Toward Pathway Engineering:
A New Database of Genetic andMolecular Pathways

Minoru Kanehisa
Institute for Chemical Research, Kyoto University

FromGenome

Se- sequencing projects have been ing of genes and molecules iscompleted for budding yeast (12Mbp) and for several bacteria including cyanobacteria (3.6 Mbp)
The Human Genome Project which was carried out by thewas initiated in the late 1980s Kazusa DNA Research Instituteas a natural consequence of in Japan.
the technology developments inmolecular biology and with theFor the rst time in humanexpectation of new biomedical history we are beginning to haveapplications. The project will the data at hand which leads touncover the complete DNA se- ward a basic understanding of
quence of the human genome the fundamental problems in life
consisting of 3 billion base pairs sciences including the origin andand 100 thousand genes. In evolution of life and the con1977, a small virus genome, ception and development of anx174, consisting of just 5,000 individual. The data will alsobase pairs and 11 genes was de- stimulate practical applications
termined by the emerging tech- in medical, pharmaceutical, andnology of DNA sequence deter- agricultural sciences. However,mination. After two decades somewhat contrary to public noof technology developments the tion, the sequence data obtained
rst complete genome of a by genome projects do not by
free-living biological organism, themselves provide direct anHaemophilus in uenzae, was de- swers to such fundamental probtermined in 1995. The bacteri- lems or practical applications.
al genome consisting of 1.8 mil- The sequencing of a genome islion nucleotides and 1,700 genes an easier part than the underis already followed by the ex- standing of functional implicaplosion of complete genomic se- tions of when, where, and how
quences of a number of organ- genes and molecules function inisms from bacteria to eukary- living organisms. Fortunately,otes. As of mid 1996, the genome our knowledge of the functionquences to Functions

also rapidly expanding owing to
the advancement of experimental technologies in the broad
areas of molecular and cellularbiology. In order to make fulluse of the information obtainedby genome projects, it is essential that such functional data
are properly computerized indatabases and informatics technologies are developed for functional prediction.
From Gene Gatalogs
to Pathways

The functional data that relate
to sequence information are currently stored as annotations tosequence data, for example, inthe so-called features tables, inthe sequence databases of DNAs
and proteins. However, thesebasically represent the sequencefunction relationships of single
molecules, i.e., the individualcomponents of a biological system, and they do not containhigher level information, i.e.,
wiring diagrams, of genetic interactions and molecular interac-tions. It is obvious that without such wiring-diagrams a biological system could never be described or understood.
We have thus initiated a
project named KEGG, Kyoto
Encyclopedia of Genes andGenomes, to computerize thecurrent knowledge of molecularand cellular biology in terms of
the information pathways thatconsist of interacting genes ormolecules. The basic data itemin KEGG is a pairwise interaction of genes or moleculesthat is represented by what istermed a binary relation. An
expert in the eld would synthesize a pathway from a collectionof binary relations obtained byexperimental observations. In
order to cope with the rapidly expanding body of information it is necessary to computerize the process of synthesizing
pathways, in addition to computerizing known pathways derived by human experts.
Currently, we are focusing
our attention on the metabolic

pathways, although we intend
to computerize other pathways,
such as signal transduction andcell cycle pathways and thegenetic pathways of the earlystages in fruit y development.
We expect that once such data
are properly computerized, it
will become feasible to assist experiments, facilitate understanding, and even perform logical simulations of information
pathways controlling all aspectsof living organisms.

Figure 1: The home page of the GenomeNet WWW server at http://www.genome.ad.jp/ and theDBGET and KEGG search windows.
GenomeNet Database GenomeNet under the Genome The aim of GenomeNet is not

Informatics Project, a part of theHuman Genome Program of theMinistry of Education, Science,
In 1991 we established a Sports and Culture (Monbusho).
computernetwork
named
Service

simply a network connection; it
is to establish the informatics
infrastructure for genome research and related research areas

