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α螺旋中特定侧链相互作用能的计算估计

Computational estimation of specific side chain interaction energies in alpha helices.

作者信息

Fisinger S, Serrano L, Lacroix E

机构信息

European Molecular Biology Laboratory, D-69117 Heidelberg, Germany.

出版信息

Protein Sci. 2001 Apr;10(4):809-18. doi: 10.1110/ps.34901.

Abstract

We have used a structure energy-based computer program developed for protein design, Perla, to provide theoretical estimates of all specific side chain-side chain interaction energies occurring in alpha helices. The computed side chain-side chain interaction energies were used as substitutes for the corresponding values used by the helix/coil transition algorithm, AGADIR. Predictions of peptide helical contents were nearly as successful as those obtained with the originally calibrated set of parameters; a correlation to experimentally observed alpha-helical populations of 0.91 proved that our theoretical estimates are reasonably correct for amino acid pairs that are frequent in our database of peptides. Furthermore, we have determined experimentally the previously uncharacterized interaction energies for Lys-Ile, Thr-Ile, and Phe-Ile amino acid pairs at i,i + 4 positions. The experimental values compare favorably with the computed theoretical estimates. Importantly, the computed values for Thr-Ile and Phe-Ile interactions are better than the energies based on chemical similarity, whereas for Lys-Ile they are similar. Thus, computational techniques can be used to provide precise energies for amino acid pairwise interactions, a fact that supports the development of structure energy-based computational tools for structure predictions and sequence design.

摘要

我们使用了一个为蛋白质设计开发的基于结构能量的计算机程序Perla,来提供对α螺旋中所有特定侧链-侧链相互作用能的理论估计。计算得到的侧链-侧链相互作用能被用作螺旋/卷曲转变算法AGADIR所使用的相应值的替代。肽螺旋含量的预测几乎与使用最初校准的参数集所获得的预测一样成功;与实验观察到的α螺旋群体的相关性为0.91,这证明我们的理论估计对于我们肽数据库中常见的氨基酸对来说是相当正确的。此外,我们通过实验确定了i、i + 4位置的赖氨酸-异亮氨酸、苏氨酸-异亮氨酸和苯丙氨酸-异亮氨酸氨基酸对以前未表征的相互作用能。实验值与计算得到的理论估计值相比很有利。重要的是,苏氨酸-异亮氨酸和苯丙氨酸-异亮氨酸相互作用的计算值比基于化学相似性的能量更好,而赖氨酸-异亮氨酸的计算值与之相似。因此,计算技术可用于为氨基酸对相互作用提供精确的能量,这一事实支持了基于结构能量的计算工具用于结构预测和序列设计的开发。

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