Is Five Percent Too Small? Analysis of the Overlaps between Disorder, Coiled Coil and Collagen Predictions in Complete Proteomes
Zoltán Gáspári
Abstract
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Zoltán Gáspári
Abstract
Open-access reader
Identification of intrinsic disorder in proteins and proteomes has revealed important novel aspects of protein function and interactions. However, it has been pointed out that several oligomeric fibrillar protein motifs such as coiled coils and collagen triple helical segments can also identified as intrinsically disordered. This feature has not yet been investigated in more detail at the proteome level. The present work aims at the identification and quantification of such overlaps in full proteomes to assess their significance in large-scale studies of protein disorder. It was found that the percentage of cross-predicted residues is around 5% in the human proteome and is generally near that value in other metazoan ones but shows remarkable variation in different organisms. In particular, smaller proteomes are increasingly prone to such cross-predictions, thus, especially the analysis of viral proteomes requires the use of specific prediction tools.
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Identification of intrinsic disorder in proteins and proteomes has revealed important novel aspects of protein function and interactions. However, it has been pointed out that several oligomeric fibrillar protein motifs such as coiled coils and collagen triple helical segments can also identified as intrinsically disordered. This feature has not yet been investigated in more detail at the proteome level. The present work aims at the identification and quantification of such overlaps in full proteomes to assess their significance in large-scale studies of protein disorder. It was found that the percentage of cross-predicted residues is around 5% in the human proteome and is generally near that value in other metazoan ones but shows remarkable variation in different organisms. In particular, smaller proteomes are increasingly prone to such cross-predictions, thus, especially the analysis of viral proteomes requires the use of specific prediction tools.
Key concepts: Proteome, Computational biology, Human proteome project, Identification (biology), Function (biology), Biology, Intrinsically disordered proteins, Bioinformatics