Translating precision medicine for autism spectrum disorder: A pressing need

Autism spectrum disorder (ASD) is a heterogenous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. Currently, ASD is diagnosed according to behavior-based criteria that overlook clinical and genomic heterogeneity, thus repeatedly resulting in failed clinical trials. Here, we summarize the scientific evidence pointing to the pressing need to create a precision medicine framework for ASD and other NDDs. We discuss the role of omics and systems biology to characterize more homogeneous disease subtypes with different underlying pathophysiological mechanisms and to determine corresponding tailored treatments. Finally, we provide recent initiatives towards tackling the complexity in NDDs for precision medicine and cost-effective drug discovery.

gene2drug: a computational tool for pathway-based rational drug repositioning

Motivation

Drug repositioning has been proposed as an effective shortcut to drug discovery. The availability of large collections of transcriptional responses to drugs enables computational approaches to drug repositioning directly based on measured molecular effects.

Results

We introduce a novel computational methodology for rational drug repositioning, which exploits the transcriptional responses following treatment with small molecule. Specifically, given a therapeutic target gene, a prioritization of potential effective drugs is obtained by assessing their impact on the transcription of genes in the pathway(s) including the target. We performed in silico validation and comparison with a state-of-art technique based on similar principles. We next performed experimental validation in two different real-case drug repositioning scenarios: (i) upregulation of the glutamate-pyruvate transaminase (GPT), which has been shown to induce reduction of oxalate levels in a mouse model of primary hyperoxaluria, and (ii) activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy, whose modulation may be beneficial in neurodegenerative disorders.

Availability and implementation

A web tool for Gene2drug is freely available at http://gene2drug.tigem.it. An R package is under development and can be obtained from https://github.com/franapoli/gep2pep.

Contact

dibernardo@tigem.it.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comparing structural and transcriptional drug networks reveals signatures of drug activity and toxicity in transcriptional responses

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.

Transcriptional responses to drug treatment can reveal mechanism of action and off-target effects thus enabling drug repositioning, but only if measured in the appropriate cells at clinically relevant concentrations. A team led by Diego di Bernardo and Diego Medina generated a network representing structural similarities among compounds to automatically group together drugs with similar scaffolds and MOA. By comparing the structural drug network with a transcriptional drug network based on similarities in transcriptional response, the team observed broad differences between the two. This observation led to the identification of a transcriptional signature related lysosomal stress and phospholipidosis, and a physicochemical model to identify such compounds. These results provide general guidelines to prevent erroneous conclusion when using transcriptional responses of small molecules for drug discovery and drug repositioning

Goblet Cell Hyperplasia Requires High Bicarbonate Transport To Support Mucin Release

Goblet cell hyperplasia, a feature of asthma and other respiratory diseases, is driven by the Th-2 cytokines IL-4 and IL-13. In human bronchial epithelial cells, we find that IL-4 induces the expression of many genes coding for ion channels and transporters, including TMEM16A, SLC26A4, SLC12A2, and ATP12A. At the functional level, we find that IL-4 enhances calcium- and cAMP-activated chloride/bicarbonate secretion, resulting in high bicarbonate concentration and alkaline pH in the fluid covering the apical surface of epithelia. Importantly, mucin release, elicited by purinergic stimulation, requires the presence of bicarbonate in the basolateral solution and is defective in cells derived from cystic fibrosis patients. In conclusion, our results suggest that Th-2 cytokines induce a profound change in expression and function in multiple ion channels and transporters that results in enhanced bicarbonate transport ability. This change is required as an important mechanism to favor release and clearance of mucus.

Evaluation of a systems biology approach to identify pharmacological correctors of the mutant CFTR chloride channel

BACKGROUND

Mistrafficking of CFTR protein caused by F508del, the most frequent mutation in cystic fibrosis (CF), can be corrected by cell incubation at low temperature, an effect that may be mediated by altered expression of proteostasis genes.

METHODS

To identify small molecules mimicking low temperature, we compared gene expression profiles of cells kept at 27°C with those previously generated from more than 1300 compounds. The resulting candidates were tested with a functional assay on a bronchial epithelial cell line.

RESULTS

We found that anti-inflammatory glucocorticoids, such as mometasone, budesonide, and fluticasone, increased mutant CFTR function. However, this activity was not confirmed in primary bronchial epithelial cells. Actually, glucocorticoids enhanced Na(+) absorption, an effect that could further impair mucociliary clearance in CF airways.

CONCLUSIONS

Our results suggest that rescue of F508del-CFTR by low temperature cannot be easily mimicked by small molecules and that compounds with closer transcriptional and functional effects need to be found.

