The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics.
ABSTRACT The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL: http://www.cazy.org/.
- SourceAvailable from: Marco Kadowaki[Show abstract] [Hide abstract]
ABSTRACT: Biomass is the most abundant and short-term renewable natural resource on Earth whose recalcitrance toward enzymatic degradation represents significant challenge for a number of biotechnological applications. The not so abundant but critically necessary class of GH45 endoglucanases constitutes an essential component of tailored industrial enzyme cocktails because they randomly and internally cleave cellulose molecules. Moreover, GH45 glucanases are core constituents of major-brand detergent formulations as well as enzymatic aid components in the cotton processing industry, clipping unwanted cellulosic fibers from cotton (cellulosic)-based tissues. Here we report on a recombinant high-yield Neurospora crassa OR74A NcCel45A production system, a single-band GH45 endoglucanase purification, and a complete enzyme functional characterization. NcCel45A is a bimodular endoglucanase showing maximum activity at pH 6.0 and 60 °C, while most active against lichenan and β-glucans and lesser active toward filter paper, carboxymethylcellulose, and phosphoric acid-swollen cellulose. Gluco-oligosaccharide degradation fingerprinting experiments suggest cellopentaose as the minimal length substrate and ThermalFluor studies indicate that NcCel45A displays excellent stability at elevated temperatures up to 70 °C and pHs ranging from 5 to 9. Remarkably, we show that NcCel45A is uniquely resistant to a wide-range of organic solvents and small-angle X-ray scattering show a monkey-wrench molecular shape structure in solution, which indicates, unlike to other known cellulases, a non-fully extended conformation, thus conferring solvent protection. These NcCel45A unique enzymatic properties maybe key for specific industrial applications such as cotton fiber processing and detergent formulations.Molecular biotechnology. 02/2015;
- American Journal of Potato Research 10/2014; 91(5):517-524. · 0.95 Impact Factor
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ABSTRACT: Crop residue is an abundant, low-cost plant biomass material available worldwide for use in the microbial production of enzymes, biofuels, and valuable chemicals. However, the diverse chemical composition and complex structure of crop residues are more challenging for efficient degradation by microbes than are homogeneous polysaccharides. In this study, the transcriptional responses of Neurospora crassa to various plant straws were analyzed using RNA-Seq, and novel beneficial factors for biomass-induced enzyme production were evaluated. Comparative transcriptional profiling of N. crassa grown on five major crop straws of China (barley, corn, rice, soybean, and wheat straws) revealed a highly overlapping group of 430 genes, the biomass commonly induced core set (BICS). A large proportion of induced carbohydrate-active enzyme (CAZy) genes (82 out of 113) were also conserved across the five plant straws. Excluding 178 genes within the BICS that were also upregulated under no-carbon conditions, the remaining 252 genes were defined as the biomass regulon (BR). Interestingly, 88 genes were only induced by plant biomass and not by three individual polysaccharides (Avicel, xylan, and pectin); these were denoted as the biomass unique set (BUS). Deletion of one BUS gene, the transcriptional regulator rca-1, significantly improved lignocellulase production using plant biomass as the sole carbon source, possibly functioning via de-repression of the regulator clr-2. Thus, this result suggests that rca-1 is a potential engineering target for biorefineries, especially for plant biomass direct microbial conversion processes. Transcriptional profiling revealed a large core response to different sources of plant biomass in N. crassa. The sporulation regulator rca-1 was identified as beneficial for biomass-based enzyme production.Biotechnology for Biofuels 01/2015; 8:21. · 6.22 Impact Factor
Published online 05 October 2008Nucleic Acids Research, 2009, Vol. 37, Database issueD233–D238
The Carbohydrate-Active EnZymes database
(CAZy): an expert resource for Glycogenomics
Brandi L. Cantarel, Pedro M. Coutinho, Corinne Rancurel, Thomas Bernard,
Vincent Lombard and Bernard Henrissat*
Architecture et Fonction des Macromole ´cules Biologiques, UMR6098, CNRS, Universite ´s Aix-Marseille I & II,
163 Avenue de Luminy, 13288 Marseille, France
Received September 15, 2008; Accepted September 19, 2008
The Carbohydrate-Active Enzyme (CAZy) database
is a knowledge-based resource specialized in the
enzymes that build and breakdown complex carbo-
hydrates and glycoconjugates. As of September
2008, the database describes the present knowledge
on 113 glycoside hydrolase, 91 glycosyltransferase,
19 polysaccharide lyase, 15 carbohydrate esterase
These families are created based on experimentally
sequences from public databases with significant
similarity. Protein biochemical information is con-
tinuously curated based on the available literature
and structural information. Over 6400 proteins have
assigned EC numbers and 700 proteins have a PDB
structure. The classification (i) reflects the structural
features of these enzymes better than their sole sub-
strate specificity, (ii) helps to reveal the evolutionary
relationships between these enzymes and (iii) pro-
vides a convenient framework to understand mech-
anistic properties. This resource has been available
for over 10 years to the scientific community, contri-
buting to information dissemination and providing a
transversal nomenclature to glycobiologists. More
recently, this resource has been used to improve
the quality of functional predictions of a number
genome projects by providing expert annotation.
