The mechanistic functional landscape of retinitis pigmentosa: a machine learning-driven approach to therapeutic target discovery

BACKGROUND

Retinitis pigmentosa is the prevailing genetic cause of blindness in developed nations with no effective treatments. In the pursuit of unraveling the intricate dynamics underlying this complex disease, mechanistic models emerge as a tool of proven efficiency rooted in systems biology, to elucidate the interplay between RP genes and their mechanisms. The integration of mechanistic models and drug-target interactions under the umbrella of machine learning methodologies provides a multifaceted approach that can boost the discovery of novel therapeutic targets, facilitating further drug repurposing in RP.

METHODS

By mapping Retinitis Pigmentosa-related genes (obtained from Orphanet, OMIM and HPO databases) onto KEGG signaling pathways, a collection of signaling functional circuits encompassing Retinitis Pigmentosa molecular mechanisms was defined. Next, a mechanistic model of the so-defined disease map, where the effects of interventions can be simulated, was built. Then, an explainable multi-output random forest regressor was trained using normal tissue transcriptomic data to learn causal connections between targets of approved drugs from DrugBank and the functional circuits of the mechanistic disease map. Selected target genes involvement were validated on rd10 mice, a murine model of Retinitis Pigmentosa.

RESULTS

A mechanistic functional map of Retinitis Pigmentosa was constructed resulting in 226 functional circuits belonging to 40 KEGG signaling pathways. The method predicted 109 targets of approved drugs in use with a potential effect over circuits corresponding to nine hallmarks identified. Five of those targets were selected and experimentally validated in rd10 mice: Gabre, Gabra1 (GABARα1 protein), Slc12a5 (KCC2 protein), Grin1 (NR1 protein) and Glr2a. As a result, we provide a resource to evaluate the potential impact of drug target genes in Retinitis Pigmentosa.

CONCLUSIONS

The possibility of building actionable disease models in combination with machine learning algorithms to learn causal drug-disease interactions opens new avenues for boosting drug discovery. Such mechanistically-based hypotheses can guide and accelerate the experimental validations prioritizing drug target candidates. In this work, a mechanistic model describing the functional disease map of Retinitis Pigmentosa was developed, identifying five promising therapeutic candidates targeted by approved drug. Further experimental validation will demonstrate the efficiency of this approach for a systematic application to other rare diseases.

Repurposing of FDA approved kinase inhibitor bosutinib for mitigation of radiation induced damage via inhibition of JNK pathway

Radiotherapy is a common modality for cancer treatment. However, it is often associated with normal tissue toxicity in 20-80% of the patients. Radioprotectors can improve the outcome of radiotherapy by selectively protecting normal cells against radiation toxicity. In the present study, compound libraries containing 54 kinase inhibitors and 80 FDA-approved drugs were screened for radioprotection of lymphocytes using high throughput cell analysis. A second-generation FDA-approved kinase inhibitor, bosutinib, was identified as a potential radioprotector for normal cells. The radioprotective efficacy of bosutinib was evinced from a reduction in radiation induced DNA damage, caspase-3 activation, DNA fragmentation and apoptosis. Oral administration of bosutinib protected mice against whole body irradiation (WBI) induced morbidity and mortality. Bosutinib also reduced radiation induced bone-marrow aplasia and hematopoietic damage in mice exposed to 4 Gy and 6 Gy dose of WBI. Mechanistic studies revealed that the radioprotective action of bosutinib involved interaction with cellular thiols and modulation of JNK pathway. The addition of glutathione and N-acetyl cysteine significantly reduced the radioprotective efficacy of bosutinib. Moreover, bosutinib did not protect cancer cells against radiation induced toxicity. On the contrary, bosutinib per se exhibited anticancer activity against human cancer cell lines. The results highlight possible use of bosutinib as a repurposable radioprotective agent for mitigation of radiation toxicity in cancer patients undergoing radiotherapy.

A genetically supported drug repurposing pipeline for diabetes treatment using electronic health records

BACKGROUND

The identification of new uses for existing drug therapies has the potential to identify treatments for comorbid conditions that have the added benefit of glycemic control while also providing a rapid, low-cost approach to drug (re)discovery.

