Insights from coarse-grained go models for protein folding and dynamics

Abstract

Exploring the landscape of large scale conformational changes such as protein folding at atomistic detail poses a considerable computational challenge. Coarse-grained representations of the peptide chain have therefore been developed and over the last decade have proved extremely valuable. These include topology-based Go models, which constitute a smooth and funnel-like approximation to the folding landscape. We review the many variations of the Go model that have been employed to yield insight into folding mechanisms. Their success has been interpreted as a consequence of the dominant role of the native topology in folding. The role of local contact density in determining protein dynamics is also discussed and is used to explain the ability of Go-like models to capture sequence effects in folding and elucidate conformational transitions.