OBIF: An omics-based interaction framework to reveal molecular drivers of synergy

Jezreel Pantaleón García, Vikram V. Kulkarni, Tanner C. Reese, Shradha Wali, Saima J. Wase, Jiexin Zhang, Ratnakar Singh, Mauricio S. Caetano, Humam Kadara, Seyed Javad Moghaddam, Faye M. Johnson, Jing Wang, Yongxing Wang, Scott E. Evans

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Bioactive molecule library screening may empirically identify effective combination therapies, but molecular mechanisms underlying favorable drug-drug interactions often remain unclear, precluding further rational design. In the absence of an accepted systems theory to interrogate synergistic responses, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in synergistic biological responses. OBIF performs full factorial analysis of feature expression data from single versus dual exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed transcriptomic and proteomic data of a dyad of immunostimulatory molecules that induces synergistic protection against influenza A and revealed unanticipated NF-κB/AP-1 cooperation that is required for antiviral protection. To demonstrate generalizability, OBIF analyzed data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, unlike existing synergy quantification and prediction methods, OBIF is a phenotype-driven systems model that supports multiplatform interrogation of synergy mechanisms.

Original languageEnglish (US)
Article numberlqac028
JournalNAR Genomics and Bioinformatics
Volume4
Issue number2
DOIs
StatePublished - Jun 1 2022

ASJC Scopus subject areas

  • Genetics
  • Structural Biology
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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