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从氨基酸序列中提取折叠信息:在不存在三级相互作用的情况下对具有优先构象的蛋白质区域进行准确预测。

Extracting information on folding from the amino acid sequence: accurate predictions for protein regions with preferred conformation in the absence of tertiary interactions.

作者信息

Rooman M J, Kocher J P, Wodak S J

机构信息

Unité de Conformation des Macromolécules Biologiques, Université Libre de Bruxelles, Belgium.

出版信息

Biochemistry. 1992 Oct 27;31(42):10226-38. doi: 10.1021/bi00157a009.

Abstract

A recently developed procedure to predict backbone structure from the amino acid sequence [Rooman, M., Kocher, J. P., & Wodak, S. (1991) J. Mol. Biol, 221, 961-979] is fine tuned to identify protein segments, of length 5-15 residues, that adopt well-defined conformations in the absence of tertiary interactions. These segments are obtained by requiring that their predicted lowest energy structures have a sizable energy gap relative to other computed conformations. Applying this procedure to 69 proteins of known structure, we find that regions with largest energy gaps--those having highly preferred conformations--are also the most accurately predicted ones. On the basis of previous findings that such regions correlate well with sites that become structured early during folding, our approach provides the means of identifying such sites in proteins without prior knowledge of the tertiary structure. Furthermore, when predictions are performed so as to ignore the influence of residues flanking each segment along the sequence, a situation akin to excising the considered peptide from the rest of the chain, they offer the possibility of identifying protein segments liable to adopt well-defined conformations on their own. The described approach should have useful applications in experimental and theoretical investigations of protein folding and stability, and aid in designing peptide drugs and vaccines.

摘要

最近开发的一种从氨基酸序列预测主链结构的方法[鲁曼,M.,科赫尔,J. P.,& 沃达克,S.(1991)《分子生物学杂志》,221,961 - 979]经过了微调,以识别长度为5 - 15个残基的蛋白质片段,这些片段在没有三级相互作用的情况下会形成明确的构象。这些片段是通过要求其预测的最低能量结构相对于其他计算出的构象具有相当大的能量差距而获得的。将此方法应用于69个已知结构的蛋白质,我们发现能量差距最大的区域——那些具有高度偏好构象的区域——也是预测最准确的区域。基于先前的发现,即这些区域与折叠早期形成结构的位点密切相关,我们的方法提供了在不预先了解三级结构的情况下识别蛋白质中此类位点的手段。此外,当进行预测时忽略序列中每个片段侧翼残基的影响,这类似于从链的其余部分切除所考虑的肽段,此时它们提供了识别可能自身形成明确构象的蛋白质片段的可能性。所描述的方法在蛋白质折叠和稳定性的实验和理论研究中应该有有用的应用,并有助于设计肽类药物和疫苗。

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