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Prediction of human-Streptococcus pneumoniae protein-protein interactions using logistic regression

Vivitri Dewi Prasasty1, Rory Anthony Hutagalung1, Reinhart Gunadi2

  • 1Faculty of Biotechnology, Atma Jaya Catholic University of Indonesia, Jakarta, 12930, Indonesia.

Computational Biology and Chemistry
|May 8, 2021
PubMed

Insights

This study predicts interactions between human and Streptococcus pneumoniae proteins to identify virulence factors. The findings highlight key bacterial proteins like BgaA, crucial for developing new treatments against antibiotic-resistant pneumonia.

Area of Science:

  • Microbiology
  • Computational Biology
  • Immunology

Background:

  • Streptococcus pneumoniae causes significant childhood mortality, with rising antibiotic resistance.
  • Identifying virulence factors is critical for developing new vaccines and therapeutics.
  • Host-pathogen protein-protein interactions (HP-PPIs) offer insights into infection mechanisms.

Purpose of the Study:

  • To predict HP-PPIs between human and S. pneumoniae proteins.
  • To identify potential virulence factors of S. pneumoniae.
  • To analyze the biological pathways and network centrality of predicted interactions.

Main Methods:

  • A logistic regression model was developed using protein domain occurrences as features.
  • The model was trained on HP-PPIs from three pathogens.
  • Predicted interactions were analyzed using pathway enrichment and network topology analysis.

Main Results:

  • The prediction model achieved 57-77% precision and 64-75% recall.
  • 5823 human-S. pneumoniae interactions were predicted, involving 30 bacterial and 324 human proteins.
  • Immune system pathways were predominantly implicated, with β-galactosidase (BgaA) identified as a highly central S. pneumoniae protein.

Conclusions:

  • Computational prediction of HP-PPIs can identify potential virulence factors.
  • BgaA is a key S. pneumoniae protein potentially involved in host-pathogen interactions.
  • Experimental validation is necessary to confirm predicted interactions and their roles in infection.

Keywords:
Host-pathogen protein-protein interactionsLogistic regressionNetwork centralityPathway enrichmentStreptococcus pneumoniae

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