Drug-set enrichment analysis: a novel tool to investigate drug mode of action

MOTIVATION

Automated screening approaches are able to rapidly identify a set of small molecules inducing a desired phenotype from large small-molecule libraries. However, the resulting set of candidate molecules is usually very diverse pharmacologically, thus little insight on the shared mechanism of action (MoA) underlying their efficacy can be gained.

RESULTS

We introduce a computational method (Drug-Set Enrichment Analysis-DSEA) based on drug-induced gene expression profiles, which is able to identify the molecular pathways that are targeted by most of the drugs in the set. By diluting drug-specific effects unrelated to the phenotype of interest, DSEA is able to highlight phenotype-specific pathways, thus helping to formulate hypotheses on the MoA shared by the drugs in the set. We validated the method by analysing five different drug-sets related to well-known pharmacological classes. We then applied DSEA to identify the MoA shared by drugs known to be partially effective in rescuing mutant cystic fibrosis transmembrane conductance regulator (CFTR) gene function in Cystic Fibrosis.

AVAILABILITY AND IMPLEMENTATION

The method is implemented as an online web tool publicly available at http://dsea.tigem.it.

CONTACT

dibernardo@tigem.it

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Detailed analysis of biased histamine H₄ receptor signalling by JNJ 7777120 analogues

BACKGROUND AND PURPOSE

The histamine H₄ receptor, originally thought to signal merely through Gαi proteins, has recently been shown to also recruit and signal via β-arrestin2. Following the discovery that the reference antagonist indolecarboxamide JNJ 7777120 appears to be a partial agonist in β-arrestin2 recruitment, we have identified additional biased hH₄R ligands that preferentially couple to Gαi or β-arrestin2 proteins. In this study, we explored ligand and receptor regions that are important for biased hH₄R signalling.

EXPERIMENTAL APPROACH

We evaluated a series of 48 indolecarboxamides with subtle structural differences for their ability to induce hH₄R-mediated Gαi protein signalling or β-arrestin2 recruitment. Subsequently, a Fingerprints for Ligands and Proteins three-dimensional quantitative structure-activity relationship analysis correlated intrinsic activity values with structural ligand requirements. Moreover, a hH₄R homology model was used to identify receptor regions important for biased hH₄R signalling.

KEY RESULTS

One indolecarboxamide (75) with a nitro substituent on position R7 of the aromatic ring displayed an equal preference for the Gαi and β-arrestin2 pathway and was classified as unbiased hH₄R ligand. The other 47 indolecarboxamides were β-arrestin2-biased agonists. Intrinsic activities of the unbiased as well as β-arrestin2-biased indolecarboxamides to induce β-arrestin2 recruitment could be correlated with different ligand features and hH₄R regions.

CONCLUSION AND IMPLICATIONS

Small structural modifications resulted in diverse intrinsic activities for unbiased (75) and β-arrestin2-biased indolecarboxamides. Analysis of ligand and receptor features revealed efficacy hotspots responsible for biased-β-arrestin2 recruitment. This knowledge is useful for the design of hH₄R ligands with biased intrinsic activities and aids our understanding of the mechanism of H₄R activation.

Absolute configuration and biological profile of two thiazinooxadiazol-3-ones with L-type calcium channel activity: a study of the structural effects

In the framework of our interest in racemic thiazinooxadiazol-3-ones we determined the absolute configuration and the biological activity as L-type calcium channel blockers of two compounds that differ in the length of the acetal chain, which could affect the pharmacological profile. We observed an interesting inversion of the stereoselectivity, with the activity residing on the R-form for a short chain compound (n = 1) and on the S-form for a long chain one (n = 12). The length of the linear acetal chain appears to be able to invert the stereoselectivity of such a class of compounds, and in silico simulations suggested that this different behaviour might be explained by different hydrophilic and hydrophobic interactions with the binding site.

Synthesis, modeling and functional activity of substituted styrene-amides as small-molecule CXCR7 agonists

The chemokine receptor CXCR7 is an atypical G protein-coupled receptor as it preferentially signals through the β-arrestin pathway rather than through G proteins. CXCR7 is thought to be of importance in cancer and the development of CXCR7-targeting ligands is of huge importance to further elucidate the pharmacology and the therapeutic potential of CXCR7. In the present study, we synthesized 24 derivatives based on a compound scaffold patented by Chemocentryx and obtained CXCR7 ligands with pK(i) values ranging from 5.3 to 8.1. SAR studies were supported by computational 3D Fingerprint studies, revealing several important affinity descriptors. Two key compounds (29 and 30, VUF11207 and VUF11403) were found to be high-potency ligands that induce recruitment of β-arrestin2 and subsequent internalization of CXCR7, making them important tool compounds in future CXCR7 research.