Integration and mining of malaria molecular, functional and pharmacological data: how far are we from a chemogenomic knowledge space?

• Published in: Malaria Journal
• Main Authors: Hofmann-Apitius Martin, Roy Sylvaine, Saïdani Nadia, Jacq Nicolas, Ortet Philippe, Zimmermann Marc, Kasam Vinod, Joubert Fourie, Grando Delphine, Wells Gordon, Bastien Olivier, Birkholtz Lyn-Marie, Breton Vincent, Louw Abraham I, Maréchal Eric
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2006
• Subjects: Arctic medicine. Tropical medicine; RC955-962; Infectious and parasitic diseases; RC109-216; Arctic
• Online Access: https://doi.org/10.1186/1475-2875-5-110; https://doaj.org/article/dfa6e43edfd441198f993e71b60865f2

Abstract The organization and mining of malaria genomic and post-genomic data is important to significantly increase the knowledge of the biology of its causative agents, and is motivated, on a longer term, by the necessity to predict and characterize new biological targets and new drugs. Biological targets are sought in a biological space designed from the genomic data from Plasmodium falciparum , but using also the millions of genomic data from other species. Drug candidates are sought in a chemical space containing the millions of small molecules stored in public and private chemolibraries. Data management should, therefore, be as reliable and versatile as possible. In this context, five aspects of the organization and mining of malaria genomic and post-genomic data were examined: 1) the comparison of protein sequences including compositionally atypical malaria sequences, 2) the high throughput reconstruction of molecular phylogenies, 3) the representation of biological processes, particularly metabolic pathways, 4) the versatile methods to integrate genomic data, biological representations and functional profiling obtained from X-omic experiments after drug treatments and 5) the determination and prediction of protein structures and their molecular docking with drug candidate structures. Recent progress towards a grid-enabled chemogenomic knowledge space is discussed.