Structural Databases of Biological
Macromolecules
Helen M Berman, Rutgers, The State University of New Jersey, New Brunswick,
New Jersey, USA
The Protein Data Bank began as an archive of the structural data available about known
biological macromolecules. The advances made in all technologies have been mirrored in
further development of the Protein Data Bank and in the structural, speciality and structural
characteristic databases that have also evolved.
Historical Background
In 1957, the first structure of a biological macromolecule
(myoglobin) was determined (Kendrew et al.,
1958). This was followed by the determinations of
several more key molecules, including hemoglobin
(Perutz et al., 1960), lysozyme (Blake et al., 1965) and
ribonuclease (Kartha et al., 1967; Wyckoff et al.,
1967). In 1971, small-molecule and protein crystallographers
from both sides of the Atlantic agreed to
establish a data bank of the protein structures being
determined. Its mission would be to collect, archive
and disseminate data on the three-dimensional
structures of biological macromolecules. Walter
Hamilton of the Brookhaven National Laboratory
and Olga Kennard of the Cambridge Structural
Database (CSD) collaborated to manage the Protein
Data Bank (PDB) resource (1971). Hamilton’s interest
was borne from his work on the high-resolution
determination of amino acid crystal structures and
from his visionary idea of setting up distributed
computing resources whereby every crystallographer
would have a graphics workstation on his/her desk
with full network access to powerful high-speed
computers. Kennard had founded the CSD in 1965
to create a database of organic and metal-organic
compounds studied by X-ray and neutron diffraction,
and was well experienced in managing structural data.
(See Crystallization of Nucleic Acids; Protein Structure.)
The PDB contained less than a dozen structures at
its inception, with a few more structures added each
year. The structures themselves were relatively small.
The PDB file format was simple, and it was relatively
easy to extract the structures from magnetic tape to
find out what you wanted to know about any
particular molecule.
In the 1980s, the improvements in the technology
required to do crystal structures began to evolve
rapidly. Now, two decades later, modern molecular
biology techniques have made it much more straightforward
to obtain large quantities of proteins. Crystallization
methods have emerged that allow investigators
to screen many different conditions using exceedingly
small amounts of material. Data collection methods
have improved at all levels. The lifetimes of crystals are
routinely extended by flash freezing. The radiation
sources are much more intense, especially with the
emergence of powerful synchrotron beam lines. Detectors
are much more sensitive and allow the very rapid
collection of arrays of reflections. Methods for phase
determination and refinement have improved. Indeed,
crystallography is now part of the armament of
techniques that is readily accessible to biologists.
As crystallographic methods continue to improve,
another method of structure determination has come
of age: nuclear magnetic resonance (NMR). This
method, which allows the determination of structures
in solution, is currently responsible for approximately
15% of the structures released in the PDB.
The improvements in technology have also made it
possible to determine the structures of very complex
molecules. Several structures of ribosomal subunits
(Moore, 2001), as well as the entire 70S ribosome
structure (Yusupov et al., 2001), have been deposited
in the PDB. During this same period, the structural
genomics initiative (2000) has begun with the goal of
determining thousands of structures in a highthroughput
mode. Thus, the PDB holdings will
continue to grow (Figure 1).
The level of activity in structural biology has made
it essential that the PDB use the most modern
technologies to collect, archive and disseminate data.
The PDB is an archival database, which contains
coordinates of biological macromolecules determined
using public funds as well as many from the private
sector. It also contains information about the methods
and materials used to determine those structures.
Other databases have emerged (Table 1) that extract
some of the information contained in the PDB and
Advanced article
Article contents
 Historical Background
 The Protein Data Bank
 Structural Databases
 Speciality Databases
 Databases of Structural Characteristics
 Challenges
doi: 10.1038/npg.els.0005252
Structural Databases of Biological Macromolecules
ENCYCLOPEDIA OF LIFE SCIENCES & 2005, John Wiley & Sons, Ltd. www.els.net 1
organize that information in different ways so as to
enable different types of query. These are value-added
databases, which serve the needs of particular users. In
this article we describe the PDB and some of these
other structural databases.
