Native state of natural proteins optimizes local entropy

Abstract

The differing ability of polypeptide conformations to act as the native state of proteins has long been rationalized in terms of differing kinetic accessibility or thermodynamic stability. Building on the successful applications of physical concepts and sampling algorithms recently introduced in the study of disordered systems, in particular artificial neural networks, we quantitatively explore how well a quantity known as the local entropy describes the native state of model proteins. In lattice models and all-atom representations of proteins, we are able to efficiently sample high local entropy states and to provide a proof of concept of enhanced stability and folding rate. Our methods are based on simple and general statistical-mechanics arguments, and thus we expect that they are of very general use.

Key interaction patterns in proteins revealed by cluster expansion of the partition function

“…For the 4 most abundant graphs, remarkably, the counts found in natural proteins are larger than for random decoys (red bars in Fig. 5), obtained from the collapse of a protein model in which all atoms interact with the same energy [18].…”

“…It was suggested that some protein conformations are more 'designable' than others, being able to act as native state of more sequences [11]. Several properties of the native conformation have been associated with an increased designability, including conformational symmetries [12][13][14], abundance of local interactions [15], of returning loops [16], of loops of specified size [17], or a large local entropy [18].…”