Nucleic Acids Research Advance Access published online on May 23, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn326
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Domain Hierarchy and closed Loops (DHcL): a server for exploring hierarchy of protein domain structure
Grzegorz Koczyk1,2 and
Igor N. Berezovsky1,*
1Computational Biology Unit, Bergen Center for Computational Science, University of Bergen, Bergen 5008, Norway and 2Institute of Plant Genetics, Polish Academy of Sciences, Strzeszy
ska 34, 60-479 Pozna, Poland
*To whom correspondence should be addressed. Tel: +47 55 58 47 12; Fax: +47 55 58 42 95; Email: igor.berezovsky{at}bccs.uib.no
Received February 11, 2008. Revised April 24, 2008. Accepted May 7, 2008.
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ABSTRACT
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Domain hierarchy and closed loops (DHcL) (
http://sitron.bccs.uib.no/dhcl/)
is a web server that delineates energy hierarchy of protein
domain structure and detects domains at different levels of
this hierarchy. The server also identifies closed loops and
van der Waals locks, which constitute a structural basis for
the protein domain hierarchy. The DHcL can be a useful tool
for an express analysis of protein structures and their alternative
domain decompositions. The user submits a PDB identifier(s)
or uploads a 3D protein structure in a PDB format. The results
of the analysis are the location of domains at different levels
of hierarchy, closed loops, van der Waals locks and their interactive
visualization. The server maintains a regularly updated database
of domains, closed loop and van der Waals locks for all X-ray
structures in PDB. DHcL server is available at:
http://sitron.bccs.uib.no/dhcl.
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INTRODUCTION
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Interest in the connection between protein structure and its
stability and function has a long history starting from the
Svedberg's ‘multiplicity hypothesis’ (
1). The limited
proteolysis of proteins (
2) was the next step towards an invention
of the concept of protein globule as conglomerate of domains:
stable, semi-independent and functionally distinct parts (
3).
Eventually, domain decomposition became a routine in the analysis
of newly crystallized proteins and several manual and automatic
methods were developed during last 20 years (
4). While the human
experts disagree in
10% of cases, the automatic methods can
not reach even this level of performance (
5). Most of the current
domain assignments are based on structural characteristics,
such as C
–C
distance maps, the decrease in accessible
surface area, the number of intra-/inter-domain contacts (
6)
all of which are used to estimate compactness of the structure.
Compactness-based approaches disregard, however, physical, evolutionary
and functional origins of domains. Different physical factors
govern domain formation and stabilizing effect of some of them
depends on the factors connected with alteration of charge distributions
(
7). Evolution and protein function contribute their own specificity
in domain definition (
8).
A hierarchical approach to domain decomposition employs van der Waals model of domains and polymer nature of polypeptide chains, and results in alternative domain decompositions at different levels of energy hierarchy (6,9). To explore energy hierarchy of protein domain structure, it is necessary to start from the analysis of a distribution of van der Waals interaction in a protein globule for the following reasons. Van der Waals interactions is the only energy term for which analytical approximation using distribution of the electron density is possible (10), contrary to other non-bonded interactions (such as hydrogen bonds, ion pairs) stabilizing protein structure. Electrostatic interactions and hydrogen bonds can be shielded by water and counter ions, they can even be a cause of structure destabilization processes as a consequence of variations of pH, hydration or other factors of the environment (7). On the contrary, van der Waals interactions are not shielded at all and occur in every pair of atoms in the structure. It was theoretically shown long before the first protein structure was solved that van der Waals contacts between hydrophobic side chains in the protein core ‘must play a decisive role in the processes of the formation of a globula and in the determination of its final configuration’ (11). The polymer nature of the polypeptide chain returns is another aspect of protein physics invoked in our approach. It was discovered that there is a common basic element of protein structure (12) closed loops (returns of the protein backbone) of nearly standard size 25–30 amino acid residues. It was further shown that closed loops also play a role of elementary units of protein domains (9). The domains consist of one to several such loops, and variety of domain decompositions at different levels of energy hierarchy is a result of regrouping of closed loops (9).
This work presents an automated server, which provides a fast analysis of the hierarchy of protein domain structure, outputs domain decompositions at different levels of this hierarchy and detects closed loops and van der Waals locks. The server helps to analyze alteration of the domain structure and conformational changes. The hierarchical approach to domain decomposition used in the server was recognized as ‘a logical reconciliatory approach that allows the user to choose appropriate level of resolution’ in the recent analysis of domain assignment methods (8).
