Complete genome sequences of bacterial organisms
have revolutionized the search for antibiotics. The completion of ~30 bacterial whole-genome sequences and
ongoing sequencing projects of over 100 microbial organisms will allow
researchers to find novel therapeutic targets in innovative ways (1). The search for new antibiotics can be
assisted by computational methods such as homology-based analyses, structural
genomics, motif analyses, protein-protein interactions, and experimental
functional genomics (1). The greatest
obstacle is the massive wealth of data from the genome sequences. The sequence of microbial pathogens catalogs
every gene product that would be relevant for the host-parasite interaction and
potential antibiotic drug target (2).
Therefore, scientists interested in discovering antibiotics must extract
useful information from genomes through comparative, functional, or structural
genomics in order to simplify drug target selection.
The advent of bacterial whole-genome sequences
and establishment of useful genomic analyses comes at a crucial time for
antibiotic development. Increased
resistance of commonly used antibiotics, a growing prevalence of infections,
and the emergence of new pathogenic organisms challenge current use of
antibiotic therapy (3). Resistance is
more likely when newly introduced antibiotics are chemically similar to ones
already rendered ineffective.
Therefore, new antimicrobial compounds should ideally have novel
mechanisms of action. Effective drug
targets are selected based on several important criteria: they must be
necessary to bacterial survival or growth, highly conserved in either a broad-
or narrow- range of pathogens, absent or very different in humans, and
understood biochemically (3).
Currently, commonly used antibiotic drugs target series-specific genes,
unique enzymes and membrane transporters (4).
Antibiotics have several different mechanisms of actions: preventing
cell wall or membrane synthesis, protein synthesis, membrane transport, and
nucleic acid replication (5). The
availability of whole genomes of many pathogenic bacteria allows one to speed
up the process of drug target selection by finding novel genes in new and old
functional categories previously mentioned.
The analysis of open reading frames of bacterial
sequences makes all genes and gene products as possible drug targets (6). Scientist must therefore isolate the genes
that are essential to cell survival or growth, which would be most effective as
antibiotic targets. Traditionally, new
genes that were necessary to bacterial survival or virulence were discovered
through random mutagenesis and phenotyping of the bacterial genome (2). However, scientists can now use automated
comparisons of bacterial genomes to categorize genes and the proteins encoded. Primary sequence comparison programs, like
BLAST or PSI-BLAST, can determine gene functions by sequence homology. Sequence homology is also used to determine
clusters of orthologous groups (COGs).
COGs are groups of genes shared by evolutionarily distant
organisms. These orthologous families
of genes are prime candidates for broad-spectrum antimicrobial agents (2).
Sequence homology based methods have
disadvantages however. About 25-40% of the genes in a bacterial genome usually
do not find matches with known genes (6).
Furthermore, sequence homology is based on the assumption that similar
sequences will share similar functions—a presupposition that does not hold true
in many cases where similar sequences are structurally and functionally
diverse.
Therefore, one must turn to methods that do not
rely on sequence homology. One accurate
way of accessing function is gene expression profiling with cluster
analysis. Cluster analysis uses
microarray technology to analyze gene expression in order to organize genes
into functional groups (7). Unknown
genes functions can be estimated based on the general pathways or metabolic
functions of nearby clusters. However,
assigning gene function by cluster analyses are subject to inaccuracies as
well. The notion of function itself is
ambiguous and often misannotated.
Second, some proteins have multiple functions and likewise, some
functions require multiple proteins (8).
Therefore, structural genomics has been
suggested as a better method of drug target selection. Function is more directly a consequence of
its structure than its sequence (3, 8).
One way to assign unknown gene function is by 3D structure comparison to
a protein structure database.
Structural homologs tend to share functions. Furthermore, a good drug target would be structurally different
or nonexistent in humans. Checking for
structural homology against a human genome protein structure database would
determine whether the antibiotic against that drug target would also interfere
with any human functions.
Scientists can use phylogenetic groups that are
based on the specific folds shared by organisms. These fold and sequence families in bacterial pathogens can be
useful antibiotic targets (9). One can
find a fold common to an entire phylogenetic group in order to target all of
the organisms with a broad-spectrum antibiotic. Alternatively, one can find a fold that is unique to one
particular pathogen for an effective narrow-spectrum antibiotic target. Structural methods are the ideal for
selection of drug targets. However,
structural databases are not complete since quality protein-crystals are
difficult to form and hinders x-ray crystallography (10). However, nuclear magnetic resonance can
determine 3D structure determination.
Also, computational modeling is approaching accurate functional
predictions based on alignment of amino acid sequences (11).
Motif analysis is another strategy to identify
potential antibiotic targets among genes with unknown functions. Many databases, including PROSITE database,
can search for motifs in a sequence (2).
The motifs may show the approximate biochemical function of the
gene. Fourth, gene fusion is a new
computational method to infer protein interactions from genome sequences. Proteins that interact with each other tend
to have homologs in other organisms that are joined into a single protein
chain. This method would give
additional functional information for target proteins (2).
Finally, drug targets can be characterized
further by using gene expression profiles: DNA microarrays, large-scale protein
interaction mapping, and proteomics (2).
Genes that are functionally related are assumed to have similar gene
expression profile patterns. Protein
synthesis patterns are also useful to analyze the antimicrobial effect certain
drugs would have on particular necessary or important proteins (12).
The use of computational methods and expression
profiling all point to the need for a nonredundant, complete database of
structural and functional annotation of the proteins from known pathogenic
bacterial genomes and the human genome, once it is completed. The organization, accuracy, and easy
accessibility of such databases are crucial in the hunt for novel antibiotics. Perhaps a program can be specifically
designed to highlight antibiotic drug targets in query sequences. This program would scan structural databases
and other bacterial genomes for homology and similar folds. The program could be complemented by a
central, tailored database that reorganizes data for the most efficient search
of novel antibiotic targets. For
example, each protein or gene that is essential to certain bacterial
species. For example, the database
could include the protein’s phylogenetic group, 3D structure, proteins of
similar structural homology, and whether any similar protein exists in
humans. It could also use foreign keys
to connect to other databases that catalogue which known antibiotics and
inhibitors are used against similar targets.
In conclusion, the need for functional and
structural characterization and highly efficient management systems for the
data is integral for antibiotic drug-hunting.
Database management of these complete microbial genomes should be
constructed carefully and interconnected with other public and private databases. These databases containing structural and
functional annotation of whole-genome sequences of pathogenic bacteria will
make the search for new antibiotics highly effective and efficient. One should note that although the prospects
for new antibiotics are brightened by whole-genome sequences, there are still
many obstacles to developing an effective antibiotic. Most target sites generated would be cytoplasmic and would be
difficult to reach past the bacterial cell envelope (13). The Federal Drug Agency is also reluctant to
approve new antibiotics that use novel mechanisms and drug targets (20). Thus,
although the use of comparative, functional, and structural genomics speeds up
the process drug development, there are many more obstacles toward generating
an effective and approved antibiotic.
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References
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