Nucleic Acids Research 2005 33(Web Server Issue):W249-W251; doi:10.1093/nar/gki363
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Fragnostic: walking through protein structure space
Iddo Friedberg* and
Adam Godzik
The Burnham Institute 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA
*To whom correspondence should be addressed. Tel: +1 858 646 3100; Fax: +1 858 713 9925; Email: idoerg{at}burnham.org
Received February 8, 2005. Revised February 23, 2005. Accepted February 23, 2005.
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ABSTRACT
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The Fragnostic (
http://ffas.burnham.org/Fragnostic) web tool
implements a novel and useful view of protein structure space.
We mined a non-redundant subset of the PDB for common fragments
shared between proteins inhabiting different SCOP folds. Subsequently,
we formulated an inter-fold similarity measure based on fragment
sharing. Fold space is described as a graph whose nodes are
folds between which the edges are drawn depending on the extent
of fragment sharing. In this fashion, Fragnostic helps discover
meaningful relationships between proteins belonging to different
folds, based on sharing similar fragments in the proteins comprising
those folds. Distant fold similarity information is supplemented
by annotations taken from Gene Ontology, SCOP and CATH. Overall,
Fragnostic is a tool which helps discover structural and functional
relationships between proteins which are distantly related or
seemingly unrelated.
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BACKGROUND
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The two popular protein classification schemes, CATH (
1) and
SCOP (
2), partition the protein structure universe hierarchically,
proceeding from coarse-grained to fine-grained partitions. The
initial, coarse-grained partitioning of structure space is based
on the secondary structure content. Because there are two well-ordered
secondary structure elements, we have four possible classes
as the topmost partitioning rank in those databases (SCOP and
CATH actually use a few more,
ad hoc classes). Classes are then
more finely partitioned into folds (SCOP) or topologies (CATH),
based on manual assignment. There may be between 100 and 200
folds per class. We know from experience that many proteins
which are assigned to different folds share a structural/functional
similarity. When proteins are categorically assigned to different
folds, we lose important information about possible similarities
between individual proteins assigned to different folds. Furthermore,
because fold assignment is manual and sometimes arbitrary, there
are cases where a fold–fold similarity between proteins
inhabiting two different folds is glaringly obvious. These anomalies
arise from the categorical assignment of proteins in a hierarchical
classification scheme. We named the gap between the few classes
and the many folds the ‘granularity gap’. This granularity
gap acts as a barrier preventing us from seeing obvious and
not-so-obvious similarities between proteins from different
folds, as was elaborated upon in studies conducted by Harrison
et al. (
3) and Choi
et al. (
4).
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BRIDGING THE GRANULARITY GAP
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One way of bridging the granularity gap is to re-establish the
relationships between fold populations using similarities in
a sub-domain level. We have chosen to address this problem using
short fragments shared between populations of proteins in different
folds. In another place (I. Friedberg and A. Godzik, submitted
for publication) we describe in detail the generation and analysis
of a fragment dataset. Briefly, we used a non-redundant set
of solved structures, PDB-SELECT25 (
5), to generate a dataset
of 2.5
x 10
7 fragments of lengths 5, 10, 15 and 20 residues.
Fragments were generated using a sliding window along each protein's
sequence. Those fragments were aligned using FFAS03 (
6), a sensitive
profile–profile alignment program. The high scoring profile-based
alignments were then screened by aligning them structurally,
and only the alignments with a C-
RMSD of
1 Å were retained.
After this two-step screening process, we had a dataset of 1.25
x 10
5 fragment pairs. The fragments were derived without any
assumptions regarding their secondary structure content, an
‘agnostic’ approach; hence, ‘Fragnostic’.
We proceeded to implement a distance measure between folds,
fragment based fold similarity (FBFS), based on fragment sharing.
- Given n folds, indexed (1, ..., n).
- Each fold will have a set of fragments shared with other folds: (X1, X2, ..., Xn).
- Xi being the set of all fragment pairs which are shared in fold i. |Xi| is the number of those pairs.
- Xi,j is the set of all fragment pairs shared between fold i and fold j and |Xi,j| is a number of such pairs.
- FBFS is then defined as follows:
 | (1) |
Having FBFS as a distance measure,
we generated four weighted graphs, using fragment lengths of
5, 10, 15 and 20 residues. Each vertex represents a population
of PDB-SELECT25 proteins in a given fold. Two vertices may be
connected by a weighted edge, with the weight determined by
the FBFS score.
