A hybrid framework to characterize SLiM Mimicry by Leishmania (SMILE) parasites.

Pathogens invade and colonize their target host by modulating several key processes of host cells, resulting in modified physiology.

Interference mechanisms are intensively studied in the case of viruses and bacteria, however, our knowledge about invasive eukaryotic pathogens is more limited.To understand how eukaryotic pathogens hijack host processes at the molecular level, Leishmania will be examined using computational methods and the results will be validated by experimental techniques.

Leishmaniasis is a parasitic protozoan disease, responsible for non-resolving and chronic infection, affecting over 10 million people worldwide. Ongoing environmental changes are considered to be helping the disease to spread to new regions.

Leishmania pathogenesis is poorly understood and to combat the infection and to control the disease, further insights into host-pathogen interaction are desperately needed.An integral part of the constant arms race between the host immune system and pathogens is the rapid evolution of pathogenic Short Linear Motifs (SLiMs), capable of modulating the host cell regulation.

The limited sequence length of these protein-binding segments provides evolutionary advantages for the pathogen, as SLiMs can arise de novo and many can be packed into a single protein.

Their properties make them hard to explore using biochemical methods alone, however, using bioinformatics approaches this process can be accelerated.SMILE aims to identify SLiMs mediating Leishmaniasis.

My hierarchical strategy starts from protein level identification to detailed structural characterisation of host-pathogen interactions, as an ultimate goal. The description of SLiMs already suggests novel therapeutic strategies to counteract mutation-based diseases.

The outcome of the project has the potential to suggest targets for the development of similar treatments against eukaryotic parasitic diseases.