in molecular and cellular biology. In view of the subsequent
government funding of Internet
activities in Japan, we are only
currently maintaining the connection between Tokyo, Kyotoand Fukuoka. Originally, we envisioned a network community
where the informatics needs ofindividual researchers and individual projects would be realizedon their local machines by integrating databases and computational resources distributed overthe network. We believe that thewide-ranging database service
in GenomeNet, which is jointly
provided by the Supercomputer
Laboratory of the Institute for
Chemical Research, Kyoto University and the Human Genome
Center of Institute of MedicalScience, the University of Tokyo,
has greatly contributed towardthat end.
The most popular modeof access to the GenomeNet
database service is to use ourWWW server shown in Fig. 1,
which provides among others,
the DBGET integrated databaseretrieval system and the sequence interpretation tools including sequence similarity andmotif search programs. The
server receives tens of thousandsof queries per day, one-third ofwhich are from abroad. Although the GenomeNet databaseservice is a result of technological developments in Japan, forexample, DBGET was developedin my laboratory, most of thedatabases that we o er originat-

ed in the U.S. or Europe. Even
the databases which claimed to
be organized in Japan actuallyheavily depend on the systems
and protocols developed in othercountries.
KEGG is an attempt to advance our original concepts andtechnologies, and actual datacollection e orts.
Although
we have not yet made a formal announcement of KEGG,
a preliminary version has been
publicly available through theGenomeNet WWW server since
December 1995. The target dateof the rst release of KEGG isOctober 1996. We plan to distribute compact discs in addition
to the service over the Internet.

Pathways

KEGG

Binary relations
Hierarchies

GenesMolecules
LIGAND

GenomeDatabases

OMIM

DBGET

CAS

DNA/Protein Databases

MedlineFigure 2: The concept of KEGG and its relation to DBGET. In KEGG functional aspects of genes
and molecules are represented by binary relations, hierarchies, and pathways.

The Concepts

Currently, KEGG is composedof three interconnected sections:pathways, genes, and molecules,
which are also linked to anumber of existing databases
through DBGET (Fig.
2).
Both conceptually and practically, KEGG and DBGET
are tightly coupled systems.
DBGET provides an integrated
view of various databases inmolecular biology, where the basis of integration is the link (binary relation) between related
entries in di erent databases. InKEGG, an organism may beconsidered a database of genes
and gene products, and the link
between them is used for synthesizing a pathway.
Thus,both KEGG and DBGET contain an aspect of the deductive
database where new relations
can be deduced from relations
stored in the database.
Another important concept
in KEGG is the hierarchy that
represents functional, structural,and evolutionary relationships ofgenes and molecules. For example, the degree of similarity
in sequences and 3D structuresof proteins is used for classifying superfamilies and 3D folds.
The taxonomy is the classi cation of organisms, which is important in extending sequenceand 3D structural similarities tofunctional similarities. Theseand other classi cations are taken from appropriate sources andimplemented in KEGG.
While the binary relation
represents at, horizontal relationships, the hierarchy represents vertical relationships.
Both are naturally integrated
in the process of deduction.

The concept of relation anddeduction is thus the basisof our KEGG project. For
our logic-based activities, weacknowledge the past collaborations with the Fifth Generation
Computer Project team members in ICOT and the researchers
in the Genome Informatics Research Projects 1991-1995 and1996-2000.
The Technologies

KEGG makes full use of theadvancements in the databaseand networking technology, including deductive and objectoriented databases, the multimedia environment of WWW, andthe mobile agent, Java. Although we maintain the logicbased formalism of relation anddeduction, we take a practical,exible approach in the actualimplementation. For example,
we use the CORAL deductive
database system for experimenting the deduction process, but
in the actual implementation ofKEGG we have developed ourown C++ library for manipulating binary relations and hierarchies.
With a similar philosophy,
DBGET does not depend on
any database management system. The entire system has
been developed in house. Actually, DBGET has its roots in theIDEAS sequence analysis package that I developed in the early
1980s in the U.S. National Institutes of Health. DBGET aims atintegrating di erent databases
and di erent types of data inmolecular biology. The integration, however, is at the level ofdata entries; for example, entries in di erent databases canbe retrieved uniformly and links
are made between related entries
in di erent databases. In thisloosely-coupled integration, theschema or the format of how anentry is organized by data items
is left to each database. Thisshould be contrasted with using
the same relational database andenforcing a uni ed schema forentries coming from many di erent sources, which necessarily involves the process of data conversion.
The proliferation of WWW
was a boon to our approachof loose integration; the link
capabilities of DBGET t themechanism of WWW very nicely. The text-based DBGET system was easily extended to themultimedia environment, where
3D graphics, 2D graphics, andimages are now retrievable inthe WWW version of DBGET.
In addition, because the updateprocedure does not involve data
conversion, DBGET has beenand will continue to be able tocope with the ever increasing
number and volume of daily updated databases.
KEGG inherits all these
DBGET capabilities. Furthermore, the graphics handling of
pathway diagrams and chromosome maps has been implemented by Java. The new capabilities
of logical inference and simulation are still under development,
but we hope to make the rst
test version available shortly.
DataCollection

