Aita Takuyo, Hamamatsu Norio, Nomiya Yukiko, Uchiyama Hidefumi, Shibanaka Yasuhiko, Husimi Yuzuru
Tsukuba Research Institute, Novartis Pharma K. K., Ohkubo 8, Tsukuba 300-2611, Japan.
Biopolymers. 2002 Jul 5;64(2):95-105. doi: 10.1002/bip.10126.
We present a method for analysis of a fitness landscape of a biopolymer with significantly epistatic sites. The analysis is based on a quasi-additive fitness model. The fitness model is constructed with additive terms conducted by "site-fitness" and epistatic terms conducted by "pair-fitness," where the site-fitness is a fitness contribution from an independent residue and the pair-fitness is a fitness contribution from a pair of epistatic residues. As a case study, we analyzed the sequence-fitness data for 45 clones of thermostable prolyl endopeptidase mutants. They were generated by a mutation scrambling method, which can accumulate advantageous mutations. The fitness contributions from 14 single-point mutations including E67Q and Q656R were identified by the analysis. As a result, we found that the fitness model with a significant epistatic term by a pair of the 67th site and 656th site was in good agreement with the experimental data and that the explored landscape in the binary 14-dimensional sequence space is still a mountainous landscape with twin peaks. The validity was supported by the analysis of mutant fitness distributions derived from another mutation scrambling experiment and by (3D) structural data.
我们提出了一种分析具有显著上位性位点的生物聚合物适应度景观的方法。该分析基于准加性适应度模型。适应度模型由“位点适应度”产生的加性项和“配对适应度”产生的上位性项构建而成，其中位点适应度是独立残基的适应度贡献，配对适应度是一对上位性残基的适应度贡献。作为案例研究，我们分析了45个热稳定脯氨酰内肽酶突变体克隆的序列 - 适应度数据。它们是通过一种能够积累有利突变的突变重排方法产生的。通过分析确定了包括E67Q和Q656R在内的14个单点突变的适应度贡献。结果，我们发现由第67位和第656位的一对位点产生显著上位性项的适应度模型与实验数据高度吻合，并且在二元14维序列空间中探索的景观仍然是具有双峰的山地景观。通过对另一个突变重排实验得出的突变体适应度分布的分析以及（三维）结构数据支持了该有效性。