The Protein Data Bank
After 27 years at Brookhaven National Laboratory,
the PDB is now managed by the Research Collaboratory
of Structural Bioinformatics (RCSB) (Berman
et al., 2000). The RCSB is a consortium consisting of
three member groups: Rutgers, the State University of
New Jersey; the San Diego Supercomputer Center of
the University of California, San Diego; and the
National Institute of Standards and Technology. The
PDB collects information about biological macromolecular
structures and the methods used to determine
those structures. Coordinates, primary experimental
data, statistics about the structure determination and
refinement, information about the source, sequence
and chemistry of the molecule and the solution and/or
crystallization conditions are collected and assembled
using a software tool called the AutoDep Input Tool
(ADIT) (see Web Links). Annotation, checking and
validation of the data are carried out with a variety
of programs whose output is reviewed by skilled
annotation staff working in close collaboration with
the depositors of the data.
Once the data are fully checked and approved for
release, they are loaded into a series of databases. Two
different search engines can query the databases:
SearchLite and SearchFields. A rich set of reporting
options make it possible to access information about a
single molecule, compare it with other molecules, and
access other databases that contain information about
that molecule. Particular groups of macromolecules
can be selected according to their features so that a
variety of reports can be created. The PDB maintains
mirrors around the world, which provide the same
capabilities as the main RCSB site.
As of this writing there are more than 15 800
molecules in the PDB. The distribution of these data
is shown in Table 2.
Structural Databases
While the PDB focuses on individual structures, some
databases organize their data according to tertiary
structural characteristics. SCOP (a Structural Classification
of Proteins) classifies each structure in the
PDB according to family, superfamily, common fold and
class. Families are classified according to their sequence
similarities. Families with similar structure and
function belong to the same superfamily. Families and
0
1000
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Deposited structures for the year
Total available structures
Figure 1 Growth of the contents of the Protein Data Bank. The number of structures deposited each year is shown in gray, the total
number of structures available in black. This chart is regularly updated at http://www.rcsb.org/pdb/holdings.html.
Structural Databases of Biological Macromolecules
2
superfamilies with the same arrangement of secondary
structures, which are connected with one another in
the same way, have the same common fold. Class refers
to the types of secondary structures (all alpha, all beta,
alpha–beta, etc.). SCOP was one of the earliest
databases that attempted to integrate sequence,
structure and function information; it continues to
be a major resource in structural biology.
Table 1 Selected database resources for macromolecular structures
Archival database of biological macromolecules
Protein Data Bank (Berman et al., 2000; Bernstein et al., 1977) http://www.pdb.org/
Structural databases
3D ALI (a database of aligned protein
structures and related sequences)
(Pascarella and Argos, 1992)
http://www.embl-heidelberg.de/argos/ali/ali_info.html
CAMPASS (Sowdhamini et al., 1998) http://www-cryst.bioc.cam.ac.uk/campass/
CATH (Orengo et al., 1997) http://www.biochem.ucl.ac.uk/bsm/cath/
CSD (Allen et al., 1979) http://www.ccdc.cam.ac.uk/
FSSP (Holm and Sander, 1998) http://www2.ebi.ac.uk/dali/fssp/
HSSP (Dodge et al., 1998) http://www.sander.embl-heidelberg.de/hssp/
ISSD (Adzhubei et al., 1998) http://www.protein.bio.msu.su/issd/
Library of Protein Family Cores (LPFC) (Schmidt et al., 1997) http://WWW-SMI.Stanford.EDU/projects/helix/LPFC/
Molecular Modeling Database (Holm and Sander, 1994) http://www.ncbi.nlm.nih.gov/Structure/
SCOP (Murzin et al., 1995) http://scop.mrc-lmb.cam.ac.uk/scop/
Speciality databases
ENZYME database (Bairoch, 2000) http://www.expasy.ch/enzyme/
Enzyme Structures Database http://www.biochem.ucl.ac.uk/bsm/enzymes/
HIV Protease Database (Vondrasek et al., 1997) http://srdata.nist.gov/hivdb/
International Immunogenetics Database (IMGT) (Lefranc et al., 1998) http://imgt.cines.fr:8104/