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IMPLEMENTATION
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Domain structure and its hierarchy
Figure 1 shows major steps in the analysis of the domain hierarchy
and the comparison of the server output with those of other
methods for the maltogenic amylase (1sma, chain A,
Figure 1A).
First, van der Waals interaction energies are calculated for
contacting atoms, which belong to amino acids separated by at
least two residues along the polypeptide chain. Only the contact
distances between 2.5 and 5.0 Å are considered, the Lennard-Jones
6–12 potential and the standard Scheraga parameters for
different atom types are used (
6).
Figure 1B contains a van
der Waals ‘energy walk’, where every point of the
curve is an interaction energy between parts of the globule
separated by a given amino acid residue. Thus, van der Waals
interaction energy between parts of the native globule can be
determined, and its minimal value (
E0) can be found (
Figure 1B).
Second, ‘energy barriers’ 0.3
E0 (
Figure 1B) 0.25
E0,
0.2
E0, 0.15
E0, 0.1
E0, 0.05
E0, are set according to the value
of
E0 (the lowest minimum) on the initial curve. Third, for
a given energy barrier maxima and minima on the van der Waals
energy curve are analyzed. Any maximum on the curve is considered
to be a point of structural separation if the differences between
this maximum and neighboring deep minima exceed the value of
a chosen barrier (
Figure 1B, note that there can be several
minima between maximum and minimum, which satisfy the barrier's
condition). Points of structural separation split a structure
into number of segments corresponding to the level of energy
barrier (
Figure 1C). Fourth, for each level of energy barrier
internal energies of segments (total interaction energy between
residues within one and the same segment) and external energies
(interaction energy between residues of a particular segment
and residues of other segments) are analyzed in order to identify
domain structure at this level. If the internal energy of the
segment is at least 2.5 times lower than the external one the
segment is defined as an independent domain. Any two segments
with their internal energies 2.5–1.5 times lower than
their external energies are combined in one independent domain
if one of the following conditions is satisfied: (i) the interaction
energy between these segments is higher than the rest of external
interaction energies in each segment, or (ii) more than 0.7
of the external interaction energy of one segment pertains to
the interaction with a second segment. Any segment with the
internal interaction energy less than 1.5 times lower than the
external one is joined with domains/segments with which it has
the lowest interaction energy. The procedure results in domains
determined for each energy barrier, which delineates energy
hierarchy of domain structure for a given protein (
Figure 1D).
The current implementation of current Domain Hierarchy and closed
Loops (DHcL) delineates a domain hierarchy for six energy levels
(0.3
E0, 0.25
E0, 0.2
E0, 0.15
E0, 0.1
E0 and 0.05
E0). Additionally,
if any large (more than 150 residues) segments exist at 0.05
E0 level, the domain structure is also calculated for 0.02
E0 level.
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Figure 1. The hierarchy of domain structure in maltogenic amylase (1smaA). (A) The on-plane projection of maltogenic amylase; (B) the initial van der Waals energy curve; (C) decomposition into segments at 0.3E0, 0.25E0 and 0.05E0 energy barrier levels; (D) domain structures obtained at 0.3E0, 0.25E0 and 0.05E0 energy barrier levels; (E) Domain Parser, NCBI and PDP domain decomposition match best to the decompositions at 0.3E0, 0.25E0 and 0.05E0 energy barrier levels in DHcL, respectively.
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We found alternative domain decompositions at different levels
of the energy barrier (hierarchy of domain structure) in many
analyzed proteins. Alternatively, some of the structures yield
one and the same domain decomposition for all energy levels.
The latter case raises a question about comparison of domain
decomposition obtained by our approach with other methods. We
used our results obtained at the intermediate level of the energy
barrier (0.2
E0) for the comparison with domain decompositions
in the Balanced_Domain_Benchmark_2 [(
8),
http://pdomains.sdsc.edu/dataset.php].
The histogram in
Figure 2 shows that DHcL completely agrees
in most of the cases with PDP approach (
13) and Experts [a consensus
between domain assignments, which involves human expertise,
CATH (
14), SCOP (
15) and authors (
8)].
Supplementary Table 1 contains a complete data on domain decompositions at all levels
of energy hierarchy. It is important to note, that if there
is a hierarchy of domain structure with alternative domain decompositions
at different levels, DHcL approach usually reconciles different
algorithms of domain partitioning. Examples of structures (in
addition to 1sma in
Figure 1), where DHcL results at different
level of energy hierarchy are similar to the domain decompositions
obtained by distinct methods are given in the
Supplementary Figures [selection of structures was done based on the Figures 5–10
in ref. (
8)].
