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| Heidelberg,
Tuesday 15 November 2005 |
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| Many needles, many haystacks |
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| EMBL PhD student Victor Neduva and Group Leader Rob Russell |
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Press
Release 15 November 2005 [PDF]
A new method to discover links between cellular machines
Most of what happens in cells is the work of machines
that contain dozens of molecules, chiefly proteins.
With the completion of human and other genomes,
researchers now have a nearly complete 'parts list'
of such machines; what's lacking is the manual telling
where all the pieces go. A new study by scientists
at the European Molecular Biology Laboratory [EMBL]
promises to answer this question for some of the
smallest and trickiest components in the cellular
toolbox. Their work appears in the current issue
of the Public Library of Science's on-line journal,
PLoS Biology.
A protein consists of a sticky string
of amino acids which usually folds up because of
attractions between some of its atoms. This creates
a bundle called a globular domain whose shape and
chemistry determine what other molecules can bind
to it.
"If we could look at the chemical 'spelling'
of a protein and guess what machines it fits into,
we'd know a lot more about what happens in cells,"
says Rob Russell, head of the Heidelberg lab that
carried out the current study. "We've made
a lot of progress in predicting how globular domains
interact with each other. But sometimes a surface
on one globular domain will grab a tiny, string-like
region of another protein called a linear motif.
Finding such motifs and predicting where they fit
in is like looking for needles in haystacks."
Or like looking at a line of automobiles and trying
to decide which one a bulky motor fits into –
versus trying to find where a tiny screw goes. Linear
motifs are so small that it is hard to tell what
features allow them to bind to other molecules.
Now Victor Neduva, a PhD student in Russell's group,
has developed a method to scan molecules and tease
out new linear motifs.
"If two or more different proteins share a
binding partner, there is often a common motif,"
Neduva says. "The hard part is finding a 3-to-8
'letter' pattern in a protein sequence that may
be thousands of amino acids long."
The method Neduva and his colleagues invented draws
on large-scale studies of protein binding in the
cells of yeast, flies, worms and humans. Those studies
have produced parts lists of molecular machines.
And the data holds a wealth of information about
linear motifs – if it can be mined.
The scientists distilled all of this information
in a series of steps – discarding parts of
the proteins likely to dock via large surfaces,
and zooming in on small regions of the remaining
molecules that might hold motifs. Then it was up
to the computer to scan the sequences for small
patterns. The attempt was successful: in the fly
data, for example, 26 sets of proteins seemed to
be interacting through linear motifs.
"One challenge was to eliminate red herrings,
which crop up everywhere when you look for very
small patterns," Russell says. "The fact
that nine of these motifs were already known was
a sign we were on the right trail; we then did follow-up
experiments in collaboration with Luis Serrano's
group at EMBL to test some of the others."
One prediction, for example, suggested
that a linear motif would bind to the fly protein
translin. The scientists verified that this happened,
then they made subtle changes in the sequence. When
these changes stopped the molecules binding, they
knew they had a new linear motif.
Now the lab will expand the method; Russell predicts
that hundreds of linear motifs remain to be discovered.
This has important implications for the study of
genetic diseases. "A lot of work has gone into
discovering mutations that affect protein binding,"
he says. "Because linear motifs are so small,
every bit of information is crucial, and any change
is likely to be disruptive. But so far, because
of their size, these motifs have been below the
radar of most methods to tie protein structures
to disease."
Source article
Systematic discovery of new recognition peptides mediating protein interaction networks
V. Neduva, R. Linding, I. Su-Angrand, A. Stark,
F. De Masi, T. J. Gibson, J. Lewis, L. Serrano and
R. B. Russell
PLoS Biology, 15 November 2005
Press contact
Sarah Sherwood
EMBL Information Officer, European Molecular Biology
Laboratory, Meyerhofstrasse 1, 69117 Heidelberg,
Germany
Tel: +49 [0] 6221 387-125
E-mail: sarah.sherwood@embl.de |
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