Predicting the alternative conformation of a known protein structure based on the distogram of AlphaFold2

Abstract AlphaFold2 (AF2) has become one of the most established and leading tools for predicting protein structures, although it often favors a single conformation. While it has been shown that sampling different conformations is possible by manipulating the multiple sequence alignment (MSA), the potential for multi‐state information within a standard AF2 prediction remains underexplored. In this work, we demonstrate that even with a deep MSA, AF2 predictions encode structural heterogeneity. Specifically, we observe that the predicted residue–residue distance distributions often exhibit multiple probability peaks before recycling, suggesting the presence of alternative states. We derive state‐specific distance restraints by fitting and separating these multi‐peak distributions. These restraints are then incorporated into Rosetta as energy terms to model large‐scale conformational transitions. Across multiple protein systems undergoing diverse types of conformational changes, our method effectively samples alternative conformations starting from an input conformation, producing models comparable to those from existing approaches. Our findings highlight a previously underutilized feature of AF2 predictions and offer a novel strategy to take advantage of these insights to study conformational flexibility and dynamics in proteins. This work broadens the applicability of AF2 in structural biology and the modeling of multi‐state protein systems.