Hydrophobic cluster analysis at protein and proteome scales

Hydrophobic Cluster Analysis (HCA) adds secondary structure information to the analysis of protein amino acid sequence. Focusing on the elementary building blocks of protein folds, this approach has proved to be a powerful tool for detecting distant (hidden) relationships between proteins. At a time when huge masses of data are now available, both in terms of protein sequences and models of three-dimensional structures, it still constitutes a relevant tool for analyzing structural features at the scale of whole proteomes, enabling, among other things, to characterize the continuum between disorder and order and to explore the characteristics of protein dark matter. The aim of this mini-review is to provide a brief overview of this approach, describing its principles and achievements, recent developments and future prospects. • HCA gives information on regular secondary structures from a single protein sequence • HCA-based fold signatures allow to detect remote relationships • Segments with high density in hydrophobic clusters are foldable • Foldability indexes position foldable segments on a disorder to order continuum • HCA-derived features open perspectives to better characterize the dark proteome