The oligodeoxynucleotide sequences corresponding to never-expressed peptide motifs are mainly located in the non-coding strand

By Giovanni Capone, Giuseppe Novello, Candida Fasano, Brett Trost, Mikelis G. Bickis, Anthony J. Kusalik, Darja Kanduc. 2010

13 citations recorded by the source corpus.

BackgroundWe study the usage of specific peptide platforms in protein composition. Using the pentapeptide as a unit of length, we find that in the universal proteome many pentapeptides are heavily repeated (even thousands of times), whereas some are quite rare, and a small number do not appear at all. To understand the physico-chemical-biological basis underlying peptide usage at the proteomic level, in this study we analyse the energetic costs for the synthesis of rare and never-expressed versus frequent pentapeptides. In addition, we explore residue bulkiness, hydrophobicity, and codon number as factors able to modulate specific peptide frequencies. Then, the possible influence of amino acid composition is investigated in zero- and high-frequency pentapeptide sets by analysing the frequencies of the corresponding inverse-sequence pentapeptides. As a final step, we analyse the pentadecamer oligodeoxynucleotide sequences corresponding to the never-expressed pentapeptides.ResultsWe find that only DNA context-dependent constraints (such as oligodeoxynucleotide sequence location in the minus strand, introns, pseudogenes, frameshifts, etc.) provide a coherent mechanistic platform to explain the occurrence of never-expressed versus frequent pentapeptides in the protein world.ConclusionsThis study is of importance in cell biology. Indeed, the rarity (or lack of expression) of specific 5-mer peptide modules implies the rarity (or lack of expression) of the corresponding n-mer peptide sequences (with n > 5), so possibly modulating protein compositional trends. Moreover the data might further our understanding of the role exerted by rare pentapeptide modules as critical biological effectors in protein-protein interactions.

Subfields: Molecular Biology

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Citations in the corpus

UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches (2014, methodology): “…of metagenomics data (Foerstner et al., 2008; Wommack et al., 2012), developing large-scale hierarchical clustering algorithms (Loewenstein et al., 2008), studying gene duplication (Rivera et al., 2010) and conducting genomic studies of peptide and oligonucleotide frequencies (Capone et al., 2010).”