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Protein evolution is determined by constraints at several 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 these 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 constraints 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 constraints, but not both.
SodaPop is a new 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 function. 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. SodaPop is designed such that population geneticists can explore the role of protein biochemistry on genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution. This highly flexible tool takes as input a fitness landscape based on protein biochemistry and biophysics, experimental deep mutational scans or a phenomenological distribution of fitness effects. SodaPop was designed such that population geneticists can explore the role of protein biochemistry on genetic variation, and that biochemists and biophysicists can explore the role of population size and demography on protein evolution.
The goal of this wiki is to demonstrate the functionalities of SodaPop and to provide useful and informative examples for its users.