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. 2017 Aug 25;3:23.
doi: 10.1038/s41540-017-0022-3. eCollection 2017.

Comparing Structural and Transcriptional Drug Networks Reveals Signatures of Drug Activity and Toxicity in Transcriptional Responses

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Free PMC article

Comparing Structural and Transcriptional Drug Networks Reveals Signatures of Drug Activity and Toxicity in Transcriptional Responses

Francesco Sirci et al. NPJ Syst Biol Appl. .
Free PMC article

Abstract

We performed an integrated analysis of drug chemical structures and drug-induced transcriptional responses. We demonstrated that a network representing three-dimensional structural similarities among 5452 compounds can be used to automatically group together drugs with similar scaffolds, physicochemical parameters and mode-of-action. We compared the structural network to a network representing transcriptional similarities among a subset of 1309 drugs for which transcriptional response were available in the Connectivity Map data set. Analysis of structurally similar, but transcriptionally different drugs sharing the same MOA enabled us to detect and remove weak and noisy transcriptional responses, greatly enhancing the reliability of transcription-based approaches to drug discovery and drug repositioning. Cardiac glycosides exhibited the strongest transcriptional responses with a significant induction of pathways related to epigenetic regulation, which suggests an epigenetic mechanism of action for these drugs. Drug classes with the weakest transcriptional responses tended to induce expression of cytochrome P450 enzymes, hinting at drug-induced drug resistance. 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 found that this transcriptional signature is shared by 258 compounds and it is associated to the activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy. Finally, we built a predictive Random Forest model of these 258 compounds based on 128 physicochemical parameters, which should help in the early identification of potentially toxic drug candidates.

Conflict of interest statement

The authors declare that they have no competing financial interests.

Figures

Fig. 1
Fig. 1
The structural network among 5452 compounds. The network is partitioned into communities (groups of highly interconnected nodes) and rich-clubs (groups of communities) sharing common chemical structures and enriched for drugs with similar Mode of Action. Examples of three Rich Clubs are shown. a The steroids rich-club (1: testosterone scaffold, 2: estradiol scaffold, 3: cortisone scaffold, 4: progesterone scaffold, 5 and 6: mixed steroids); b The antibiotics rich-club (1 and 2: tetracycline scaffold, 3: cephalosporin scaffold, 4: penicillin scaffold); and c The CNS-acting drug rich-club (1 and 2: phenothiazine scaffold, 3–6: various tricyclic antidepressant scaffolds)
Fig. 2
Fig. 2
Comparison of transcriptional and structural distances between 784 CMAP compounds having at least one ATC annotation. Each dot represents the structural (x-axis) and transcriptional (y-axis) distance between two compounds. A total of 306,936 drug-pairs are shown. Drug-pairs having the same clinical application as annotated by their ATC code are represented by red dots. Dashed lines represent the significance threshold for the transcriptional (horizontal line) and structural (vertical line) distance, splitting the plane into four quadrants. Representative examples of drug-pairs are shown for quadrants I, II and III: drug-pairs in quadrant I have similar structure but induce different transcriptional responses; drug-pairs in quadrant II exhibit both similar structure and similar transcriptional responses; drug-pairs in quadrant III have different structures but induce similar transcriptional responses
Fig. 3
Fig. 3
The Transcriptional Variability (TV) of different drug classes. Box-plots summarizing the TV for drugs within each class. The bold line in each box represents the median, while the whiskers represent the 25th and the 75th percentile. Dots represent outliers. Prt.inh.: Protein synthesis inhibitors; HDAC: histone deacetylase inhibitors; Chemoth.: chemotherapeutic agents; Antibio.: antibiotics; NSAIDs: non-steroid antinflammatory agents; GC: glucocorticoids; Antipsych: antipsychotics; Antihist: antihistamines
Fig. 4
Fig. 4
Performance of the transcriptional distance in detecting drugs with the same ATC code. Compounds were divided into three sets: (all) the 1165 compounds in CMAP having at TV value; (high TV) 582 compounds with a TV higher than the median TV among all the compounds; (low TV) 582 compounds with a TV lower than the median TV. For each set, the transcriptional distance of each drug-pair was computed. Drug-pairs were then sorted according to their transcriptional distance, with drug-pairs with the smallest distance towards the origin of the x-axis; the positive predictive value (PPV) was computed as the percentage of true positives over false positives plus true positives and shown on the y-axis. The PPV obtained by randomly sorting drugs is also shown (Random)
Fig. 5
Fig. 5
Drugs inducing a lysosomotropic gene expression signature. The transcriptional responses elicited by eight lysosomotropic compounds were combined into a single node in the transcriptional drug network (red triangle). Transcriptional distances to this lysosomotropic gene expression signature were computed for all the 1309 drugs in CMAP. Only drugs with a transcriptional distance below the significance threshold are shown (0.8) and color-coded according to their ATC classification. Triangles (PLD + drugs); squares (CAD + drugs); circles (CAD- and PLD)
Fig. 6
Fig. 6
Effects of drugs on TFEB nuclear translocation and LipidTOX assay. a TFEB localization in stably HeLa cells overexpressing TFEB-GFP and treated with DMSO or the indicated drugs. b Lipid accumulation in HeLa cells was detected by staining with LipidTOX reagent upon drug treatment

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