Rxivist logo

Omics-Based Interaction Framework - a systems model to reveal molecular drivers of synergy

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

Posted 18 Apr 2020
bioRxiv DOI: 10.1101/2020.04.16.041350

Bioactive molecule library screening strategies may empirically identify effective combination therapies. However, without a systems theory to interrogate synergistic responses, the molecular mechanisms underlying favorable drug-drug interactions remain unclear, precluding rational design of combination therapies. Here, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in supra-additive biological responses. OBIF performs full factorial analysis of feature expression data from single vs. dual factor exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed a therapeutic dyad of immunostimulatory small molecules that induces synergistic protection against influenza A pneumonia. OBIF analysis of transcriptomic and proteomic data identified biologically relevant, unanticipated cooperation between RelA and cJun that we subsequently confirmed to be required for the synergistic antiviral protection. To demonstrate generalizability, OBIF was applied to data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, OBIF is a phenotype-driven systems model that supports multiplatform exploration of synergy mechanisms. ### Competing Interest Statement S.E.E. is an author on U.S. patent 8,883,174 “Stimulation of Innate Resistance of the Lungs to Infection with Synthetic Ligands” and owns stock in Pulmotect Inc., which holds the commercial options on these patent disclosures. All other authors declare that no conflict of interest exists.

Download data

  • Downloaded 457 times
  • Download rankings, all-time:
    • Site-wide: 109,977
    • In systems biology: 2,213
  • Year to date:
    • Site-wide: 156,900
  • Since beginning of last month:
    • Site-wide: 141,326

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide