![]() ![]() The original change could then be reversed once the epistasis was overcome. Overcoming epistasis typically involved making a change to one amino acid that paved the way for further changes while avoiding the need to lose fitness. Contrary to expectations, the results suggested that the protein could evolve quickly to maximise fitness despite there being epistasis between the four amino acids. focused on four amino acids in part of a protein called GB1 and tested the efficiency of every possible combination of these four amino acids, a total of 160,000 (20 4) variants. However, new techniques have now made it easier to study protein evolution by testing many more protein variants. ![]() Previous studies only measured the fitness of a few variants and showed that epistasis could block protein evolution by requiring the protein to lose some fitness before it could improve further. Studying protein evolution involves making variants of the same protein, each with just a few changes, and comparing how efficient, or “fit”, they are. Proteins are made from twenty different kinds of amino acid, and there are millions of different combinations of amino acids that could, in theory, make a protein of a given length. This phenomenon is called epistasis and in some cases it can trap proteins in a sub-optimal form and prevent them from improving further. However the effect of each change depends on the protein as a whole, and so two changes that separately make the protein worse can make it much better if they occur together. These changes usually happen one at a time and natural selection tends to preserve those changes that make the protein more efficient at its specific tasks, while discarding those that impair the protein’s activity. Proteins can evolve over time by changing their component parts, which are called amino acids. These indirect paths alleviate the constraint on adaptive protein evolution, suggesting that the heretofore neglected dimensions of sequence space may change our views on how proteins evolve. We found that while reciprocal sign epistasis blocked many direct paths of adaptation, such evolutionary traps could be circumvented by indirect paths through genotype space involving gain and subsequent loss of mutations. Here we experimentally characterized the fitness landscape of four sites in protein GB1, containing 20 4 = 160,000 variants. In reality, the dimensionality of protein sequence space is higher (20 L) and there may be higher-order interactions among more than two sites. Previous empirical studies on fitness landscapes were confined to either the neighborhood around the wild type sequence, involving mostly single and double mutants, or a combinatorially complete subgraph involving only two amino acids at each site. The structure of fitness landscapes is critical for understanding adaptive protein evolution. ![]()
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