Nucleic Acids Research Advance Access originally published online on October 29, 2008
Nucleic Acids Research 2009 37(Database issue):D636-D641; doi:10.1093/nar/gkn839
Nucleic Acids Research, 2009, Vol. 37, Database issue D636-D641
© 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.
Update of KDBI: Kinetic Data of Bio-molecular Interaction database
Pankaj Kumar1,
B. C. Han1,
Z. Shi1,
J. Jia1,
Y. P. Wang2,
Y. T. Zhang2,
L. Liang2,
Q. F. Liu2,
Z. L. Ji2 and
Y. Z. Chen1,*
1Bioinformatics and Drug Design Group, Centre for Computational Science and Engineering, National University of Singapore, Blk S16, Level 8, 3 Science Drive 2, Singapore 117543 and 2Bioinformatics Research Group, School of Life Sciences, Xiamen University, Xiamen 361005, FuJian Province, P. R. China
*To whom correspondence should be addressed. Tel: +65 6516 6877; Fax: +65 6774 6756; Email: phacyz{at}nus.edu.sg
Received September 15, 2008. Revised October 10, 2008. Accepted October 14, 2008.
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ABSTRACT
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Knowledge of the kinetics of biomolecular interactions is important
for facilitating the study of cellular processes and underlying
molecular events, and is essential for quantitative study and
simulation of biological systems. Kinetic Data of Bio-molecular
Interaction database (KDBI) has been developed to provide information
about experimentally determined kinetic data of protein–protein,
protein–nucleic acid, protein–ligand, nucleic acid–ligand
binding or reaction events described in the literature. To accommodate
increasing demand for studying and simulating biological systems,
numerous improvements and updates have been made to KDBI, including
new ways to access data by pathway and molecule names, data
file in System Biology Markup Language format, more efficient
search engine, access to published parameter sets of simulation
models of 63 pathways, and 2.3-fold increase of data (19 263
entries of 10 532 distinctive biomolecular binding and 11 954
interaction events, involving 2635 proteins/protein complexes,
847 nucleic acids, 1603 small molecules and 45 multi-step processes).
KDBI is publically available at
http://bidd.nus.edu.sg/group/kdbi/kdbi.asp.
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INTRODUCTION
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Biomolecular interactions, via individual and network actions,
play fundamental roles in biological, disease and therapeutic
processes (
1–4). Extensive experimental and computational
studies have significantly advanced our understanding of the
characteristics, organization, evolution and complexity of biomolecular
interaction networks in biological systems (
5–8), and
enabled the generation of genome-scale protein–protein
interactions and the development prediction tools (
6,
7,
9–12).
Many databases have been developed for providing information about biomolecular interactions [e.g. MIPS (13), DIP (14), BIND (15), Biocyc (16), MINT (17), Biomodels (18), STRING (19) and IntAct (20)], and biological networks and pathways [KEGG (21), BioGRID (22), NetworKIN (23), STITCH (24), DOMINE (25), CellCircuits (26), Reactome (27) and enzyme reactions (28)].
In view that quantitative as well as mechanistic understanding of biomolecular interactions is important for exploration and engineering of biological networks and for the development of novel therapeutics to combat diseases (29,30), kinetic data of biomolecular interactions have been provided in some databases. For instance, BRENDA (31) and SABIO-RK (32) provide kinetic constants of enzymatic activities, DOQCS contains kinetic parameters of simulation models of cellular signaling derived from experimental and other sources (33). To complement these databases for providing the kinetic data not yet covered by other databases, we have developed the Kinetic Data of Bio-molecular Interactions database [KDBI; (34)] to provide experimentally measured kinetic data for protein–protein, protein–nucleic acid and protein–small molecule interactions aimed at facilitating mechanistic investigation, quantitative study and simulation of cellular processes and events (31–33,35–39). Kinetic data in KDBI have been manually collected from literatures, a substantial percentage of which are not yet available in other databases (e.g. some protein–protein interactions in thrombin, translation initiation, DNA repair, and ion transport pathways, and individual protein–nucleic acid interactions).
In the updated KDBI, apart from 2.3-fold increase of experimental kinetic data, we added four new features. The first is the access of KDBI entries via the list of nucleic acid and pathway names. The second is the inclusion of literature-reported kinetic parameter sets of 63 pathway simulation models (35–44) for facilitating the applications, assessments and further development of these pathway models. The third is the facility for collectively accessing the available kinetic data of multi-step processes (e.g. metabolism and pathway segments) collected in KDBI. The fourth is the availability of SBML (45) files for all records of the kinetic parameter sets of pathway simulation models for facilitating the use of the relevant data in such software tools as Celldesigner (46), Copasi (47), cPath (48), PaVESy (49) and SBMLeditor (50).
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EXPERIMENTAL KINETIC DATA AND ACCESS
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Additional sets of the experimentally determined kinetic data
of biomolecular interactions were collected from published literatures.
Compared to the last version of KDBI, the number of entries
in the updated KDBI is increased by 2.3-fold to 19 263, which
include 2635 protein–protein, 1711 protein–nucleic
acid, 11 873 protein–small molecule and 1995 nucleic acid–small
molecule interactions. Each entry provides detailed description
about binding or reaction event, participating molecules, binding
or reaction equation, kinetic data and related references. As
shown in
Figures 1–3
, kinetic data for protein–protein,
small molecule–nucleic acid and protein–small molecule
interactions are provided in terms of one or a combination of
kinetic quantities as given in the literature of a particular
event. These quantities include association/dissociation rate
constant, on/off rate constant, first/second/third/ ... order
rate constant, catalytic rate constant, equilibrium association/dissociation
constant, inhibition constant, and binding affinity constant,
IC50, etc. and experimental conditions (pH value and temperature).
