| Literature DB >> 35387383 |
Jezreel Pantaleón García1, Vikram V Kulkarni1, Tanner C Reese1, Shradha Wali1, Saima J Wase1, Jiexin Zhang2, Ratnakar Singh3, Mauricio S Caetano1, Humam Kadara4, Seyed Javad Moghaddam1, Faye M Johnson3, Jing Wang2, Yongxing Wang1, Scott E Evans1.
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.Entities:
Year: 2022 PMID: 35387383 PMCID: PMC8982434 DOI: 10.1093/nargab/lqac028
Source DB: PubMed Journal: NAR Genom Bioinform ISSN: 2631-9268