Closed loops
Figure 3 shows an example of closed loop decomposition for maltogenic
amylase (1sma, chain A). The closed loops [continuous returns
of the protein chain trajectory (
12)] are identified in the
following five-step procedure. First, C
–C
distances for
all pairs of residues separated in the protein chain by 15–45
residues are measured. Second, returns of the trajectory with
C
–C
distances between their ends within the 2.5–12Å
interval are selected for further consideration and enumerated.
Third step is a mapping of closed loops. It starts from the
tightest loops (i.e. returns with the shortest C
–C
distances
between their ends), and at each iteration sequence region corresponding
to the mapped loop is excluded from further consideration. If
there is a partial overlap between two loops (more than five
amino acid residues) the tighter one is accepted. The mapping
ends when the whole sequence is covered by a unique set of tightest
loops, and no new loops can be added to improve the sequence's
total coverage or all 15–45 residues-long loops with C
–C
distances up to 12 Å were considered. Fourth, large loops
(more than 39 residues) with surrounding linker regions (noncovered
by closed loops parts of the chain) are reconsidered. The procedure
checks if combination of relatively tight (C
–C
distance
up to 4–5Å) shorter loops (up to 30 residues) can
provide better coverage of the sequence. Fifth, adjustment of
terminal loops is performed. N- and C-terminal loops are extended
providing better coverage if: (i) they were not modified in
the previous step and (ii) C
–C
distance will not exceed
1.15 of the original one. The maximal overlap between loops
allowed in all steps of the procedure is five residues.
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Figure 3. Closed loops in maltogenic amylase, 1smaA. The coloring, according to 0.05 domain hierarchy level, demonstrates the correspondence between loops and domains at this hierarchy level. Loops are (starting from top yellow—clockwise): (271–298), (324–353), (356–374), (6–29), (38–58), (83–116), (545–572), (532–546), (520–535), (508–524), (462–483), (426–466), (380–420), (146–177), (175–198), (200–216), (212–244).
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Van der Waals locks
The van der Waals lock is defined as a pair of 3- to 5-residue
long segments, which have maximal number of contacts between
strongly interacting parts of the structures (minimum 100 contact
per residue) they belong to. Segments forming van der Waals
lock are separated from each other by at least five consecutive
residues, which weakly interact with the rest of the structure
(less than 40 contacts per residue). Below is the step by step
procedure for determining a van der Waals lock. First, a matrix
of residue–residue van der Waals contacts [all atom model,
distance: 2.5-5Å; (
16)] is calculated. Continuous fragments
of strongly interacting residues are extracted from the matrix
using a minimum cutoff of 100 contacts per residue. A stretch
of at least five residues scoring below the threshold (40 contacts
per residues) is required to separate neighboring segments.
The van der Waals lock is defined for each segment as continuous
3–5 residues, which make maximal number of contacts with
continuous 3–5 residues in one of the other segments.
The length of the lock (3, 4 or 5 residues) is chosen according
to the maximal average number of contacts per pair of residues
in the lock.
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SERVER: INPUT, OUTPUT AND OPTIONS
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As an input, the server accepts one or several PDB identifiers
(separate protein chain can be requested, e.g. 1abcA), a structure
file (in PDB format), or the content of the file in PDB format
(as pasted text). If user provides a list of PDB IDs (or one
ID), the server checks its internal database which contains
precalculated and regularly updated data for all X-ray structures
in PDB. If DHcL database does not contain data on query structure
and user provided valid a PDB identifier, the server provides
a link to RCSB PDB page for manual downloading and submission
of the structure. If user wants to analyze a structure which
is not in DHcL repository yet (by uploading file or pasting
its content), the query structure is sent to the processing
queue. The page with a task identifier and a status of the job
is returned to the user. User can use the job identifier to
check the status of a current job (waiting, processing or failed
with errors) or to access pages with results and their visualization
when computations are completed. User is also suggested to provide
and e-mail address, in order to be notified upon the job completion.
It is specifically recommended to use an e-mail option for large
structures with more than 30 000 atoms.