Nucleic Acid Database (Berman et al., 1992) http://ndbserver.rutgers.edu/
Prolysis (protease and protease inhibitor web server) http://delphi.phys.univ-tours.fr/Prolysis/
Protein Kinase Resource (Smith et al., 1997) http://pkr.sdsc.edu/html/index.shtml
Structural characteristic databases
Biological Macromolecule Crystallization
Database (BMCD) (Gilliland, 1997)
http://wwwbmcd.nist.gov:8080/bmcd/bmcd.html
Dictionary of Interfaces in Proteins (DIP) http://www.drug-redesign.de/
ISOSTAR (Bruno et al., 1997) http://www.ccdc.cam.ac.uk/prods/isostar/
Molecular Movements Database (Gerstein and Krebs, 1998) http://bioinfo.mbb.yale.edu/MolMovDB/
OLDERADO (Kelley and Sutcliffe, 1997) http://neon.chem.le.ac.uk/olderado/
PDBSum (Laskowski et al., 1997) http://www.biochem.ucl.ac.uk/bsm/pdbsum/
PROCAT (Wallace et al., 1996) http://www.biochem.ucl.ac.uk/bsm/PROCAT/PROCAT.html
PROMISE (Degtyarenko et al., 1998) http://metallo.scripps.edu/PROMISE/
Protein Quaternary Structures (PQS) http://pqs.ebi.ac.uk/
ReLiBase (Receptor/ligand complexes database) (Hendlich et al., 2003) http://relibase.ccdc.cam.ac.uk/
TESS
Table 2 Protein Data Bank holdings (as of 14 August 2001)
Proteins, peptides
and viruses
Protein–nucleic acid
complexes Nucleic acids Carbohydrates Total
X-ray diffraction and other 11 893 569 579 14 13 055
NMR 1964 73 390 4 2431
Theoretical modeling 293 20 23 0 336
Total 14 150 662 992 18 15 822
Structural Databases of Biological Macromolecules
3
CATH provides another classification scheme
based on class (C), architecture (A), topology (T)
and homologous superfamilies (H). Class defines the
secondary structure content as in SCOP. Architecture
defines the description of the arrangement of these
secondary structures without consideration of the
connectivities. Topology is equivalent to fold in
SCOP. Finally, homologous superfamilies contain all
folds with a similar function. CATH has a systematic
classification system for all structures analogous to the
EC classification for enzyme function. The type of
research possible with this database is exemplified by
an analysis of all enzymes in which it was shown that
the topology of enzymes is more related to the ligands
bound than the enzyme EC class (Martin et al., 1998).
Speciality Databases
Another type of database that has proved invaluable
in research has been the speciality database. These
databases are curated by experts in the field and
provide information beyond the structures themselves.
These may include derived structural data, sequence
information and other biochemical information. An
example is the Protein Kinase Resource, which
provides not only structural but also functional and
pharmacological data about these key drug targets.
The same is true of the HIV Protease Database, which
has captured all the information about HIV protease
structures to be included in one place with the goal of
aiding drug development. The Nucleic Acid Database
(NDB) has provided a searchable resource about
nucleic acids. The Enzyme Structures Database
organizes all the enzyme structures in the PDB
according to the EC codes contained in the ENZYME
Data Bank and provides information about them. (See
DNA Structure.)
Databases of Structural
Characteristics
Databases of structural features contained within
macromolecules have also emerged. The Molecular
Movements Database provides information about the
possible motions of macromolecules by analyzing
the various structures of particular molecules.
OLDERADO (On Line Database of Ensemble Representatives
And Domains) provides a database of
structures for which there are several representatives,
such as an ensemble of NMR structures. The TESS
(Template Search and Superimposition) algorithm has
allowed for the creation of a database of active site
templates called PROCAT. This type of database will
become invaluable in the quest for relating structure to
function. PROMISE is a database that provides
information about the prosthetic centers and metal
ions in the active sites. ISOSTAR provides an
integrated view of the nonbonded interactions geometry
around ligands in proteins. PDBsum gives a
variety of carefully curated information about all the
structures in the PDB. The Dictionary of Interfaces in
Proteins (DIP) is a data bank of complementary
molecular surface patches and is meant to enable
molecular recognition research.
