Our method for predicting folding dynamics/mechanisms from sequence info is now a book chapter! link.springer.com/book/9781071...

@diegulise.bsky.social

Some sites have, on average over all the possible variants, high Dark Energy. In those cases, there is a function beyond protein folding affecting natural selection. This is clearly the case of Enzyme catalytic sites

The idea is simple. For a deleterious mutation, we expect the protein to get destabilized. But how much? Correlations between a ΔΔG DMS and the corresponding ESM-2 scores are not perfect. We define the difference between these two free energies as a ‘Dark Energy’.

Also, we show that both the stability and cooperativity changes induced by mutations can be computed directly using sequence-based evolutionary models.
6/n

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.
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For 15 diverse protein families, we computed the folding mechanisms of hundreds of proteins by simulating an Ising chain of folding elements, or foldons. The energetics is determined by each amino acid sequence.
4/n

We show that it is possible to use sequence info to go beyond predicting native structures and global stability to infer the folding mechanisms of globular proteins. We mapped a Potts evolutionary energy at the amino-acid level to a coarse-grained description of folding.
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