Figure 4 presents typical
output of the server. If the query structure has several chains,
the report is provided for every chain separately. There are
two summary pages for every chain in the structure. User can
switch between these pages using links ‘domain hierarchy
& closed loops’ and ‘vdW locks’. From
any of summary pages user can also return to the main page using
a link ‘return to main’. The first page shows the
domain hierarchy and closed loops in the whole structure and
individual domains (
Figure 4A). Cartoon and ribbon-like modes
are available for showing domains (accessible by clicking buttons
‘Cartoon’ and ‘Trace’,
Figure 4A). The
domain structure at a given level of hierarchy (buttons in the
‘Domain hierarchy’ section) or closed loops (buttons
in the ‘Loops’ section) can be displayed. Filter
options are provided to highlight the decomposition of a particular
domain into loops (‘Loops’ button next to the domain
coordinates) or hide other domains at a given hierarchy level
(‘Hide’ button). The color scheme for individual
structural domains/loops is indicated in the ‘X’
signs next to the coordinates of the corresponding domain/loop.
There are also links to relevant pages in CATH (
14) and SCOP
(
15) databases, in case of structure files valid PDB identifiers.
The second summary page shows primary and secondary van der
Waals locks and their location in closed loops (
Figure 4B).
Primary (located within the loop ends ±5 residues) and
secondary (stabilizing contact between different loops and/or
linker regions) locks are shown separately in the sections ‘Primary
locks’ and ‘Secondary locks’. For each lock,
the report lists loops with ends within five residues from the
lock. In this section, the entire structure of the protein chain
is visualized as ribbon-like trace, and structure of the lock
can be displayed in wireframe or filled spheres representation
using corresponding buttons. The locks are colored dark orange,
and the color scheme for the closed loops which contain these
locks is given by ‘X’ signs near the loop coordinates.
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Figure 4. Overview of the DHcL server for domain decomposition at different levels of energy hierarchy and loop-n-lock structure. (A) Domain decomposition at different levels of hierarchy; (B) primary and secondary van der Waals locks.
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SERVER: IMPLEMENTATION
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The server is implemented in Python, using the open-source Django
web framework (
http://www.djangoproject.com). Computationally
intensive parts of domain hierarchy calculation are written
in C++. BioPDB package from BioPython (
http://biopython.org)
is used to parse PDB structures (
17).
Java-based Jmol (http://jmol.sourceforge.net/) software package is used as molecule viewer for visualizing domains at different levels of energy hierarchy, closed loops and van der Waals locks. The example reports shown in Figure 4 (7tim, a triosephosphate isomerase TIM barrel protein) can be also accessed and interacted with via the following link: http://sitron.bccs.uib.no/dhcl/database/single/domains_loops/7tim/chain/A/.
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DATABASE: STATISTICS OF THE DOMAIN ASSIGNMENTS
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The current internal database of X-ray structures contains results
for total 98 403 chains in 40 315 PDB files.
Table 1 shows that
the same structure partitioning was reached at different levels
of energy hierarchy for 35 040 chains, two alternatives were
observed for 31 170 chains, three variants of partitioning were
found for 21 089 chains, etc. The numbers of protein chains
decomposed into one, two or more domains at different level
of the energy barrier are shown in
Table 2. Comparison with
other methods was done for the energy barrier level 0.2
E0 using
the following formula adapted from ref. (
9):
where
is the number of residues assigned to the same domain both by
our program and another method or author definition,
Ntot is
the total number of residues in the protein chain,
M is the
number of domains under comparison. If the number of domains
assigned by our method is not equal to the number of domains
assigned by others, then
M is the maximal number of domains
in the compared assignments.
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Table 1. Number of protein chains with different numbers of domain decomposition at different levels of energy hierarchy
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Table 2. Statistics of protein chains with different number of domains at 0.3E0–0.05E0 levels of the energy barrier
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CONCLUSIONS AND OUTLOOK
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The energy hierarchy of domains structure establishes a framework
for the analysis of a relationship between structurally, functionally
and evolutionary distinct parts of protein molecules. It is
important to note that the hierarchical approach to domain decomposition
is a ‘reconciliatory’ one (
8), because it eliminates
contradiction between the results of different methods for domain
decomposition (
Figure 1D and E).
The results of the analysis provided by DHcL server can be used by the researches in the fields as different as biophysics, enzymology, structural biology, bioinformatics, etc. In particular, DHcL output will help for the detecting cooperative units in protein microcalorimetry (18), and for the predicting conformational changes in allosteric regulation and protein function.
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SUPPLEMENTARY DATA
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Supplementary data are available at NAR Online.
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ACKNOWLEDGEMENTS
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This work was supported by the Research Council of Norway through
its allocation to the Bioinformatics Technology Platform under
the functional genomics program FUGE. Funding to pay the Open
Access publication charges for this article was provided by
the FUGE project.
Conflict of interest statement. None declared.
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ABSTRACT
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