The CAZy resource resides at URL: http://www.
Due to the extreme variety of monosaccharide structures,
to the variety intersugar linkages and to the fact that vir-
tually all types of molecules can be glycosylated (from
sugars themselves, to proteins, lipids, nucleic acids,
antibiotics, etc.), the large variety of enzymes acting
on these glycoconjugates, oligo- and polysaccharides
probably constitute one of the most structurally diverse
set of substrates on Earth. Collectively designated as
Carbohydrate-Active enZymes (CAZymes), these enzymes
build and breakdown complex carbohydrates and glyco-
conjugates for a large body of biological roles (collectively
studied under the term of Glycobiology). Therefore, CAZ-
ymes have to perform their function usually with high
specificity. Because carbohydrate diversity (1) exceeds by
far the number of protein folds, CAZymes have evolved
from a limited number of progenitors by acquiring novel
specificities at substrate and product level. Such a dizzying
array of substrates and enzymes makes CAZymes a partic-
ularly challenging subject for experimental characteriza-
tion and for functional annotation in genomes.
Nearly 20 years ago, the first foundation for a family
classification of CAZymes was seen in an effort that clas-
sified cellulases into several distinct families based on
amino-acid sequence similarity (2). Soon after, the
family classification system based on protein sequence
and structure similarities, was extended to all known gly-
coside hydrolases (2–4), and subsequently extended to all
CAZymes involved in the synthesis, degradation and mod-
ification of glycoconjugates. The classification of CAZ-
ymes has been made available on the web since
September 1998. Because based on amino-acid sequence
similarities, these classifications correlate with enzyme
mechanisms and protein fold more than enzyme specifi-
city. Consequently, these families are used to conserva-
tively classify proteins of uncharacterized function whose
only known feature is sequence similarity to an experimen-
tally characterized enzyme, avoiding overprediction of
At present, CAZy covers approximately 300 protein
families in the following classes of enzyme activities:
(1) Glycoside hydrolases (GHs), including glycosidases
and transglycosidases (3–5). These enzymes consti-
tute 113 protein families that are responsible for
*To whom correspondence should be addressed. Tel: +33 4 91 82 55 87; Fax: +33 491 26 67 20; Email: Bernard.Henrissat@afmb.univ-mrs.fr
Correspondence may also be addressed to Pedro M. Coutinho. Email: Pedro.Coutinho@afmb.univ-mrs.fr
? 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.
the hydrolysis and/or transglycosylation of glycosidic
bonds. GH-coding genes are abundant and present in
the vast majority of genomes corresponding to
almost half—presently about 47%—of the enzymes
classified in CAZy. Because of their widespread
importance for biotechnological and biomedical app-
lications, GHs constitute so far the best biochemi-
cally characterized set of enzymes present in the
(2) Glycosyltransferases (GTs). These are the enzymes
responsible for the biosynthesis of glycosidic bonds
from phospho-activated sugar donors (6–8). They
form over 90 sequence-based families and present
in virtually every single organism and represent
about 41% of CAZy at present.
(3) Polysaccharide lyases (PLs) cleave the glycosidic
bonds of uronic acid-containing polysaccharides by
a b-elimination mechanism (6). They are presently
found in 19 families in CAZy (7), corresponding to
only about 1.5% of CAZy content. Many PLs have
biotechnological and biomedical applications and,
despite their small overall number, they are among
the CAZymes with the highest proportion of bio-
chemically characterized examples present in the
(4) Carbohydrate esterases (CEs). They remove ester-
based modifications present in mono-, oligo- and
polysaccharides and thereby facilitate the action
described in 15 families (7), CEs represent roughly
5% of CAZy entries. As the specificity barrier
between carbohydrate esterases and other esterase
activities is low, it is likely that the sequence-based
classification incorporates some enzymes that may
act on non-carbohydrate esters.
