Direct correlation analysis improves fold recognition

[Display omitted] ► The problem of protein prediction from sequence is difficult and incompletely solved. ► We show that a new method based on correlated mutations in a multiple sequence alignment, filtered through a process to extract direct contacts provide powerful constraints on selecting the correct fold in a large number of well constructed decoy models. The extraction of correlated mutations through the method of direct information (DI) provides predicted contact residue pairs that can be used to constrain the three dimensional structures of proteins. We apply this method to a large set of decoy protein folds consisting of many thousand well-constructed models, only tens of which have the correct fold. We find that DI is able to greatly improve the ranking of the true (native) fold but others still remain high scoring that would be difficult to discard due to small shifts in the core beta sheets.