Exploring the Evolutionary History of Kinetic Stability in the α-Lytic Protease Family.

In addition to encoding the tertiary fold and stability, the primary sequence of a protein encodes the folding trajectory and kinetic barriers that determine the speed of folding. How these kinetic barriers are encoded is not well understood. Here, we use evolutionary sequence variation in the α-lytic protease (αLP) protein family to probe the relationship between sequence and energy landscape.

Inferring a complete genotype-phenotype map from a small number of measured phenotypes.

Understanding evolution requires detailed knowledge of genotype-phenotype maps; however, it can be a herculean task to measure every phenotype in a combinatorial map. We have developed a computational strategy to predict the missing phenotypes from an incomplete, combinatorial genotype-phenotype map. As a test case, we used an incomplete genotype-phenotype dataset previously generated for the malaria parasite's 'chloroquine resistance transporter' (PfCRT).

Molecular ensembles make evolution unpredictable.

Evolutionary prediction is of deep practical and philosophical importance. Here we show, using a simple computational protein model, that protein evolution remains unpredictable, even if one knows the effects of all mutations in an ancestral protein background. We performed a virtual deep mutational scan-revealing the individual and pairwise epistatic effects of every mutation to our model protein-and then used this information to predict evolutionary trajectories.

High-order epistasis shapes evolutionary trajectories.

High-order epistasis-where the effect of a mutation is determined by interactions with two or more other mutations-makes small, but detectable, contributions to genotype-fitness maps. While epistasis between pairs of mutations is known to be an important determinant of evolutionary trajectories, the evolutionary consequences of high-order epistasis remain poorly understood. To determine the effect of high-order epistasis on evolutionary trajectories, we computationally removed high-order epistasis from experimental genotype-fitness maps containing all binary combinations of five mutations.

Detecting High-Order Epistasis in Nonlinear Genotype-Phenotype Maps.

High-order epistasis has been observed in many genotype-phenotype maps. These multi-way interactions between mutations may be useful for dissecting complex traits and could have profound implications for evolution. Alternatively, they could be a statistical artifact.