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The
use of antimalarial drugs is an important component of malaria control
programmes. These drugs class broadly into quinolines, artemisinins, antifolates,
atovaquone/proguanil and antibiotics. The effectiveness of drugs is increasingly
compromised by resistance. The development of new antimalarials and improvement
of existing ones is therefore crucial to reduction of the increasing disease
burden and economic loss due to malaria. Publication of the genome sequences of
the most virulent human malaria parasite, Plasmodium falciparum and a
rodent parasite, P. yoelii yoelii open new opportunities for intensive
research to identify critical parasite determinants encoded in the genomes that
can serve as drug targets and candidates for drug discovery programmes. The
future availability of genome sequences of primate and other human and rodent
malaria parasites will permit comparative analysis and open the ability to test
the efficacy of drugs in robust model systems prior to clinical trials.
The
challenge of identifying good drug targets will rely on integration of disparate
data from high-throughput technologies such as genome and cDNA sequencing,
microarrays, proteomics, structural genomics and metabolic networks. This
integration requires mining databases using bioinformatics tools to detect
patterns that make parasite determinants stand out as candidates for drug
discovery. According to Yuthavong1 the characteristics of a good
malaria drug target are (i) essential feature of the parasite life cycle, must
differ significantly from any analogous process in the host (ii) lack of
alternative pathways which circumvent the target (iii) preferred accessibility
to the parasite or accumulation within the parasite of lead compounds (iv) low
potential for development of drug resistance (v) involvement in a rate limiting
biochemical process (vi) ability to readily test effects of inhibitors on the
target (to validate the target) (vii) presence of a straightforward test system
for high-throughput screening and (viii) different specificity for inhibition
from the host enzyme/receptor, existence of known specific inhibitors.
Comprehensive
study of the function and interactions of candidates in the context of a
host-parasite relationship is crucial before committing them to the complete
discovery process. Some bioinformatics approaches that exploit the biological
data include gene expression analysis, search for acquisition of foreign genetic
material and scanning for genes under positive selection.
Knowledge
of how malaria parasite genes are regulated is key to exploiting them as
targets; the differences in levels, time and stage/tissue of expression as well
as in comparison to that of the host. Little is known about the mechanisms of
transcription and translation in malaria parasites when compared to organisms
such as yeast or their apicomplexan relative Toxoplasma gondii. For
example, the role of alternative splicing needs to be intensively studied. Early
studies on alternative transcripts in P. falciparum speculated that
multiple protein isoforms could be a means of diverting host immune response
from the major functional isoform. Temporal and spatial data on protein
diversity can be used to design inhibitors that are specific to the major
isoform.
Malaria
parasites have an indispensable organelle called the apicoplast that is thought
to be of bacterial and algal origins by secondary endosymbiosis. Genome analysis
has identified about 500 nuclear-encoded genes that are targeted to the
apicoplast. Horizontal transfer of genetic material from this organelle to the
nuclear genome can now be intensively studied using bioinformatics to reveal
biological processes unique to the parasite, which take place in the apicoplast
and/or the parasite cytoplasm. Such processes can be target of antibiotics and
herbicides.
Bioinformatics
tools for high-throughput positive selection scanning of inter- and intraspecies
orthologous DNA sequences has the potential to yield important mutations that
confer a selective advantage to malaria parasites. Combining data from sequence
alignment such as type, location and effect of such mutations with protein
structure data such as substrate binding and cleavage sites can improve design
of selective inhibitors. This type of integrated view has been used to explain
host specificity among blood‑feeding parasites.
It
is important to re-emphasise the need to develop bioinformatics capacity in
disease endemic countries2. A better understanding of the parasite
biology and excellent capacity to use bioinformatics tools will accelerate the
control of malaria.
Raphael
D. Isokpehi
South
African National Bioinformatics Institute (SANBI)
University
of the Western Cape, Bellville 7535
South
Africa
1. Yuthavong Y. Drug targets for the malaria parasite genome. In: Kamchonwongpaisan S. and Uthaipibull C. (eds). Microarray Technology and Its Application in Malaria Research. The International Workshop on Microarrray Technology for Malaria Parasites. Pathumthani, Thailand, NASTDA, 2003.
2.
Hide W. Malaria and the developing worlds of genome bioinformatics.
Science Scope 2000. http://scope.educ.washington.edu/malaria/commentary/ -
accessed 10 May 2003
@2002. TJPR Faculty of Pharmacy, University of Benin, Benin City, Nigeria |
Tel: +234 802 3360318 Fax: +234 52 602257 E-mail: okhamafe@uniben.edu erah@uniben.edu p_erah@yahoo.com |
Last updated: August 19, 2003 |