(5) Carbohydrate-binding modules (CBMs). These are
autonomously folding and functioning protein frag-
ments that have no enzymatic activity per se but are
known to potentiate the activity of many enzyme
activities described above by targeting to and pro-
moting a prolonged interaction with the substrate.
CBMs are most often associated to the other carbo-
hydrate-active enzyme catalytic modules in the same
polypeptide and can target different substrate forms
(9,10). However, occasionally they can be present
in isolated or tandem forms not coupled with an
enzyme. Roughly 7% of CAZy entries contain at
least one CBM module. CBMs are presently classi-
fied in 52 families in CAZy (7).
In addition to protein families that are well curated by
the CAZy database, CAZymes are known to contain
domains not acting on carbohydrates, including other
enzymes—such as proteases, myosin motors or phospha-
tases, etc.—and a variety of protein–protein or protein–
cell wall binding domains—cohesins, SLHs, TPR, etc.
The CAZy family classification system covers all taxo-
nomic groups, and provides the ground for common
nomenclature for CAZymes across different glycobiolo-
gists (11,12) generally specialized only in some specific
groups of organisms. Day-to-day inspection of new
enzyme characterizations reported in the literature regu-
larly led and continues to lead to the definition of new
enzyme families. Significantly, the CAZy families, origin-
ally created following hydrophobic cluster analysis in the
1990s from very limited number of sequences available
(2–6) and later complemented by BLAST- and HMMer-
based sequence similarity approaches, are globally surviv-
ing the challenge of time in spite of a hundred-fold
increase in the number of sequences.
The CAZy database contains information from (i)
sequence annotations from publicly available sources,
namely the NCBI, including taxonomical, sequence
and reference information, (ii) family classification and
(iii) known functional information. This data allow the
exploration of an enzyme (CAZyme), all CAZymes in an
organism or a CAZy protein family. The addition of new
family members and the incorporation of biochemical
information extracted from the literature are updated reg-
ularly, following careful inspection. Newly released three-
dimensional (3D) structures and genomes are analyzed as
they are released by public databases. Daily update
releases from GenBank form the bulk of sequence addi-
tions to the database (8) are complemented by weekly
PDB releases (13). Presently only genome released
through these GenBank releases are analyzed regularly,
whereas other genomes protein predictions are analyzed
upon request as part of collaborative efforts (vide infra).
Another feature of CAZy is that the number of families,
the family-associated information and content are con-
tinuously updated. When new families are created, old
previously released genomes and sequence in public data-
bases are reanalyzed to take the additional new family into
account to ensure completeness in sequence description.
Internally, curators include and maintain all referenced
biochemical and other characterization data from the lit-
erature and the analysis of full sets of protein sequences
present in a single genome. Because of this continuous
effort of data addition, new families are frequently
added and reflect the advances in experimental character-
ization of CAZymes. New families are exclusively created
based on the availability of at least one biochemically-
characterized member for which a sequence is available
and the information published in peer-reviewed scientific
literature. This sequence then serves as a seed for the
family that is gradually extended with sequences that
share statistically significant similarity.
Only functional assignments based on experimental
data are included in the CAZy database by the association
of EC numbers to protein sequences. Therefore inferred
functional assignments are not included. Experimental
data are ideally a direct enzyme analysis, but also could
include indirect evidence such as gene knockout experi-
ments with extensive characterization. Because there is a
shortage of EC numbers, relative to the number of func-
tions characterized experimentally, some incomplete EC
numbers such as 3.2.1.-, 2.4.1.-, 2.4.2.- and 2.4.99.- are
Nucleic Acids Research, 2009, Vol. 37, Databaseissue
also included in the database. In addition, as the described
functions in CAZy are only of enzymatic nature, addi-
tional and complementary binding and inhibitory func-
tions known to be associated with several CAZy
proteins will be curated and explored in the near future.
SEMI-AUTOMATIC MODULAR ASSIGNMENT
Carbohydrate-active enzymes, can exhibit a modular
structure (Figure 1), where a module can be defined as a
structural and functional unit (7,14). Each family in CAZy
is dependent on the definition of a common segment in
each full sequence that ultimately contains the catalytic or
binding module. The definition of the limits within the
sequence of the composing modules depends on available
information derived from a combination of different
(1) protein 3D structures,
(2) reported deletion studies and
(3) protein-sequence analysis and comparisons.
Different sequence comparison tools are used to define
enzyme families, particularly gapped BLAST (9) and
HMMER (10) using hidden markov models (HMMs)
made from each family. All the sequences corresponding
to the catalytic and binding of carbohydrate-active
enzymes are excised from the full protein sequence and
grouped in a BLAST library. Positive hits against this
‘high quality’ library, are entered into the database by
trained curators following manual check on a daily basis
with a small number of sequences with high identity
(>85%) ungapped alignments to previously examined
sequences being entered automatically.
A new layer dealing with the analysis of whole protein
sets issued from genomes has been introduced recently.
Modular annotation has been in fact applied to genome
data released by the NCBI, with over 750 genomes ana-
lyzed. Approximately 1–3% of the proteins encoded by a
typical genome correspond to CAZymes (10,11). In addi-
tion to publicly released sequences, annotation of proteins
in recently sequenced genomes prior to full release are
regularly performed by the CAZy team in collaboration
with scientists from all over the globe.
MANUAL FUNCTIONAL ANALYSIS
All too often, functional annotation methods employed
during whole genome annotation are erroneous and lack
consistent language (12,15). While sequence similarity to
genes annotated by GO or best BLAST hits can be a
good-starting point to assignment to pathways or possible
general functions, such as serine/theonine kinase, many
automatic functional assignments
much more specific. This is particularly true in the case
of CAZymes, since related families of the latter group
together enzymes of widely differing specificity.
The CAZy database employs practices that aim to elim-
Biochemical characterization of new proteins from the
literature is used to create new protein families, to anno-
tate their referring entries and to update family descrip-
employed to help the manual curator estimate the likely
general functions and add descriptions that indicate which
enzymatically characterized proteins are related to new
sequences. Inclusion of reference data compiled by com-
munities centered on model organisms is considered for
the future. Bibliographic references are included in CAZy
by a specific layer that includes over 16000 different bib-
liographic references. These references were extracted
automatically from individual accessions using ProFal
(16) and about one-third was entered manually.
When functional predictions are made, they arise from
manual curation by examination of closely related
sequences and when biochemical information is not avail-
able, such as the case for many genome projects, very
general functional tags are used to convey general func-
tions of a family. Recently, we have begun further break-
ing down families into subfamilies in the hope of grouping
proteins by specificity using sequence similarity. This
would allow us to give more insights into possible func-
tions. This new classification can also give insights into
conserved active sites and active site specificity, when com-
paring biochemically characterized enzymes. Currently
subfamily assignments are available publicly only for
GH13 (14), GH1, GH2 and GH5 (released with this pub-
lication). This effort will be continued in the future with
many more subfamilies being incorporated into the CAZy
knowledge base in the future. Subfamilies identify sub-
groups of sequences that are more homogeneous in their
functional properties. Most identified subfamilies are
monospecific. If polyspecific, the functional variability is
low and typically limited to two or three EC activities.
There, often the known subfamily functions often share
a substrate or product. Furthermore, rational enzyme
engineering may be used to switch the functions for several
cases (data not shown). Subfamilies also open the door for
further enzymatic characterization—a few subfamilies as
still no known activity—or for the identification of mean-
ingful targets for structural characterization.
LARGE-SCALE ANALYSIS AND COLLABORATION
Internal CAZy tools, such as our semi-automatic modular
assignment presently allow the analysis of a larger number
Figure 1. Examples of modular carbohydrate-active enzymes. (a)
Cellobiohydrolase I from Hypocrea jecorina (SP P00725); (b) alginate
lyase from Sphingomonas sp. A1 (GB BAB03312.1); (c) xylanase from
from Ruminococcus flavefaciens (GB CAB51934.1); (e) chitin synthase
from Emericella nidulans (GB BAA21714.1); (f) cyclicb-1-3-glucan
synthase from Bradyrhizobium japonicum (GB AAC62210.1).
Nucleic Acids Research, 2009,Vol. 37,Database issue D235
of sequences than a few years ago, making it possible to
perform large-scale analyses, such as the annotation of
CAZyme systems in genomes and metagenomic investiga-
tions of the breakdown of complex carbohydrates. A typi-
cal genome analysis begins with the assignment of protein
models to one or several CAZy families (depending on the
number of CAZy modules present within the sequence).
