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富士山型适应度景观上随机突变体的适应度谱。

Fitness spectrum among random mutants on Mt. Fuji-type fitness landscape.

作者信息

Aita T, Husimi Y

机构信息

Graduate School of Science and Engineering, Saitama University, Urawa, Japan.

出版信息

J Theor Biol. 1996 Oct 21;182(4):469-85. doi: 10.1006/jtbi.1996.0189.

Abstract

Statistical properties of a Mt. Fuji-type fitness landscape on a multi-valued sequence space were analysed. We constructed the model landscape based on additivity of the free energy contributed by each residue on a biopolymer, introducing "tolerance functions" that describe tolerance to residue substitution at each site. The fitness spectrum among a random mutant population around a wild-type sequence was theoretically obtained as the probability density distribution function of fitness. As the Hamming distance from the wild-type to the mutants increases, the mean fitness of the mutant population gradually decreases, and the variance of the fitness increases. These features are originated from the anisotropy of the landscape. On the assumption that the free energy is statistically additive around a wild-type in a sequence space of a real biopolymer, one can estimate the Hamming distance from the wild-type to the optimal biopolymer and the fitness of the optimum. Two sets of experimental data were analysed: (1) a promoter strength spectrum of a mutant population produced by the random mutagenesis of a wild-type lac promoter; (2) four stepwise optimization processes of different peptide mixtures evaluated with ligand binding affinity. Analysis of both experiments showed the compatibility with the hypothesis that local fitness landscapes around contemporary biopolymers are near Mt. Fuji-type. The mean slope of each of the four affinity landscapes for (2) was estimated as delta In K(d)/delta d = 1.3 approximately 2.3, where d denotes the Hamming distance from the optimum and K(d) represents the mean dissociation constant of sequences located at the Hamming distance of d. Mt. Fuji-type landscape can be regarded as a zero-th order approximation to the real local landscape just like an "ideal gas". We showed a method to gauge statistically the shape of a near Mt. Fuji-type landscape by measuring mutant fitness spectra.

摘要

分析了多值序列空间上富士山型适应度景观的统计特性。我们基于生物聚合物上每个残基贡献的自由能的加和性构建了模型景观,引入了描述每个位点对残基替换耐受性的“耐受函数”。理论上获得了野生型序列周围随机突变群体中的适应度谱,作为适应度的概率密度分布函数。随着从野生型到突变体的汉明距离增加,突变群体的平均适应度逐渐降低,适应度的方差增加。这些特征源于景观的各向异性。假设在真实生物聚合物的序列空间中,围绕野生型的自由能在统计上是可加的,则可以估计从野生型到最优生物聚合物的汉明距离以及最优解的适应度。分析了两组实验数据:(1)野生型乳糖启动子随机诱变产生的突变群体的启动子强度谱;(2)用配体结合亲和力评估的不同肽混合物的四个逐步优化过程。对这两个实验的分析表明,与当代生物聚合物周围的局部适应度景观接近富士山型这一假设相符。对于(2)中四个亲和力景观中的每一个,平均斜率估计为δlnK(d)/δd = 1.3 约 2.3,其中d表示与最优解的汉明距离,K(d)表示位于汉明距离为d处的序列的平均解离常数。富士山型景观可以被视为对真实局部景观的零阶近似,就像“理想气体”一样。我们展示了一种通过测量突变体适应度谱来统计测量接近富士山型景观形状的方法。

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