Department of Chemical Engineering, Princeton University, Princeton, New Jersey, USA.
Biophys J. 2010 May 19;98(10):2337-46. doi: 10.1016/j.bpj.2010.01.057.
Two de novo protein design frameworks are applied to the discovery of new compstatin variants. One is based on sequence selection and fold specificity, whereas the other approach is based on sequence selection and approximate binding affinity calculations. The proposed frameworks were applied to a complex of C3c with compstatin variant E1 and new variants with improved binding affinities are predicted and experimentally validated. The computational studies elucidated key positions in the sequence of compstatin that greatly affect the binding affinity. Positions 4 and 13 were found to favor Trp, whereas positions 1, 9, and 10 are dominated by Asn, and position 11 consists mainly of Gln. A structural analysis of the C3c-bound peptide analogs is presented.
两种从头蛋白质设计框架被应用于新型 Compstatin 变体的发现。一种基于序列选择和折叠特异性,而另一种方法则基于序列选择和近似结合亲和力计算。所提出的框架被应用于 C3c 与 Compstatin 变体 E1 的复合物,预测并实验验证了具有改善结合亲和力的新型变体。计算研究阐明了 Compstatin 序列中对结合亲和力有重大影响的关键位置。位置 4 和 13 有利于色氨酸,而位置 1、9 和 10 主要由天冬酰胺主导,位置 11 主要由谷氨酰胺组成。呈现了与 C3c 结合的肽类似物的结构分析。