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Prediction of novel host-pathogen interactions for Helicobacter pylori through interface mimicry and their implications to gastric cancer

Friday, September 15, 2017 — Poster Session IV

1:00 p.m. – 2:30 p.m.
FAES Terrace
NCI
COMPBIO-5

Authors

  • E Guven Maiorov
  • CJ Tsai
  • B Ma
  • R Nussinov

Abstract

About 20% of the cancer incidences worldwide have been estimated to be associated with infections. There is a strong correlation of some pathogens with various cancer types, such as Helicobacter pylori with gastric cancer. However, the molecular mechanisms how they trigger cancer in the host is generally unknown/incomplete. Pathogens interact with the host mainly through proteins. To subvert host defense, they mimic host proteins at different levels: sequence, structure, motif and interface -binding surface-. Interface mimicry seems to be the most common type. This similarity in interfaces permits pathogenic protein to compete with host proteins to bind to a target protein, alter physiological signaling and cause persistent infections, as well as cancer. Detection of host-pathogen interactions (HPIs) and mapping the re-wired HPI network – along with its structural details – is critical for in-depth understanding of the underlying pathogenesis mechanisms of infections, pathogen-triggered cancers, and developing efficient therapeutics. HPI data including structural details is far from complete and experimental characterization of the large-scale inter-species interactions is challenging. Thus, computational tools are becoming increasingly important in enriching the HPI data, uncovering their complex (bound) structures, and complementing the experiments. Here, we developed the first computational approach to identify novel HPIs that utilizes solely interface mimicry. Employing interface mimicry is promising to identify more HPIs than utilizing sequence or complete structural similarity since interface mimicry is more common. We applied our interface-based approach to H. pylori, dominant species in gastric microbiome that greatly increases gastric cancer risk in order to understand how they modulate host immunity and lead to tumorigenesis. We found that its proteins interfere with the functioning of host apoptosis pathway, cytokine and chemokine pathways, and also cell-cell adhesions. Our results shed light on the molecular mechanisms of resistance to apoptosis, immune evasion and loss of cell junctions that are seen in H. pylori-infected host cells. In conclusion, HPIs can help us unravel which human pathways are targeted by pathogenic proteins and how they contribute to pathogenesis of infections and pathogen-triggered cancer. With a better grasp on virulence strategies, we can develop better therapies.

Category: Computational Biology