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Bioinformaticsnpj Systems Biology and Applications
Peer-reviewed journal article

Integrated Structure-Transcription analysis of small molecules reveals widespread noise in drug-induced transcriptional responses and a transcriptional signature for drug-induced phospholipidosis

Francesco SirciiD, Francesco NapolitanoiD, Sandra Pisonero‐Vaquero, Diego CarrellaiD, Diego Luis MedinaiD, Diego di BernardoiD

Abstract

We performed an integrated analysis of drug chemical structures and drug-induced transcriptional responses. We demonstrated that a network representing 3D structural similarities among 5,452 compounds can be used to automatically group together drugs with similar scaffolds and mode-of-action. We then compared the structural network to a network representing transcriptional similarities among a subset of 1,309 drugs for which transcriptional response were available in the Connectivity Map dataset. Analysis of structurally similar, but transcriptionally different, drugs sharing the same mode of action (MOA) enabled us to detect and remove weak and noisy transcriptional responses, greatly enhancing the reliability and usefulness of transcription-based approaches to drug discovery and drug repositioning. Analysis of transcriptionally similar, but structurally different drugs with unrelated MOA, led us to the identification of a \"toxic\" transcriptional signature indicative of lysosomal stress (lysosomotropism) and lipid accumulation (phospholipidosis) partially masking the target-specific transcriptional effects of these drugs. We further demonstrated by High Content Screening that this transcriptional signature is caused by the activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy. Our results show that chemical structures and transcriptional profiles provide complementary information and that combined analysis can lead to new insights on on- and off-target effects of small molecules.

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