The respective roles of polar/nonpolar binary patterns and amino acid composition in protein regular secondary structures explored exhaustively using hydrophobic cluster analysis

Abstract

Several studies have highlighted the leading role of the sequence periodicity of polar and nonpolar amino acids (binary patterns) in the formation of regular secondary structures (RSS). However, these were based on the analysis of only a few simple cases, with no direct mean to correlate binary patterns with the limits of RSS. Here, HCA-derived hydrophobic clusters (HC) which are conditioned binary patterns whose positions fit well those of RSS, were considered. All the HC types, defined by unique binary patterns, which were commonly observed in three-dimensional (3D) structures of globular domains, were analyzed. The 180 HC types with preferences for either α-helices or β-strands distinctly contain basic binary units typical of these RSS. Therefore a general trend supporting the "binary pattern preference" assumption was observed. HC for which observed RSS are in disagreement with their expected behavior (discordant HC) were also examined. They were separated in HC types with moderate preferences for RSS, having "weak" binary patterns and versatile RSS and HC types with high preferences for RSS, having "strong" binary patterns and then displaying nonpolar amino acids at the protein surface. It was shown that in both cases, discordant HC could be distinguished from concordant ones by well-differentiated amino acid compositions. The obtained results could, thus, help to complement the currently available methods for the accurate prediction of secondary structures in proteins from the only information of a single amino acid sequence. This can be especially useful for characterizing orphan sequences and for assisting protein engineering and design.

Sequence characteristics responsible for protein‐protein interactions in the intrinsically disordered regions of caseins, amelogenins, and small heat‐shock proteins

“…[85,86] Pro-rich sequences tend to have stiff, but not rigid, conformations with little, if any α-helix. [87][88][89][90] The method of predicting nonlinear hydrophobic regions used by Horne and Lucy [79,84] is one that was developed for, and is applicable to, proteins in stable, folded conformations, [91] as explained by the developers of the method. [92] The postulated nonlinear hydrophobic motifs were identified by arranging the sequence in an α-helical net.…”

Order in Disorder as Observed by the “Hydrophobic Cluster Analysis” of Protein Sequences

“…As illustrated with the two examples shown in Figure , some HC species have clear preference for α‐helices (H) or β‐strands (E) and have binary patterns typical of the periodicity observed in these RSSs. These binary pattern preferences have been supported in a comprehensive way over the whole set of HC species present in the experimental 3D structures of globular domains . RSS prediction can be refined for HC with strong (E/H) but also moderate preferences (e/h) for any RSS by considering amino acid composition, as distinct amino acids profiles are observed for the two RSS states associated with each HC species …”

“…Of note is the overall good prediction of the limits of foldable regions when compared to experimental information. Moreover, good correspondences are globally observed between observed RSSs and predictions, particularly for clusters with strong affinities for RSSs (H and E), for which the binary pattern overwhelms the amino acid composition . These predictions are based on the single amino acid sequence information (thus differing from current RSS predictors, based on amino acid profiles) and on the HC binary pattern information (Table S1, Supporting Information).…”

“…These predictions are based on the single amino acid sequence information (thus differing from current RSS predictors, based on amino acid profiles) and on the HC binary pattern information (Table S1, Supporting Information). For those clusters that are more difficult to predict, the amino acid composition can help the prediction . For instance, cluster with P‐code 35 (h) in the EVH1 domain contains amino acids, such as V, I, T, C, S, which have preferences for extended structures.…”

HCAtk and pyHCA: A Toolkit and Python API for the Hydrophobic Cluster Analysis of Protein Sequences

“…For each protein provided in 56 a fasta file, an HCA plot is drawn, allowing the quick inspection of the hydrophobic cluster content of 57 a protein sequence, which gives information about its composition in regular secondary structures. A can be considered for evaluating the main propensities of hydrophobic clusters towards RSS [8,24].…”