Our latest review is out in Current Opinion: Proteins with alternative folds reveal blind spots in AlphaFold-based protein structure prediction

www.sciencedirect.com/science/arti...

Together, these results suggest that AF2 has more to learn about protein energy landscapes. They also suggest that AF2 sometimes struggles to associate amino acid sequences with their correct conformations, as it did for BCCIP-alpha (correct fold on right):

Further, AF2 and AF-cluster failed to predict new fold switchers discovered after AF2.3.1 was trained:

AF2 based methods performed worse when predicting fold switchers outside of the training set. For instance, AF-cluster predictions could not distinguish between sequence-diverse fold-switching and single-folding RfaH homologs, and all helical predictions had low confidence.

Consistently, AF2's structure module--hypothesized to have learned folding physics--could not discriminate between low and high energy conformations of fold switchers. (TM-scores on x- and y- axes).

AF2 confidence metrics selected against diverse experimentally observed conformations, particularly alternative folds (p < 8.1*10-4, one-sided binomial test), in favor of experimentally unobserved conformations

We tested 5 AF2-based methods on 93 fold-switching proteins likely in AF2’s training set, >280,000 predictions total. Each method predicted <20% of fold switchers and favored experimentally unobserved folds (other) over experimentally observed alternative folds (Fold2).