Investigating primary sequence and structural features of viral proteins/genes has revealed molecular mimicry and evolutionary relationship linking viruses to eukaryotes. The continuous improvement in sequencing-techniques makes available almost daily the whole genome/proteome of several microorganisms, making now possible systematic analyses of evolutionary correlations and accurate phylogeny investigations. In the present study we set up a methodology to identify significant and relevant similarities between viral and human proteomes. To this aim, the following steps were applied: i) identification of local similarity corresponding to continuous identity over at least 8-residues long fragments; ii) filtering results for statistical significance of the identified similarities, according to BLAST parameters for short sequences; iii) additional filters applied to the BLAST outputs, to select specific viruses. The present study indicates a novel accurate methodology to find relevant similarities among virus and human proteomes, useful to further investigate pathogenic mechanisms underlying infectious and non-infectious diseases.

A computational strategy to investigate relevant similarities between virus and human proteins: Local high similarities between herpes and human proteins

Facchiano A;Facchiano;
2011

Abstract

Investigating primary sequence and structural features of viral proteins/genes has revealed molecular mimicry and evolutionary relationship linking viruses to eukaryotes. The continuous improvement in sequencing-techniques makes available almost daily the whole genome/proteome of several microorganisms, making now possible systematic analyses of evolutionary correlations and accurate phylogeny investigations. In the present study we set up a methodology to identify significant and relevant similarities between viral and human proteomes. To this aim, the following steps were applied: i) identification of local similarity corresponding to continuous identity over at least 8-residues long fragments; ii) filtering results for statistical significance of the identified similarities, according to BLAST parameters for short sequences; iii) additional filters applied to the BLAST outputs, to select specific viruses. The present study indicates a novel accurate methodology to find relevant similarities among virus and human proteomes, useful to further investigate pathogenic mechanisms underlying infectious and non-infectious diseases.
2011
Istituto di Scienze dell'Alimentazione - ISA
9789898425362
Additional filters
Autoimmunity
Computational strategy
Continuous improvements
Evolutionary relationships
Human proteins
Local similarity
Molecular mimicry
Pathogenic mechanisms
Primary sequences
Proteomes
Short sequences
Statistical significance
Structural feature
Systematic analysis
Viral proteins
Biology
Evolutionary algorithms
Investments
Mathematical models
Viruses
Bioinformatics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/296128
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