Bioinformatics approaches to malaria

Malaria is a life threatening disease found in tropical and subtropical regions of the world. Each year it kills 781 000 individuals; most of them are children under the age of five in sub-Saharan Africa. The most severe form of malaria in humans is caused by the parasite Plasmodium falciparum, which is the subject of the first part of this thesis.

The PfEMP1 protein which is encoded by the highly variablevargene family is important in the pathogenesis and immune evasion of malaria parasites. We analyzed and classified these genes based on the upstream sequence in sevenPlasmodium falciparumclones. We show that the amount of nucleotide diversity is just as big within each clone as it is between the clones.

DNA methylation is an important epigenetic mark in many eukaryotic species. We are studying DNA methylation in the malaria parasitePlasmodium falciparum. The work is still in progress and will be introduced here. One of the biggest concerns regarding the treatment of malaria is the continued development of resistance to existing drugs.

Therefore, new drugs will be needed in the future. The ApiAP2 proteins are a recently discovered family of putative transcription factors. As they might perform important regulatory functions in the parasite, they could be useful as drug targets. Here, we study one of these proteins and describe our work on identifying small compounds that can interfere with its DNA binding abilities.

Specific binding of short peptides by proteins of the major histocompatibility complex (MHC) is an important event in the activation of immune responses to various pathogens. The set of peptides that can bind a specific MHC molecule can be characterized by a binding motif. In the second part of this thesis, we developed an algorithm that can distinguish several binding motifs within a mixture of peptides from different motifs.