Mantra 2.0: An online collaborative resource for drug mode of action and repurposing by network analysis

Elucidation of molecular targets of a compound (mode of action, MoA) and of its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organised in a network of nodes (drugs) and edges (similarities) highlighting “communities” of drugs sharing a similar MoA. A user can upload gene expression profiles (GEPs) before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the GEPs into a unique drug ”node” embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA, and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource

Isozyme-Specific Ligands for O-acetylserine sulfhydrylase, a Novel Antibiotic Target

Conceived and designed the experiments: FS PC BC ES AM. Performed the experiments: FS RS ES PF SR. Analyzed the data: FS BC ES PF GEK PFC AM. Contributed reagents/materials/analysis tools: PC PB GC. Wrote the paper: FS GEK BC AM.The last step of cysteine biosynthesis in bacteria and plants is catalyzed by O-acetylserine sulfhydrylase. In bacteria, two isozymes, O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, have been identified that share similar binding sites, although the respective specific functions are still debated. O-acetylserine sulfhydrylase plays a key role in the adaptation of bacteria to the host environment, in the defense mechanisms to oxidative stress and in antibiotic resistance. Because mammals synthesize cysteine from methionine and lack O-acetylserine sulfhydrylase, the enzyme is a potential target for antimicrobials. With this aim, we first identified potential inhibitors of the two isozymes via a ligand- and structure-based in silico screening of a subset of the ZINC library using FLAP. The binding affinities of the most promising candidates were measured in vitro on purified O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B from Salmonella typhimurium by a direct method that exploits the change in the cofactor fluorescence. Two molecules were identified with dissociation constants of 3.7 and 33 µM for O-acetylserine sulfhydrylase-A and O-acetylserine sulfhydrylase-B, respectively. Because GRID analysis of the two isoenzymes indicates the presence of a few common pharmacophoric features, cross binding titrations were carried out. It was found that the best binder for O-acetylserine sulfhydrylase-B exhibits a dissociation constant of 29 µM for O-acetylserine sulfhydrylase-A, thus displaying a limited selectivity, whereas the best binder for O-acetylserine sulfhydrylase-A exhibits a dissociation constant of 50 µM for O-acetylserine sulfhydrylase-B and is thus 8-fold selective towards the former isozyme. Therefore, isoform-specific and isoform-independent ligands allow to either selectively target the isozyme that predominantly supports bacteria during infection and long-term survival or to completely block bacterial cysteine biosynthesis.Yeshttp://www.plosone.org/static/editorial#pee

Ligand-, Structure-and Pharmacophore-based Molecular Fingerprints: A Case Study on Adenosine A1, A2A, A2B, and A3 Receptor Antagonists

FLAP fingerprints are applied in the ligand-, structure- and pharmacophore-based mode in a case study on antagonists of all four adenosine receptor (AR) subtypes. Structurally diverse antagonist collections with respect to the different ARs were constructed by including binding data to human species only. FLAP models well discriminate “active” (=highly potent) from “inactive” (=weakly potent) AR antagonists, as indicated by enrichment curves, numbers of false positives, and AUC values. For all FLAP modes, model predictivity slightly decreases as follows: A2BR > A2AR > A3R > A1R antagonists. General performance of FLAP modes in this study is: ligand- > structure- > pharmacophore- based mode. We also compared the FLAP performance with other common ligand- and structure-based fingerprints. Concerning the ligand-based mode, FLAP model performance is superior to ECFP4 and ROCS for all AR subtypes. Although focusing on the early first part of the A2A, A2B and A3 enrichment curves, ECFP4 and ROCS still retain a satisfactory retrieval of actives. FLAP is also superior when comparing the structure-based mode with PLANTS and GOLD. In this study we applied for the first time the novel FLAPPharm tool for pharmacophore generation. Pharmacophore hypotheses, generated with this tool, convincingly match with formerly published data. Finally, we could demonstrate the capability of FLAP models to uncover selectivity aspects although single AR subtype models were not trained for this purpose

Detailed analysis of biased histamine H4 receptor signalling by JNJ7777120 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 hH4 R ligands that preferentially couple to Gαi or β-arrestin2 proteins. In this study, we explored ligand and receptor regions that are important for biased hH4 R signalling. EXPERIMENTAL APPROACH: We evaluated a series of 48 indolecarboxamides with subtle structural differences for their ability to induce hH4 R-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 hH4 R homology model was used to identify receptor regions important for biased hH4 R 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 hH4 R 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 hH4 R 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 hH4 R ligands with biased intrinsic activities and aids our understanding of the mechanism of H4 R activation

Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis

Abstract Summary: Elucidation of molecular targets of a compound [mode of action (MoA)] and its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organized in a network of nodes (drugs) and edges (similarities) highlighting 'communities' of drugs sharing a similar MoA. A user can upload gene expression profiles before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the gene expression profiles into a unique drug 'node' embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource. Availability and implementation: The web tool is freely available for academic use at http://mantra.tigem.it. Contact: [email protected]

Pharmacoproteomics pinpoints HSP70 interaction for correction of the most frequent Wilson disease-causing mutant of ATP7B

Pathogenic mutations in the copper transporter ATP7B have been hypothesized to affect its protein interaction landscape contributing to loss of function and, thereby, to hepatic copper toxicosis in Wilson disease. Although targeting mutant interactomes was proposed as a therapeutic strategy, druggable interactors for rescue of ATP7B mutants remain elusive. Using proteomics, we found that the frequent H1069Q substitution promotes ATP7B interaction with HSP70, thus accelerating endoplasmic reticulum (ER) degradation of the mutant protein and consequent copper accumulation in hepatic cells. This prompted us to use an HSP70 inhibitor as bait in a bioinformatics search for structurally similar Food and Drug Administration-approved drugs. Among the hits, domperidone emerged as an effective corrector that recovered trafficking and function of ATP7B-H1069Q by impairing its exposure to the HSP70 proteostatic network. Our findings suggest that HSP70-mediated degradation can be safely targeted with domperidone to rescue ER-retained ATP7B mutants and, hence, to counter the onset of Wilson disease

Optimizing virtual fragment screening for GPCRs: Identification of novel ligands for the histamine H3 receptor using ligand- and structure-based molecular fingerprints

Virtual fragment screening (VFS) is a promising new method that uses computer models to identify small, fragment-like biologically active molecules as useful starting points for fragment-based drug discovery (FBDD). Training sets of true active and inactive fragment-like molecules to construct and validate target customized VFS methods are however lacking. We have for the first time explored the possibilities and challenges of VFS using molecular fingerprints derived from a unique set of fragment affinity data for the histamine

Goblet Cell Hyperplasia Requires High Bicarbonate Transport To Support Mucin Release

none17Goblet 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.noneGorrieri, Giulia; Scudieri, Paolo; Caci, Emanuela; Schiavon, Marco; Tomati, Valeria; Sirci, Francesco; Napolitano, Francesco; Carrella, Diego; Gianotti, Ambra; Musante, Ilaria; Favia, Maria; Casavola, Valeria; Guerra, Lorenzo; Rea, Federico; Ravazzolo, Roberto; Di Bernardo, Diego; Galietta, Luis J VGorrieri, Giulia; Scudieri, Paolo; Caci, Emanuela; Schiavon, Marco; Tomati, Valeria; Sirci, Francesco; Napolitano, Francesco; Carrella, Diego; Gianotti, Ambra; Musante, Ilaria; Favia, Maria; Casavola, Valeria; Guerra, Lorenzo; Rea, Federico; Ravazzolo, Roberto; Di Bernardo, Diego; Galietta, Luis J. V