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蛋白质中各向异性侧链堆积分析及其在高分辨率结构预测中的应用。

Analysis of anisotropic side-chain packing in proteins and application to high-resolution structure prediction.

作者信息

Misura Kira M S, Morozov Alexandre V, Baker David

机构信息

Department of Biochemistry, University of Washington, Box 357350, J-567 Health Sciences, Seattle, WA 98195-7350 USA.

出版信息

J Mol Biol. 2004 Sep 10;342(2):651-64. doi: 10.1016/j.jmb.2004.07.038.

Abstract

pi-pi, Cation-pi, and hydrophobic packing interactions contribute specificity to protein folding and stability to the native state. As a step towards developing improved models of these interactions in proteins, we compare the side-chain packing arrangements in native proteins to those found in compact decoys produced by the Rosetta de novo structure prediction method. We find enrichments in the native distributions for T-shaped and parallel offset arrangements of aromatic residue pairs, in parallel stacked arrangements of cation-aromatic pairs, in parallel stacked pairs involving proline residues, and in parallel offset arrangements for aliphatic residue pairs. We then investigate the extent to which the distinctive features of native packing can be explained using Lennard-Jones and electrostatics models. Finally, we derive orientation-dependent pi-pi, cation-pi and hydrophobic interaction potentials based on the differences between the native and compact decoy distributions and investigate their efficacy for high-resolution protein structure prediction. Surprisingly, the orientation-dependent potential derived from the packing arrangements of aliphatic side-chain pairs distinguishes the native structure from compact decoys better than the orientation-dependent potentials describing pi-pi and cation-pi interactions.

摘要

π-π、阳离子-π和疏水堆积相互作用赋予蛋白质折叠特异性,并赋予天然态稳定性。作为朝着开发改进的蛋白质中这些相互作用模型迈出的一步,我们将天然蛋白质中的侧链堆积排列与通过Rosetta从头结构预测方法产生的紧密诱饵中发现的排列进行比较。我们发现,在天然分布中,芳香族残基对的T形和平行偏移排列、阳离子-芳香族对的平行堆叠排列、涉及脯氨酸残基的平行堆叠对以及脂肪族残基对的平行偏移排列都有富集。然后,我们研究了使用 Lennard-Jones 和静电模型能够在多大程度上解释天然堆积的独特特征。最后,我们基于天然和紧密诱饵分布之间的差异推导出取向依赖的π-π、阳离子-π和疏水相互作用势,并研究它们在高分辨率蛋白质结构预测中的功效。令人惊讶的是,从脂肪族侧链对的堆积排列得出的取向依赖势比描述π-π和阳离子-π相互作用的取向依赖势能更好地区分天然结构和紧密诱饵。

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