Prediction of contacts from correlated sequence substitutions

Recent work has led to a substantial improvement in the accuracy of predictions of contacts between amino acids using evolutionary information derived from multiple sequence alignments. Where large numbers of diverse sequence relatives are available and can be aligned to the sequence of a protein of unknown structure it is now possible to generate high-resolution models without recourse to the structure of a template. In this review we describe these exciting new techniques and critically assess the state-of-the-art in contact prediction in the light of these. While concentrating on methods, we also discuss applications to protein and RNA structure prediction as well as potential future developments.