Challenges
The PDB is now much more than a repository of
coordinate data. To make this resource even more
useful, all the files need to be in a uniform format so
that the many new databases of derived information
can be easily constructed without having to first
clean the files. A project at the PDB is underway to
re-examine the archive to achieve this uniformity (Bhat
et al., 2001). The PDB will also integrate the validation
criteria that have been developed by a variety of
researchers (Wilson et al., 1998).
The various methods that have been developed for
classification (Gerstein and Levitt, 1998; Orengo and
Taylor, 1996) and structure comparison (Alexandrov
and Fischer, 1996; Gibrat et al., 1996; Holm and
Sander, 1996; Shindyalov and Bourne, 1998) will
continue to improve and their results incorporated
into the databases, as will methods to understand
macromolecular interactions with one another (Jones
and Thornton, 1997), with nucleic acids (Jones et al.,
1999) and with small molecule ligands (Wallace et al.,
1995).
The goal of being able to relate structure to function
will be facilitated by different types of database efforts.
Databases that assemble information about particular
protein families will be one avenue that will provide
this information. In these databases the coverage is
very narrow and deep, so that a truly full understanding
of a single class of proteins with known function is
possible. The lessons learned from these types of
resource will perhaps allow us to develop some general
principles about the relationships of structure and
function.
The structural genomics project is an outgrowth of
the various genome projects. Its goal is to determine
macromolecular structures on a genomic scale – the
discovery, analysis and dissemination of threedimensional
structures of biological macromolecules
representing the entire range of structural diversity
found in nature (see Web Links). The sequences being
targeted by many of these efforts are being stored in a
database (see Web Links). Once the anticipated large
volume of three-dimensional data is collected and
assembled, it will be critical to coordinate and to relate
Structural Databases of Biological Macromolecules
4
the structural and sequence data in order to create a
full picture of protein fold space.
While these efforts are ongoing, databases of
information about chemical and biological properties
of macromolecules and their complexes will provide
yet another avenue to understanding function.
With the large number of databases that have been
created, it is important to develop methods to query
across all of these databases in a seamless way. To help
in this effort, the RCSB has developed a standard
application interface for macromolecular data based
on the Common Object Request Broker Architecture
(Corba). The proposal was adopted by the Object
Management Group (OMB) in February 2001 (see
Web Links). This specification opens the door to more
seamless and specific access to PDB data. More
specifically, it provides a standard application programming
interface (API) that will allow direct access
by remote programs to the binary data structures of
the PDB. This and other similar initiatives will help to
ensure that the world of biology in silico will be readily
accessible.
Acknowledgements
Parts of this work have appeared in ‘The past and
future of structural databases’ by Helen M. Berman
(1999) Current Opinion in Biotechnology 10: 76–80. The
US National Science Foundation, the Department of
Energy and the National Institutes of Health
supported this work.
See also
Protein Databases
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Web Links
PDB Deposition Information. Links to the AutoDep Input Tool
(ADIT), AutoDep, and other deposition resources
http://www.pdb.org/
Second International Structural Genomics Meeting. NIGMS statement
on coordinate deposition, highlights, agreed principles and
procedures, roster, agenda, and Task Force Reports
http://www.nigms.nih.gov/news/meetings/airlie.html
TargetDB. Target Registration Database that contains sequences
from the worldwide structural genomics centers, and the PDB
http://targetdb.pdb.org/
OMG/LSR Corba Standard for Macromolecular Structure Data
(OMG specification formal/02-05-01). First formal version of the
Macromolecular Structure specification
http://www.omg.org/technology/documents/formal/
macro_molecular.htm
The OpenMMS Toolkit. Corba, Relation Database and XML
Software for Macromolecular Structure
http://openmms.sdsc.edu/
Structural Databases of Biological Macromolecules
6