Prediction of protein function improving sequence remote alignment search by a fuzzy logic algorithm

Antonio Gómez, Juan Cedano, Jordi Espadaler, Antonio Hermoso, Jaume Piñol, Enrique Querol

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

The functional annotation of the new protein sequences represents a major drawback for genomic science. The best way to suggest the function of a protein from its sequence is by finding a related one for which biological information is available. Current alignment algorithms display a list of protein sequence stretches presenting significant similarity to different protein targets, ordered by their respective mathematical scores. However, statistical and biological significance do not always coincide, therefore, the rearrangement of the program output according to more biological characteristics than the mathematical scoring would help functional annotation. A new method that predicts the putative function for the protein integrating the results from the PSI-BLAST program and a fuzzy logic algorithm is described. Several protein sequence characteristics have been checked in their ability to rearrange a PSI-BLAST profile according more to their biological functions. Four of them: amino acid content, matched segment length and hydropathic and flexibility profiles positively contributed, upon being integrated by a fuzzy logic algorithm into a program, BYPASS, to the accurate prediction of the function of a protein from its sequence. © 2007 Springer Science+Business Media, LLC.
Original languageEnglish
Pages (from-to)130-139
JournalProtein Journal
Volume27
Issue number2
DOIs
Publication statusPublished - 1 Feb 2008

Keywords

  • Fuzzy logic
  • High redundancy homology
  • Protein function
  • PSI-BLAST

Fingerprint Dive into the research topics of 'Prediction of protein function improving sequence remote alignment search by a fuzzy logic algorithm'. Together they form a unique fingerprint.

Cite this