Comprehensive Repertoire of Foldable Regions within Whole Genomes

• Published in: PLoS computational biology Vol. 9; no. 10; p. e1003280
• Main Authors: Faure, Guilhem, Callebaut, Isabelle
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.10.2013; PLOS; Public Library of Science (PLoS)
• Subjects: Amino Acid Sequence; Amino acids; Cluster Analysis; E coli; Fungal Proteins; Gene expression; Genome; Genomes; Genomics - methods; Humans; Hydrophobic and Hydrophilic Interactions; Methods; Models, Molecular; Models, Statistical; Molecular Sequence Data; Neural networks; Protein Folding; Protein Structure, Tertiary; Proteins; Proteins - chemistry; Proteins - genetics; Proteins - metabolism; Proteome; Protozoan Proteins; Sequence Analysis, DNA; Sequence Analysis, Protein; France; Protein Structure, Tertiary; Amino Acid Sequence; Hydrophobic & Hydrophilic Interactions; Genomics; Humans; Models, Molecular; Molecular Sequence Data; Fungal Proteins; Proteome; Models, Statistical; Protozoan Proteins; Sequence Analysis, DNA; Protein Folding; Proteins; Sequence Analysis, Protein; Genome; Cluster Analysis
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1003280

In order to get a comprehensive repertoire of foldable domains within whole proteomes, including orphan domains, we developed a novel procedure, called SEG-HCA. From only the information of a single amino acid sequence, SEG-HCA automatically delineates segments possessing high densities in hydrophobic clusters, as defined by Hydrophobic Cluster Analysis (HCA). These hydrophobic clusters mainly correspond to regular secondary structures, which together form structured or foldable regions. Genome-wide analyses revealed that SEG-HCA is opposite of disorder predictors, both addressing distinct structural states. Interestingly, there is however an overlap between the two predictions, including small segments of disordered sequences, which undergo coupled folding and binding. SEG-HCA thus gives access to these specific domains, which are generally poorly represented in domain databases. Comparison of the whole set of SEG-HCA predictions with the Conserved Domain Database (CDD) also highlighted a wide proportion of predicted large (length >50 amino acids) segments, which are CDD orphan. These orphan sequences may either correspond to highly divergent members of already known families or belong to new families of domains. Their comprehensive description thus opens new avenues to investigate new functional and/or structural features, which remained so far uncovered. Altogether, the data described here provide new insights into the protein architecture and organization throughout the three kingdoms of life.