Département de Biochimie, Université de Montréal, Montréal, QC, Canada.
Centre Robert-Cedergren en Bioinformatique et Génomique, Université de Montréal, Montréal, QC, Canada.
Bioinformatics. 2019 Oct 15;35(20):4053-4062. doi: 10.1093/bioinformatics/btz175.
Protein evolution is determined by forces at multiple levels of biological organization. Random mutations have an immediate effect on the biophysical properties, structure and function of proteins. These same mutations also affect the fitness of the organism. However, the evolutionary fate of mutations, whether they succeed to fixation or are purged, also depends on population size and dynamics. There is an emerging interest, both theoretically and experimentally, to integrate these two factors in protein evolution. Although there are several tools available for simulating protein evolution, most of them focus on either the biophysical or the population-level determinants, but not both. Hence, there is a need for a publicly available computational tool to explore both the effects of protein biophysics and population dynamics on protein evolution.
To address this need, we developed SodaPop, a computational suite to simulate protein evolution in the context of the population dynamics of asexual populations. SodaPop accepts as input several fitness landscapes based on protein biochemistry or other user-defined fitness functions. The user can also provide as input experimental fitness landscapes derived from deep mutational scanning approaches or theoretical landscapes derived from physical force field estimates. Here, we demonstrate the broad utility of SodaPop with different applications describing the interplay of selection for protein properties and population dynamics. SodaPop is designed such that population geneticists can explore the influence of protein biochemistry on patterns of genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution.
Source code and binaries are freely available at https://github.com/louisgt/SodaPop under the GNU GPLv3 license. The software is implemented in C++ and supported on Linux, Mac OS/X and Windows.
Supplementary data are available at Bioinformatics online.
蛋白质进化是由多个层次的生物组织中的力量决定的。随机突变会立即影响蛋白质的生物物理特性、结构和功能。这些相同的突变也会影响生物体的适应性。然而，突变的进化命运，无论是成功固定还是被清除，也取决于种群大小和动态。理论上和实验上都有越来越大的兴趣将这两个因素整合到蛋白质进化中。虽然有几种工具可用于模拟蛋白质进化，但它们大多数都侧重于生物物理或群体水平的决定因素，而不是两者都有。因此，需要有一种公共可用的计算工具来探索蛋白质生物物理学和种群动态对蛋白质进化的影响。
为了解决这个需求，我们开发了 SodaPop，这是一个在无性种群的种群动态背景下模拟蛋白质进化的计算套件。SodaPop 接受几种基于蛋白质生物化学或其他用户定义的适应度函数的适应度景观作为输入。用户还可以提供来自深度突变扫描方法的实验适应度景观或来自物理力场估计的理论适应度景观作为输入。在这里，我们展示了 SodaPop 的广泛应用，包括描述蛋白质特性选择和种群动态相互作用的不同应用。SodaPop 的设计使得群体遗传学家可以探索蛋白质生物化学对遗传变异模式的影响，生物化学家和生物物理学家可以探索种群大小和人口统计学对蛋白质进化的作用。
源代码和二进制文件可在 https://github.com/louisgt/SodaPop 下根据 GNU GPLv3 许可证免费获得。该软件是用 C++实现的，支持 Linux、Mac OS/X 和 Windows。
补充数据可在生物信息学在线获得。