This family assignment is then followed by the prediction
of general functional classes using a manual examination
of alignments to closely related sequences, taking care to
identify the retention of active-site residues. Once a
genome is categorized by family and functional classes,
gene content analysis is utilized to give insights into how
newly sequenced organisms might be similar or different
from closely related species. Differences in genome con-
tent, i.e. relative family size, might reflect the relative
diversity or complexity of the inherent biological processes
(17) and therefore, the biology of the compared species.
For example, differences suggesting a more pronounced
pectin metabolism in ‘dicot’ Arabidopsis versus ‘monocot’
rice have been noted (17) as well as expected differences in
Arabidopsis versus long-lived poplar tree have been sug-
gested (18). With the advent of a variety of post-genomic
techniques, a new vision of the CAZymes as significant
components of carbohydrate-based systems now emerges.
Examples include: N- and O-glycosylation of proteins,
starch metabolism, biosynthesis of the cell-wall and its
subcomponents. Geisler-Lee et al. (19) have combined
bioinformatics and transcriptome analysis of various
poplar and Arabidopsis tissues and organs and have
shown that CAZyme transcripts are particularly abundant
in wood tissues.
In addition to a website facelift, the new CAZy website
comes with a host of new features. Primarily, we are now
offering users the ability to search the CAZy site for infor-
mation by GenBank protein accession number, family or
organism rather than navigate long static pages as prior to
12/31/2008 (Figure 2). To the new site we are also includ-
ing, pages to describe new releases, new genomes and
other new features. In addition, tools developed in the
lab are available for interactive use.
The CAZy database is a fluid database always changing
and growing as additional data becomes available.
Figure 2. (A) Once a search is performed, such as for a protein accession (P00275), the resulting page indicates the modular families that compose
that protein. (B) Upon clicking the resulting links provided in A, users are directed to a page about the family and gives a listing of all annotated
Nucleic Acids Research, 2009, Vol. 37, Databaseissue
In the last 2 years, the number of sequences in CAZY has
nearly doubled and the number of available genomes is
over 750. We believe this trend will continue in the coming
years. Unfortunately, while sequencing is forever more
rapid, progress in structural information and biochemical
characterization is much slower. The number of biochem-
ical data has grown only by 8% over the last 2 years
(Figure 3). This means that the gap is widening between
available sequences andbiochemically
enzymes, making better methods for high-throughput bio-
chemical characterization advantageous.
As started previously, we are actively pursuing the clas-
sification of subfamilies within each family. This further
level of classification is important for instance to identify
key residues or motifs important to define specificity.
Finally, we hope to offer soon a page to submit sequences
for a sequence similarity search and keyword search on
AVAILABILITY ON THE WEB
The CAZy database is available at www.cazy.org.
Information about selected families is available through
the website and at www.cazypedia.org. Software from
the group is available at www.cazy.org/tools.
The authors wish to thank the Departement des Sciences
de la Vie of CNRS for a 2-year funding grant to B.L.C.
and Novozymes for a contract supporting V.L.
Conflict of interest statement. P.M.C. is affiliated to
Universite ´ de Provence (Aix-Marseille I) and B.H. and
C.R. are members of CNRS.
1. Laine,R.A. (1994) A calculation of all possible oligosaccharide
isomers both branched and linear yields 1.05?10(12) structures for
a reducing hexasaccharide: the Isomer Barrier to development of
single-method saccharide sequencing or synthesis systems.
Glycobiology, 4, 759–767.
2. Henrissat,B., Claeyssens,M., Tomme,P., Lemesle,L. and
Mornon,J.P. (1989) Cellulase families revealed by hydrophobic
cluster analysis. Gene, 81, 83–95.
3. Henrissat,B. (1991) A classification of glycosyl hydrolases
based on amino acid sequence similarities. Biochem. J., 280 (Pt 2),
4. Henrissat,B. and Bairoch,A. (1993) New families in the
classification of glycosyl hydrolases based on amino acid sequence
similarities. Biochem. J., 293 (Pt 3), 781–788.
5. Henrissat,B. and Bairoch,A. (1996) Updating the sequence-based
classification of glycosyl hydrolases. Biochem. J., 316 (Pt 2),
6. Yip,V.L. and Withers,S.G. (2006) Breakdown of oligosaccharides
by the process of elimination. Curr. Opin. Chem. Biol., 10, 147–155.
