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Interface-Based Structural Prediction of Novel Host-Pathogen Interactions

Emine Guven-Maiorov1, Chung-Jung Tsai1, Buyong Ma1

  • 1Cancer and Inflammation Program, Leidos Biomedical Research, Inc. Frederick National Laboratory for Cancer Research, National Cancer Institute, Frederick, MD, USA.

Methods in Molecular Biology (Clifton, N.J.)
|October 10, 2018
PubMed

Insights

Infections cause 20% of cancers, but mechanisms are unclear. This study introduces an interface-based computational method to predict host-pathogen interactions (HPIs), aiding cancer research.

Area of Science:

  • Infectious disease
  • Oncology
  • Structural biology
  • Bioinformatics

Background:

  • Approximately 20% of global cancer cases are linked to infections, yet the precise molecular mechanisms driving tumorigenesis remain largely unknown.
  • Pathogens can disrupt host cellular processes and promote cancer by hijacking host proteins, particularly at their binding interfaces.
  • Understanding these host-pathogen interactions (HPIs) is crucial for developing novel therapeutic strategies against cancer.

Purpose of the Study:

  • To review the first computational approach for identifying novel HPIs based on interface mimicry.
  • To provide mechanistic insights into pathogen-driven cancers by analyzing structural details of HPIs.
  • To address the scarcity of experimental HPI data by proposing a computational prediction method.

Main Methods:

  • Review of an interface-based computational approach for HPI identification.
  • Concept of interface mimicry to detect HPIs beyond sequence or structural similarity.
  • Case study using Kaposi's sarcoma herpesvirus (KSHV) to demonstrate the approach.

Main Results:

  • Interface mimicry offers a promising strategy for identifying more HPIs compared to traditional methods.
  • The approach provides a framework for understanding how pathogens like KSHV subvert host immunity.
  • Demonstrates potential for elucidating molecular mechanisms contributing to malignant transformation.

Conclusions:

  • Computational prediction of HPIs, particularly using interface mimicry, is essential due to data scarcity.
  • This approach can reveal novel HPIs and offer mechanistic insights into pathogen-induced cancers.
  • Further development and application of this method could lead to innovative cancer therapies.
Keywords:
Host-pathogen interaction predictionInterface mimicryMolecular mimicryProtein–protein interactionStructural networkSuperorganism network

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