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IMPLEMENTATION
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The Fragnostic web tool lets the user examine the relationship
between fold populations, based on the graph representation
outlined above. The user enters a fragment length, an FBFS threshold
level and a number of shared fragments threshold level. The
latter was entered to correct a positive bias which may exist
in the case of folds with small populations. Fragnostic then
generates a graph. Each vertex is shown as a circle, color-coded
according to the SCOP class. The SCOP concise classification
scheme code (SCCS) is shown in the vertex. SCCS is a four-position
code assigned by SCOP to a family, with the first position (a
letter) denoting the class, the second the fold, the third the
superfamily and the fourth the family. Positions 2–4 of
the SCCS are numbers, e.g a.4.3.23. As each vertex is composed
of a population of proteins with a common fold, only the first
two positions of the SCCS are shown (a.4). Placing the cursor
over the vertex will show its fold's SCOP-assigned title. Two
vertices are connected by an edge if the FBFS score between
the two connected vertices is higher than the threshold provided
by the user.
Figure 1 shows a part of such a graph. Clicking
on a vertex will display a table showing the SCOP domains from
PDB-SELECT25 which belong to the vertex's fold. The table entry
is linked to a 3D model of that domain, viewed using the Rasmol
program (
7). The model is displayed as a cartoon, and the regions
which are covered by fragments shared with other folds are colored.
Colors range from blue to red, the ‘hotter’ (redder
in spectrum) the color, the more fragments are shared in that
region with other folds (
Figure 2). Using Rasmol—a simple
yet powerful protein visualization tool—the user can further
analyze the protein. The page is linked to the folds which are
connected to the current one and to their connecting edges (see
below). Clicking on an edge will produce a table of all the
fragment alignments making up this edge. Whenever so annotated,
a table entry will have Gene Ontology (GO) (
8) terms associated
with it, and/or Enzyme Commission (EC) classification number.
The GO terms were taken from the PDB to GO mapping provided
by The European Bioinformatics Institute (EBI). There may be
multiple mappings between the chains and GO terms. This is because
some protein chains have multiple functions, participate in
more than one metabolic pathway, or are found in more than one
cellular compartment. Care was taken, however, not to enter
two GO terms when one clearly subsumes the other in an ‘is-a’
relationship. Thus if the term ‘phosphodiesterase’
appears associated with a given chain, ‘esterase’
will not be mentioned.
View larger version (23K):
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[in a new window]
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Figure 1 Part of a Fragnostic graph for fragment length 10, FBFS threshold of 0.2 and number of fragment threshold of 1. Circles are the SCOP fold populations, color coded according to SCOP class. Red, all alpha; blue, all beta; orange, alpha/beta; green, alpha + beta; and purple, small.
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View larger version (52K):
[in this window]
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Figure 2 Coagulation factor X, light chain (PDB: 1FAX
[PDB]
:L), which belongs to the knottins SCOP fold. The non-white areas are composed of length-10 fragments, shared with other folds.
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CONCLUSIONS
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We present Fragnostic as novel method for walking through protein
structure space. Rather than replacing SCOP with a new classification,
it complements the existing classification by showing connections
between known SCOP folds. Fragnostic is a powerful tool for
revealing hidden inter-fold connections based on shared fragments.
Fragnostic is also suitable for confirming hypotheses of structural
or functional connections between proteins from different folds.
In the future, we aim to permit querying using any SCOP entry,
not only those in PDB-SELECT25. We are currently developing
a fragment-to-structure matching method, so that the fragments—or
rather a clustered library thereof—can be used as a structural
motif library. Fragnostic was written using Zope (zope.org)
for web content management and GraphViz (AT&T Laboratories)
for displaying the graphs. The fragment dataset and associated
information were generated using Biopython (biopython.org) and
are maintained in a MySQL (MySQL AB) database.
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ACKNOWLEDGEMENTS
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We thank Drs Yuzhen Ye and Ana Rojas for providing invaluable
advice for the design of the Fragnostic site. We thank Mr Bruce
Worcester for his careful reading of this manuscript. This study
was supported by NIH Grant P01GM63208-02. Funding to pay the
Open Access publication charges for this article was provided
by NIH Grant P01GM63208-02.
Conflict of interest statement. None declared.
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