A pipeline from sequence alignments through a Potts model to an Ising foldon chain predicts protein folding curves, subdomains, and mutation effects, but without new experimental validation in this paper.
Inferring protein folding mechanisms from natural sequence diversity
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abstract
Protein sequences serve as a natural record of the evolutionary constraints that shape their functional structures. We show that it is possible to use only sequence information to go beyond predicting native structures and global stability to infer the folding mechanisms of globular proteins. The one- and two-body evolutionary energy fields at the amino-acid level are mapped to a coarse-grained description of folding, where proteins are divided into contiguous folding elements, commonly referred to as foldons. For 15 diverse protein families, we calculated the folding mechanisms of hundreds of proteins by simulating an Ising chain of foldons, with their energetics determined by the amino acid sequences. We show that protein topology imposes limits on the variability of folding cooperativity within a family. While most beta and alpha/beta structures exhibit only a few possible mechanisms despite high sequence diversity, alpha topologies allow for diverse folding scenarios among family members. We show that both the stability and cooperativity changes induced by mutations can be computed directly using sequence-based evolutionary models.
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Predicting protein folding dynamics using sequence information
A pipeline from sequence alignments through a Potts model to an Ising foldon chain predicts protein folding curves, subdomains, and mutation effects, but without new experimental validation in this paper.