Ef-forts

However eciently the system
is developed as a database, themost critical thing is the quali-

ty of data that it contains. Especially, since the data we handle require biological knowledge
in speci c domains, quality control is far more dicult than, forexample, DNA and protein sequence databases. Among themany di erent subjects of molecular and genetic pathways, themetabolic pathways are probably the easiest to computerizebecause of the well-establishedknowledge and existing compilations. We have been computerizing metabolic pathways,
in collaboration with an expert
in biochemistry, mostly fromthe Boehringer wall chart andthe compilation by the Japanese
Biochemical Society, and partly
from other textbooks and on-line
databases.
KEGG currently contains
most of the known metabolic
pathways represented by about
80 graphical diagrams. An enzyme is a clickable object in the
diagram to retrieve the corresponding entry of the LIGAND
database and then, through
DBGET, a number of related
entries in di erent databases.
LIGAND is a database of enzyme reactions and metabolic
compounds that we organize ina separate project.
It provides links between the new
PATHWAY database and the existing databases of nucleotide sequences, amino acid sequences,
3D structures, sequence motifs,
amino acid mutations, geneticmaps, genetic diseases, and literature.
In addition to computerizing known pathways, we are developing methods to compute
pathways from binary relations.
The metabolic pathway is best
suited for this purpose as well,for there is a chemical basis of
the binary relation between asubstrate and a product. KEGG
contains the substrate-productrelationships and the relationships of two consecutive enzymes that appear in the known
metabolic pathways.
One of the major objectives of the KEGG project isto link the structural data (genecatalogs) obtained by genome
projects and the functional dataobtained in specialized elds ofmolecular and cellular biology.
Once the genome sequencing iscomplete, it is customary to attempt to classify all genes according to their functions, for example in the scheme developedby Monica Riley. We plan tomake a more objective classi cation based on the pathway data
being entered. At the moment,
we only perform the classi cation of enzyme genes.
Future Directions

Perhaps, the most challenging
task of the KEGG system is theinference capabilities that will
help human beings to make logical reasoning processes. Thesecapabilities have not yet beendeveloped or implemented, buthere are some examples (Fig. 3).
Given a list of enzymes (ECnumbers) that are found in thegene catalog of an organism,
KEGG automatically generates
the organism speci c pathways
by marking the enzymes found.
Then, the connectivity and completeness of marked enzymes canbe used to assess the correctness of functional assignments in
the gene catalog. The existenceof a missing element implies either the gene catalog is wrong

or there is an unknown reaction pathway that utilizes di erent enzymes in the catalog. For
the latter possibility, the deduction from binary relations of substrates and products is useful. In
any case, the pathway information is critical in the nding andfunctional assignment of genes in
the genome projects.
As in the sequence alignmentand 3D structure alignment, thepathway alignment will become
an important tool to identify
global and local similarities between two pathways or a consensus among many pathways.
For example, the comparison oforganism-speci c pathways will
identify functional similarities
and di erences, as well as evolutionary relationships, between
organisms. Because pathway
data are linked to a diverse rangeof data in KEGG and DBGET,
they can be analyzed in many
di erent perspectives. For example, by examining where theenzymes in the same operon appear on the pathway will give insights into the regulation of gene
expression, as well as the evolutionary implications of genestructures.
The pathway computations
described above will have direct practical applications,which may be collectively called
pathway engineering. For example, from pathway comparisonsand analyses, an e ective pesticide or a side-e ect free drug
may better be designed. Geneticengineering was based on theDNA sequence information, andprotein engineering was based on
the protein 3D structures. With
the availability of new types ofdata on the wiring-diagrams ofliving systems, pathway engi-

neering is bound to emerge as a new biotechnology in the 21st century.

Biological knowledge

Genome projects

Gene catalogs

Binary relations
and hierarchies
Path computation
Deduction from binary relations;gene finding and prediction.

Pathways

Pathway comparison
Similarities/differences with respect
to species/environment.
Pathway analysis
Duplication of genes;
relationships with operons; etc.

Pathway engineering
Design of new pathways andcompounds.

Figure 3: Pathway engineering will become feasible once data and knowledge are properly computerized and new computational methods are developed.