7. Coutinho,P.M. and Henrissat,B. (1999) Carbohydrate-active
enzymes: an integrated database approach. In Gilbert,H.J.,
Davies,G., Henrissat,H. and Svensson,B. (eds), Recent Advances in
Carbohydrate Bioengineering. The Royal Society of Chemistry,
Cambridge, pp. 3–12.
8. Benson,D.A., Karsch-Mizrachi,I., Lipman,D.J., Ostell,J. and
Wheeler,D.L. (2004) GenBank: update. Nucleic Acids Res., 32,
9. Altschul,S.F., Madden,T.L., Schaffer,A.A., Zhang,J., Zhang,Z.,
Miller,W. and Lipman,D.J. (1997) Gapped BLAST and
PSI-BLAST: a new generation of protein database search programs.
Nucleic Acids Res., 25, 3389–3402.
10. Eddy,S.R. (1995) Multiple alignment using hidden Markov models.
In Proc. Intl Conf. Intel. Syst. Molec. Biol. ISMB, 3, 114–120.
11. Davies,G.J., Gloster,T.M. and Henrissat,B. (2005) Recent structural
insights into the expanding world of carbohydrate-active enzymes.
Curr. Opin. Struct. Biol., 15, 637–645.
12. Doerks,T., Bairoch,A. and Bork,P. (1998) Protein annotation:
detective work for function prediction. Trends Genet., 14, 248–250.
13. Bourne,P.E., Addess,K.J., Bluhm,W.F., Chen,L., Deshpande,N.,
Feng,Z., Fleri,W., Green,R., Merino-Ott,J.C.,
Townsend-Merino,W. et al. (2004) The distribution and query
systems of the RCSB Protein Data Bank. Nucleic Acids Res., 32,
14. Stam,M.R., Danchin,E.G., Rancurel,C., Coutinho,P.M. and
Henrissat,B. (2006) Dividing the large glycoside hydrolase
family 13 into subfamilies: towards improved functional
annotations of alpha-amylase-related proteins. Protein Eng. Des.
Sel., 19, 555–562.
15. Gilks,W.R., Audit,B., De Angelis,D., Tsoka,S. and Ouzounis,C.A.
(2002) Modeling the percolation of annotation errors in a database
of protein sequences. Bioinformatics (Oxford, England), 18,
16. Couto,F.M., Silva,J.M. and Coutinho,P.M. (2003) ProFAL:
PROtein Functional Annotation through Literature. In Pimentel,E.,
Brisaboa,N.R. and Gomez, J. (eds), In Proceedings of the 8th
w/ EC #s
Figure 3. The number of proteincontaining CAZy modules were noted in
December of the years 1999–2007. Within this set (Open circle), the
number of enzymatically characterized proteins (triangle) and those
with solved structures (open diamond) were also counted. In December
2007, <10% of proteins in CAZy were characterized enzymatically and
<1% had a solved structure. In 8 years, the number of sequences has
increased 14-fold, while the number of enzymatic and structural charac-
terization has mearly doubled. Therefore, the porportion of proteins with
functional and stuctural information is decreasing rapidly unless high
throughput functional efforts are made in this category of enzymes.
Nucleic Acids Research, 2009,Vol. 37,Database issue D237
Conference on Software Engineering and Databases, Alicante, Spain,
17. Yokoyama,R., Rose,J.K. and Nishitani,K. (2004) A surprising
diversity and abundance of xyloglucan endotransglucosylase/
hydrolases in rice. Classification and expression analysis.
Plant Physiol., 134, 1088–1099.
18. Tuskan,G.A., Difazio,S., Jansson,S., Bohlmann,J., Grigoriev,I.,
Hellsten,U., Putnam,N., Ralph,S., Rombauts,S., Salamov,A.
et al. (2006) The genome of black cottonwood,
Populus trichocarpa (Torr. & Gray). Science (New York, NY),
19. Geisler-Lee,J., Geisler,M., Coutinho,P.M., Segerman,B.,
Nishikubo,N., Takahashi,J., Aspeborg,H., Djerbi,S., Master,E.,
Andersson-Gunneras,S. et al. (2006) Poplar carbohydrate-active
enzymes. Gene identification and expression analyses.
Plant Physiol., 140, 946–962.
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