test" group of 8 loops leading in most cases to very small RMSD values; thus, this set can be useful for structure prediction of loops in homology modeling. For three loops we also calculate the free energy gaps to find that they are only slightly smaller than their energy counterparts, indicating that only larger n will enable reducing too large gaps. Because of its simplicity, this model allowed carrying out an extensive application of our methodology, providing thereby a large number of benchmark results for comparison with future calculations based on n > 2 as well as on more sophisticated solvation models with as yet unknown performance for loops.

摘要

我们引入的一种优化隐式溶剂化模型参数的新方法,首先已成功应用于环肽,最近又应用于核糖核酸酶A的三个表面环(Das和Meirovitch,《蛋白质》2001年;43:303 - 314),使用简化模型E(tot) = E(FF)(epsilon = nr) + Sigma(i) sigma(i)A(i),其中sigma(i)是待优化的原子溶剂化参数(ASP),A(i)是原子i的溶剂可及表面积,E(FF)(epsilon = nr)是环 - 环和环 - 模板相互作用的AMBER力场能量,其具有距离依赖性介电常数epsilon = nr,其中n是一个参数。在蛋白质模板保持其X射线结构固定的情况下,环可以自由移动;使用我们的局部扭转变形方法对能量最小化的环结构进行广泛的构象搜索。最优的ASP和n是使得能量最小化程度最低的结构[E(tot)(n,sigma(i))]成为实验X射线结构的那些值,或者不太严格地说,这些结构之间的能量差在2 - 3千卡/摩尔以内。为了检验是否可以定义一组可转移到大量环的ASP,我们针对12个表面环优化了各自的ASP集(基于n = 2),由此定义了一个“平均”的最佳拟合集。然后将该集应用于这12个环以及一个由8个环组成的独立“测试”组,在大多数情况下得到非常小的均方根偏差(RMSD)值;因此,该集可用于同源建模中环的结构预测。对于三个环,我们还计算了自由能差,发现它们仅比相应的能量差略小,这表明只有更大的n才能使过大的差值减小。由于其简单性,该模型允许我们广泛应用我们的方法,从而提供大量的基准结果,以便与未来基于n > 2以及性能未知的更复杂溶剂化模型的计算进行比较。

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