Identifying proteins involved in parasitism by discovering degenerated motifs

author: Celine Vens, Department of Computer Science, KU Leuven
published: Nov. 8, 2010,   recorded: October 2010,   views: 123
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Identifying motifs in biological sequences is an important challenge in biology. Proteins involved in the same biological system or physiological function (e.g., immune response, chemo-sensation, secretion, signal transduction,...) are subject to similar evolutionary and functional pressures that have an outcome at the protein sequence level. Finding motifs specific to proteins involved in the same process can help deciphering the determinants of their fate and thus be used in identifying new candidate proteins involved in important biological systems.

To our knowledge all currently available methods search motifs in protein sequences at the amino acid level, sometimes allowing degenerate motifs to comply with point variations [1, 2]. However, it is known that conservation of the three-dimensional structure is more important than conservation of the actual sequence for the biological function and proteins that have no detectable sequence similarity can fold in similar structures. At a given position in the sequence, the nature and physico-chemical properties of amino acids in protein families is more conserved than the amino acid itself.

We propose a method that allows to identify emerging motifs based both on conservation of amino acids and on the physico-chemical properties of these residues. Given a set of protein sequences known to be involved in a common biological system (positive set) and a set of protein sequences known not to be involved in that system (negative set) our method is able to identifiy motifs that are frequent in positive sequences while infrequent or absent in negative sequences. The identified motifs can then be used to mine the wealth of protein data now available, in order to identify new previously uncharacterized proteins involved in biological processes of importance.

In this work, the biological system of interest is the protein secretion of a plant parasitic nematode (roundworm). The nematode in question, Meloidogyne incognita [3], is a major crop devastator, and controlling it has become an important issue. In this context, it is important to identify the proteins secreted by the nematode into the plant (e.g. cell-wall degrading enzymes that allow the parasite to enter the plant).

See Also:

Download slides icon Download slides: mlsb2010_vens_ipi_01.pdf (3.0┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: