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OBIF: an omics-based interaction framework to reveal molecular drivers of synergy
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 respon...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982434/ https://www.ncbi.nlm.nih.gov/pubmed/35387383 http://dx.doi.org/10.1093/nargab/lqac028 |
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author | Pantaleón García, Jezreel Kulkarni, Vikram V Reese, Tanner C Wali, Shradha Wase, Saima J Zhang, Jiexin Singh, Ratnakar Caetano, Mauricio S Kadara, Humam Moghaddam, Seyed Javad Johnson, Faye M Wang, Jing Wang, Yongxing Evans, Scott E |
author_facet | Pantaleón García, Jezreel Kulkarni, Vikram V Reese, Tanner C Wali, Shradha Wase, Saima J Zhang, Jiexin Singh, Ratnakar Caetano, Mauricio S Kadara, Humam Moghaddam, Seyed Javad Johnson, Faye M Wang, Jing Wang, Yongxing Evans, Scott E |
author_sort | Pantaleón García, Jezreel |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8982434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-89824342022-04-05 OBIF: an omics-based interaction framework to reveal molecular drivers of synergy Pantaleón García, Jezreel Kulkarni, Vikram V Reese, Tanner C Wali, Shradha Wase, Saima J Zhang, Jiexin Singh, Ratnakar Caetano, Mauricio S Kadara, Humam Moghaddam, Seyed Javad Johnson, Faye M Wang, Jing Wang, Yongxing Evans, Scott E NAR Genom Bioinform Methods Article 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. Oxford University Press 2022-04-05 /pmc/articles/PMC8982434/ /pubmed/35387383 http://dx.doi.org/10.1093/nargab/lqac028 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Article Pantaleón García, Jezreel Kulkarni, Vikram V Reese, Tanner C Wali, Shradha Wase, Saima J Zhang, Jiexin Singh, Ratnakar Caetano, Mauricio S Kadara, Humam Moghaddam, Seyed Javad Johnson, Faye M Wang, Jing Wang, Yongxing Evans, Scott E OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title | OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title_full | OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title_fullStr | OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title_full_unstemmed | OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title_short | OBIF: an omics-based interaction framework to reveal molecular drivers of synergy |
title_sort | obif: an omics-based interaction framework to reveal molecular drivers of synergy |
topic | Methods Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8982434/ https://www.ncbi.nlm.nih.gov/pubmed/35387383 http://dx.doi.org/10.1093/nargab/lqac028 |
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