Name
Title | ||
|---|---|---|
False occurrences of functional motifs in protein sequences highlight evolutionary constraints. |
Abstract | ||
|---|---|---|
False occurrences of functional motifs in protein sequences can be considered as random events due solely to the sequence composition of a proteome. Here we use a numerical approach to investigate the random appearance of functional motifs with the aim of addressing biological questions such as: How are organisms protected from undesirable occurrences of motifs otherwise selected for their functionality? Has the random appearance of functional motifs in protein sequences been affected during evolution?Here we analyse the occurrence of functional motifs in random sequences and compare it to that observed in biological proteomes; the behaviour of random motifs is also studied. Most motifs exhibit a number of false positives significantly similar to the number of times they appear in randomized proteomes (=expected number of false positives). Interestingly, about 3% of the analysed motifs show a different kind of behaviour and appear in biological proteomes less than they do in random sequences. In some of these cases, a mechanism of evolutionary negative selection is apparent; this helps to prevent unwanted functionalities which could interfere with cellular mechanisms.Our thorough statistical and biological analysis showed that there are several mechanisms and evolutionary constraints both of which affect the appearance of functional motifs in protein sequences. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1186/1471-2105-8-68 | BMC Bioinformatics |
Keywords | Field | DocType |
bioinformatics,algorithms,negative selection,protein sequence,false positive,microarrays,random sequence | Sequence alignment,Biology,Genetic variation,Amino Acid Motifs,Proteome,Bioinformatics,Genetics,DNA microarray,Peptide sequence | Journal |
Volume | Issue | ISSN |
8 | 1 | 1471-2105 |
Citations | PageRank | References |
1 | 0.41 | 15 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Allegra Via | 1 | 616 | 44.62 |
| Pier Federico Gherardini | 2 | 102 | 5.21 |
| Enrico Ferraro | 3 | 42 | 2.16 |
| Gabriele Ausiello | 4 | 301 | 23.59 |
| Gianpaolo Scalia Tomba | 5 | 2 | 1.16 |
| Manuela Helmer-Citterich | 6 | 456 | 33.41 |