Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction

Tatjana Braun, Julia Koehler Leman, Oliver F. Lange

Abstract: Author Summary Recently, a breakthrough has been achieved in modeling the atomic 3D structures of proteins from their sequence alone without requiring any experimental work on the protein itself. To achieve this goal, a database of evolutionary related sequences is analyzed to find co-evolving residues, giving insight into which residues are in close proximity to each other. These residue-residue contacts can help to drive a computer simulation with an atomic-scale physical model of the protein structure from a random starting conformation to a native-like 3D conformation. Although much effort is being put into the improvement of residue-residue contact predictions, their accuracy will always be limited. Therefore, structure prediction protocols with a high tolerance against incorrect distance restraints are needed. Here, we present a structure prediction protocol that combines evolutionary information with the iterative sampling approach of the molecular modeling suite Rosetta, called RASREC. RASREC has been shown to converge faster to near-native models and to be more robust against incorrect distance restraints than standard prediction protocols. It is therefore perfectly suited for restraints obtained from predicted residue-residue contacts with limited accuracy. We show that our protocol outperforms other currently published structure prediction methods and is able to achieve accurate structures, even if the accuracy of predicted contacts is low.