Nucleic Acids Research Advance Access originally published online on October 8, 2008
Nucleic Acids Research 2009 37(Database issue):D201-D204; doi:10.1093/nar/gkn672
Nucleic Acids Research, 2009, Vol. 37, Database issue D201-D204
© 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.
TMFunction: database for functional residues in membrane proteins
M. Michael Gromiha1,*,
Yukimitsu Yabuki1,
M. Xavier Suresh1,
A. Mary Thangakani2,
Makiko Suwa1 and
Kazuhiko Fukui1
1Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), AIST Tokyo Waterfront Bio-IT Research Building, 2-42 Aomi, Koto-ku, Tokyo 135-0064 and 2Advanced Technology Inc., Tokyo, Japan
*To whom correspondence should be addressed. Tel: +81 3 3599 8046; Fax: +81 3 3599 8081; Email: michael-gromiha{at}aist.go.jp
Received August 13, 2008. Revised September 22, 2008. Accepted September 22, 2008.
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ABSTRACT
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We have developed the database TMFunction, which is a collection
of more than 2900 experimentally observed functional residues
in membrane proteins. Each entry includes the numerical values
for the parameters IC50 (measure of the effectiveness of a compound
in inhibiting biological function),
Vmax (maximal velocity of
transport), relative activity of mutants with respect to wild-type
protein, binding affinity, dissociation constant, etc., which
are important for understanding the sequence–structure–function
relationship of membrane proteins. In addition, we have provided
information about name and source of the protein, Uniprot and
Protein Data Bank codes, mutational and literature information.
Furthermore, TMFunction is linked to related databases and other
resources. We have set up a web interface with different search
and display options so that users have the ability to get the
data in several ways. TMFunction is freely available at
http://tmbeta-genome.cbrc.jp/TMFunction/.
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INTRODUCTION
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Membrane proteins perform a diverse variety of functions and
are used as main drug targets of pharmaceutical agents. The
collection of information on potential amino acid residues for
the function of membrane proteins is important for understanding
the sequence–structure–function relationship of
membrane proteins as well as predicting the functional residues
from sequence/structure. Tusnady
et al. (
1) constructed a database
for transmembrane proteins, which covers the three-dimensional
structures of membrane proteins deposited in Protein Data Bank
(PDB) and information on membrane spanning
-helices and β-strands
obtained with the TMDET algorithm (
2). Saier
et al. (
3) developed
a comprehensive classification system for membrane transport
proteins known as the Transport Classification Database (TCDB).
Further, functional databases have been developed for G-protein-coupled
receptors (GPGRs), human seven transmembrane receptors,
Arabidopsis integral membrane proteins and so on (
4,
5). Edvardsen
et al. (
6) created a G-protein-coupled receptor mutant database, which
is mainly focused on different families of GPCRs. Mutational
databases have also been developed for the structure, function
and thermodynamics of proteins (
7,
8). On the other hand, several
methods have been proposed for discriminating transmembrane
-helical and β-strand proteins, predicting their membrane-spanning
segments, and functional classification of membrane proteins
(
9–16). In spite of these studies, there is no database
available for the broad collection of potential residues, which
are important for the functions of different classes of membrane
proteins including receptors, transporters, channel proteins,
etc. This information can be obtained from experimental studies
on membrane proteins that have reported the measured values
of several parameters for membrane protein function. The collection
of such data is important and necessary for analyzing and predicting
potentially important residues for practical applications.
In this work, we have developed a database, TMFunction, which is a collection of more than 2900 experimental data about important amino acid residues in membrane proteins, reported in the literature. It has information about functionally important residues, numerical values for the parameters IC50, Vmax, activity, affinity, etc., along with sequence and structure information for the protein, mutational and literature information. This database will help in understanding the relationship between amino acid sequences/structures and functions of membrane proteins. We have developed a WWW interface to facilitate searching the database and displaying the results with different options.
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CONTENTS OF THE DATABASE
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Each entry in the database includes the following information:
Sequence and structure information: name and source of the protein, Uniprot (17) and PDB (18) codes, type of the integral membrane protein (-helical or β-strand), mutational details (single, double or wild-type; mutation has been identified with mutated residue, residue number and mutant residue; e.g. A102V) and location of mutants.
Functional information: factors that are mainly affected by the mutation of amino acid residues in membrane proteins, such as relative activity of mutants, affinity for binding, channel, drug, glycosylation, membrane insertion, cellular signaling, membrane translocation, transport, etc.
Functional data: numerical values for affinity (%), Bmax, IC50, drug sensitivity, Kd, Km, Vmax, uptake (%), etc.
Experimental methods and conditions: measurement, method and the ligand used for the control data.
Literature information: keywords, reference, authors and remarks.
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DATABASE STATISTICS
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The first release of TMFunction contains 2907 entries from 83
different proteins, which perform 29 diverse functions. It has
data for 2092 single mutants, 580 multiple mutants and 273 wild-types.
The majority of the data concerns transmembrane helical proteins
(2760) followed by β-barrel membrane proteins (147). The
data are obtained from more than 100 scientific articles published
in 20 different journals.
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FEATURES OF TMFUNCTION
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TMFunction includes several features in the search and display
options as shown in
Figure 1, and as briefly explained subsequently:
- Retrieving data for a particular protein and/or source.
- Specifying the type of the mutant as single, multiple and/or wild-type.
- Selecting the function of the protein (transport) as well as the numerical value of the functional parameter (e.g. IC50).
- Mentioning the type of the protein.
- Extracting data by authors, publication year and keywords.
- Downloading entire data.
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Figure 1. An example of searching conditions, display options and results of TMFunction: (a) main menu for the search options in TMFunction. The items function (drug) and single mutants are selected for search as indicated by arrows; (b) display options in TMFunction. We have selected entry, protein, Uniprot ID, mutation, parameter, data, function and PMID to show in the output; (c) part of the results obtained from TMFunction.
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Detailed tutorials describing the usage of TMFunction are available
at the home page. For example, the data obtained for the function
‘drug’ and single mutants is shown in
Figure 1a.
The terms: entry, protein, Uniprot ID, mutation, parameter,
data, function, experiments and Pubmed ID have been selected
for displaying the results (
Figure 1b).
Figure 1c shows the
final results obtained with the search conditions and display
options.
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LINKS TO OTHER DATABASES
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Each entry in TMFunction is linked to Uniprot ID (
http://www.uniprot.org/)
and PDB code (
http://www.rcsb.org) to obtain the sequence and
structure information directly. The references for all data
are directly connected to the PUBMED literature database of
NCBI (
http://www.ncbi.nlm.nih.gov/pubmed/). Further, we have
provided links to several related databases and web servers
including sequences and structures, functions and genomes, transmembrane
helix and strand predictions (
http://tmbeta-genome.cbrc.jp/TMFunction/DBlinkspage.html).
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AVAILABILITY AND CITATION OF TMFUNCTION
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The database can be freely accessible at
http://tmbeta-genome.cbrc.jp/TMFunction/.
If this database is used as a tool in your published research
work, please cite this article including the URL. Suggestions
and comments are welcome and should be sent to
michael-gromiha{at}aist.go.jp.
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FUNDING
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The support from Computational Biology Research Center (CBRC)
and National Institute of Advanced Industrial Science and Technology
(AIST) is gratefully acknowledged. Funding for open access charge:
Computational Biology Research Center (CBRC).
Conflict of interest statement: None declared.
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ACKNOWLEDGEMENT
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We thank Dr Martin Frith for critical reading of the manuscript.
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