On the correspondence between the transcriptomic response of a compound and its effects on its targets

• Main Authors: Domingo-Fernández, D. (Author), Ence, D. (Author), Engler Hart, C. (Author), Healey, D. (Author)
• Format: Article
• Language: English
• Published: NLM (Medline) 2023
• Subjects: article; case report; clinical article; Compound target identification; deconvolution; Drug discovery; Drug target; Mechanism of action (MoA) deconvolution; transcriptomics; Transcriptomics; writing
• Online Access: View Fulltext in Publisher; View in Scopus

 Better understanding the transcriptomic response produced by a compound perturbing its targets can shed light on the underlying biological processes regulated by the compound. However, establishing the relationship between the induced transcriptomic response and the target of a compound is non-trivial, partly because targets are rarely differentially expressed. Therefore, connecting both modalities requires orthogonal information (e.g., pathway or functional information). Here, we present a comprehensive study aimed at exploring this relationship by leveraging thousands of transcriptomic experiments and target data for over 2000 compounds. Firstly, we confirm that compound-target information does not correlate as expected with the transcriptomic signatures induced by a compound. However, we reveal how the concordance between both modalities increases by connecting pathway and target information. Additionally, we investigate whether compounds that target the same proteins induce a similar transcriptomic response and conversely, whether compounds with similar transcriptomic responses share the same target proteins. While our findings suggest that this is generally not the case, we did observe that compounds with similar transcriptomic profiles are more likely to share at least one protein target and common therapeutic applications. Finally, we demonstrate how to exploit the relationship between both modalities for mechanism of action deconvolution by presenting a case scenario involving a few compound pairs with high similarity. © 2023. The Author(s).