López de la Paz M, Lacroix E, Ramírez-Alvarado M, Serrano L
European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.
J Mol Biol. 2001 Sep 7;312(1):229-46. doi: 10.1006/jmbi.2001.4918.
The design of beta-sheet proteins is still a challenge in the field of de novo protein design. Here, we have tested the validity of automatic design methods to create and/or improve beta-sheet peptides and proteins. We chose Betanova, a three-stranded beta-sheet peptide, as target system, and, as an automatic design tool, a protein design algorithm called PERLA (protein engineering rotamer library algorithm). PERLA was used to define both stabilising and destabilising single- and multiple-residue mutations of Betanova. Conformational analysis by NMR spectroscopy and far-UV circular dichroism (CD) allowed us to evaluate population differences among the set of designed peptides. Some of the new mutants are approximately 1 kcal/mol more stable than the wild-type peptide. Comparison of the scale of predicted and observed stabilities demonstrates that they are in good agreement for most peptides studied. Our results show that automatic design algorithms can be successfully applied to the design of beta-sheet peptides.
β-折叠蛋白质的设计在从头蛋白质设计领域仍然是一个挑战。在此，我们测试了自动设计方法用于创建和/或改进β-折叠肽和蛋白质的有效性。我们选择三链β-折叠肽Betanova作为目标系统，并使用一种名为PERLA（蛋白质工程旋转异构体库算法）的蛋白质设计算法作为自动设计工具。PERLA用于定义Betanova的稳定和不稳定单残基及多残基突变。通过核磁共振光谱和远紫外圆二色性（CD）进行的构象分析使我们能够评估所设计肽组之间的群体差异。一些新突变体比野生型肽稳定约1千卡/摩尔。预测稳定性与观察稳定性规模的比较表明，对于大多数研究的肽来说，二者吻合良好。我们的结果表明，自动设计算法可以成功应用于β-折叠肽的设计。
