Skip to content
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Menu
Home
About Us
Resources
Profiles Metrics
Authors Directory
Institutions Directory
Top Authors
Top Institutions
Top Sponsors
AI Digest
Contact Us
Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Estimating novel potential drug targets of Plasmodium falciparum by analysing the metabolic network of knock-out strains in silico
Infection, Genetics and Evolution, Volume 9, No. 3, Year 2009
Notification
URL copied to clipboard!
Description
Malaria is one of the world's most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Biomedical research could enable treating the disease by effectively and specifically targeting essential enzymes of this parasite. However, the parasite has developed resistance to existing drugs making it indispensable to discover new drugs. We have established a simple computational tool which analyses the topology of the metabolic network of P. falciparum to identify essential enzymes as possible drug targets. We investigated the essentiality of a reaction in the metabolic network by deleting (knocking-out) such a reaction in silico. The algorithm selected neighbouring compounds of the investigated reaction that had to be produced by alternative biochemical pathways. Using breadth first searches, we tested qualitatively if these products could be generated by reactions that serve as potential deviations of the metabolic flux. With this we identified 70 essential reactions. Our results were compared with a comprehensive list of 38 targets of approved malaria drugs. When combining our approach with an in silico analysis performed recently [Yeh, I., Hanekamp, T., Tsoka, S., Karp, P.D., Altman, R.B., 2004. Computational analysis of Plasmodium falciparum metabolism: organizing genomic information to facilitate drug discovery. Genome Res. 14, 917-924] we could improve the precision of the prediction results. Finally we present a refined list of 22 new potential candidate targets for P. falciparum, half of which have reasonable evidence to be valid targets against micro-organisms and cancer. © 2008 Elsevier B.V. All rights reserved.
Authors & Co-Authors
Fatumo, Segun A.
Nigeria, Ota
Covenant University
Plaimas, Kitiporn
Germany, Heidelberg
Universität Heidelberg
Mallm, Jan Philipp
Germany, Heidelberg
Universität Heidelberg
Schramm, Gunnar
Germany, Heidelberg
German Cancer Research Center
Adebiyi, Ezekiel Femi
Nigeria, Ota
Covenant University
Oswald, Marcus
Germany, Heidelberg
Universität Heidelberg
Eils, Roland
Germany, Heidelberg
Universität Heidelberg
Germany, Heidelberg
German Cancer Research Center
König, Rainer
Germany, Heidelberg
Universität Heidelberg
Germany, Heidelberg
German Cancer Research Center
Statistics
Citations: 88
Authors: 8
Affiliations: 3
Identifiers
Doi:
10.1016/j.meegid.2008.01.007
ISSN:
15671348
Research Areas
Cancer
Infectious Diseases
Noncommunicable Diseases