A novel complexity measure for comparative analysis of protein sequences from complete genomes.
Analysis of sequence complexities of proteins is an important step in the characterization and classification of new genomes. A new measure has been proposed to compute sequence complexity in protein sequences based on linguistic complexity. The algorithm requires a single parameter, is computationally simple and provides a framework for comparative genomic analysis. Protein sequences were classified into groups of high or low complexity based on a quantitative measure termed F(c), which is proportional to the fraction of low complexity sequence present in the protein. The algorithm was tested on sequences of 196 non-homologous proteins whose crystal structures are available at </=2.0 A resolution. Protein sequences of high complexity had 'globular' structures (95% agreement), whereas those of low complexity had non-globular structures (80% agreement). Application of this measure to proteins of unknown structure/function from different genomes revealed that the sequences of high complexity constitute the majority in all genomes (about 90% in Archaea, about 93% in Eubacteria, 89% in Saccharomyces cerevisiae and 90% in Caenorhabditis elegans). Aeropyrum pernix among Archaeae and Deinococcus radiodurans among Eubacteria have the lowest fraction of high complexity proteins (75% and 80% respectively). Further, it was observed that a few bacterial pathogens (Mycobacterium tuberculosis, Pseudomonas aeruginosa) have high fraction of low complexity proteins. The program ScanCom is available from the authors as a PERL script (UNIX system).
Nandi
Tannistha
T
Institute of Genomics and Integrative Biology, Centre for Biochemical Technology, Mall Road, Delhi 110 007, India.
Dash
Debasis
D
Ghai
Rohit
R
B-Rao
Chandrika
C
Kannan
K
K
Brahmachari
Samir K
SK
Ramakrishnan
C
C
Ramachandran
Srinivasan
S
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D001419:Bacteria / Q000235:genetics; D019295:Computational Biology; D019615:Crenarchaeota / Q000235:genetics; D030562:Databases, Protein; D016678:Genome; D008969:Molecular Sequence Data; D011506:Proteins / Q000145:classification; D020449:Repetitive Sequences, Amino Acid; D020539:Sequence Analysis, Protein / Q000379:methods*
D011506:Proteins