View larger version (62K):
[in this window]
[in a new window]
[Download PowerPoint slide]
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Figure 1. Experimental kinetic data page showing protein–protein interaction. This page provides kinetic data and reaction equation (while available) as well as the name of participating molecules and description of event.
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View larger version (62K):
[in this window]
[in a new window]
[Download PowerPoint slide]
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Figure 2. Experimental kinetic data page showing small molecule–nucleic acid interaction. This page provides kinetic data and reaction equation (while available) as well as the name of participating molecules and description of event.
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View larger version (49K):
[in this window]
[in a new window]
[Download PowerPoint slide]
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Figure 3. Experimental kinetic data page showing protein–small molecule interaction. This page provides kinetic data and reaction equation (while available) as well as the name of participating molecules and description of event.
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These data can be accessed via input of names of molecules and
bio-events (association, dissociation, complex formation, electron
transfer, inhibition, etc.), and via selection of pathway and
protein name from the pathway list and protein list fields in
KDBI webpage. The kinetic data of an event are searchable by
several methods. One method is via the name of participating
molecules (protein, nucleic acid, small peptide, ligand or ion)
or pathway involved in an event. In some events described in
the literature, a participating entity is an unidentified molecule
located in the membrane of a cell or on the surface of a virus.
In these entries, only the name of the cell or virus is given.
An entry can also be searched through a Swiss-Prot AC number
for a protein or the CAS number for a small molecule ligand.
Moreover, keyword-based text search is also supported. To facilitate
convenient access of relevant data, partial lists of proteins
and nucleic acid are provided. Searches involving combination
of these methods or selection fields are also supported.
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PARAMETER SETS OF PATHWAY SIMULATION MODELS
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As part of the efforts for facilitating the understanding and
quantitative analysis of complex biological processes and network
responses, mathematical simulation models of various pathways
have been developed and extensively used for studying and quantitative
understanding of signaling dynamics (
35–39), signal-specific
sensing (
40) and discrimination (
44), feedback regulations and
cross-talks (
42,
43), and receptor cross-activation (
41) and
internalization (
42). These mathematical models typically use
ordinary differential equations (ODEs) to describe the temporal
dynamic behavior of molecular species in the pathway. The kinetic
rate constants of protein–protein, protein–small
molecule, protein–nucleic acid and other interactions
(e.g. binding association rate
Kf, binding dissociation rate
Kb, reaction rate
K, reaction turnover rate
Kcat, Michaelis–Menten
constant
Km) are needed to establish these ODEs, which have
been primarily generated by combinations of experimental data,
computed theoretical values and empirically fitted values computational
(
39–44). To facilitate further applications, developments
and assessments of the published pathway models, we collected
and included in KDBI the parameter sets of 63 published ODE-based
models, which can be accessed from the pathway list in the ‘Pathway
Simulation Parameters’ field in KDBI webpage. Moreover,
we added kinetic data type to every entry to clearly distinguish
its original source (experimental or simulation model). In particular,
for the kinetic data of a simulation model that have been obtained
from other publications, cross-reference to the original source
is provided. A typical search result is shown in
Figure 4.
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KINETIC DATA FOR MULTI-STEP PROCESSES
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Some published studies provide information about the experimental
kinetic data for multiple components of multi-step processes
(
51–53). Examples of these processes include RNA binding
activity to translation initiation factors eIF4G, 70-kDa heat
shock protein polymerization, control of platelet function by
cyclic AMP, GroEL interaction with conformational states of
horse cytochrome c, intermolecular catalysis by hairpin ribozymes,
antisense RNA interaction with its complimentary RNA and nucleotide
binding to actin. To facilitate the development of pathway simulation
models based on these building blocks, we provided direct access
to the collection of the kinetic data for each of these processes,
which can be accessed via a separate search field ‘Multi-step
processes’ in KDBI webpage. A typical search result is
shown in
Figure 5.
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KINETIC DATA FILES IN THE SYSTEMS BIOLOGY MARKUP LANGUAGE FORMAT
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Systems Biology Markup Language (SBML) has been developed as
a free, open and XML-based format for representing biochemical
reaction networks, and it is a software-independent language
for describing models common to computational biology research,
including cell signaling pathways, metabolic pathways, gene
regulation and others (
54). Many pathway simulation and analysis
software tools have built-in SBML compatibility features to
allow the input, manipulation, simulation and analysis of different
pathway models and parameters (
45,
54–58). To facilitate
the input of the pathway parameter sets into these software
tools, we created the SBML file for the parameter sets of all
63 pathway simulation models included in KDBI, which can be
downloaded via the link provided on the top of the page that
displays the relevant kinetic data. SBML file for the user-selected
kinetic data can be dynamically generated and exported by clicking
the selected entries and then the SBML file export button.
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REMARKS
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The updated version of KDBI is intended to be a more useful
resource for convenient access of available biomolecular kinetic
data to complement other biomolecular interaction and pathway
databases in facilitating quantitative studies of biomolecular
interactions and networks. New technologies have been developed
in employing surface plasmon resonance technology for deriving
real-time dynamics and kinetic data (
59), and in using protein
microarrays (
60) and solution NMR spectroscopy (
61) for monitoring
and characterizing biomolecular interactions. Moreover, new
experimental designs of the well-established technologies such
as isothermal titration calorimetry allow the measurement and
estimate of previously inaccessible kinetic parameters (
62).
Resources for collecting and accessing the increasing amount
of kinetic data can better serve the need for mechanistic investigation,
quantitative study and simulation of biological processes and
events.
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FUNDING
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Funding for open access charge: New Century Excellent Talents
in University (NCET) of MOE, China; grant (#30873159) from the
National Natural Science Foundation of China (NSFC).
Conflict of interest statement. None declared.
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ABSTRACT
INTRODUCTION