METHODS

We developed and tested a genetically-informed drug-repurposing pipeline for diabetes management. This approach mapped genetically-predicted gene expression signals from the largest genome-wide association study for type 2 diabetes mellitus to drug targets using publicly available databases to identify drug-gene pairs. These drug-gene pairs were then validated using a two-step approach: 1) a self-controlled case-series (SCCS) using electronic health records from a discovery and replication population, and 2) Mendelian randomization (MR).

FINDINGS

After filtering on sample size, 20 candidate drug-gene pairs were validated and various medications demonstrated evidence of glycemic regulation including two anti-hypertensive classes: angiotensin-converting enzyme inhibitors as well as calcium channel blockers (CCBs). The CCBs demonstrated the strongest evidence of glycemic reduction in both validation approaches (SCCS HbA1c and glucose reduction: -0.11%, p = 0.01 and -0.85 mg/dL, p = 0.02, respectively; MR: OR = 0.84, 95% CI = 0.81, 0.87, p = 5.0 x 10-25).

INTERPRETATION

Our results support CCBs as a strong candidate medication for blood glucose reduction in addition to cardiovascular disease reduction. Further, these results support the adaptation of this approach for use in future drug-repurposing efforts for other conditions.

FUNDING

National Institutes of Health, Medical Research Council Integrative Epidemiology Unit at the University of Bristol, UK Medical Research Council, American Heart Association, and Department of Veterans Affairs (VA) Informatics and Computing Infrastructure and VA Cooperative Studies Program.

Dihydroergotamine ameliorates liver fibrosis by targeting transforming growth factor β type II receptor

BACKGROUND

The transforming growth factor β (TGFβ) signaling pathway plays a crucial role in the development of liver fibrosis by activating TGFβ type II receptor (TGFβR2), followed by the recruitment of TGFβR1 finally triggering downstream signaling pathway.

AIM

To find drugs targeting TGFβR2 that inhibit TGFβR1/TGFβR2 complex formation, theoretically inhibit TGFβ signaling pathway, and thereby ameliorate liver fibrosis.

METHODS

Food and Drug Administration-approved drugs were screened for binding affinity with TGFβR2 by virtual molecular docking. We identified 6 candidates and further explored their potential by Cell Counting Kit-8 (CCK-8) cell cytotoxic experiment to validate toxicity and titrated the best cellular working concentrations. Next, we further demonstrated the detailed molecular working mechanisms using mutagenesis analysis. Finally, we used a mouse model to investigate its potential anti-liver fibrosis effect.

RESULTS

We identified 6 drug candidates. Among these 6 drugs, dihydroergotamine (DHE) shows great ability in reducing fibrotic gene expressions such as collagen, p-SMAD3, and α-SMA in TGFβ induced cellular model of liver fibrosis in LX-2 cells. Furthermore, we demonstrated that DHE binds to TGFβR2. Moreover, mutation of Leu27, Phe30, Thr51, Ser52, Ile53, and Glu55 of TGFβR2 disrupted the binding of TGFβR2 with DHE. In addition, DHE significantly improved liver fibrosis, as evidenced by Masson’s trichrome staining of liver sections. This is further supported by the width and the velocity of the portal vein, and serum markers of liver function. In line with those observations, DHE also decreased macrophages infiltration and extracellular matrix deposition in the liver.

CONCLUSION

DHE alleviates liver fibrosis by binding to TGFβR2 thereby suppressing TGFβ signaling pathway. We show here that as far as drug repurposing, DHE has great potential to treat liver fibrosis.

The Impact of Genetically Proxied AMPK Activation, the Target of Metformin, on Functional Outcome Following Ischemic Stroke

BACKGROUND AND PURPOSE

We performed a two-sample Mendelian randomization (MR) analysis to evaluate the causal effect of genetically proxied AMP-activated protein kinase (AMPK) activation, which is the target of metformin, on functional outcome following ischemic stroke onset.

METHODS

A total of 44 AMPK-related variants associated with HbA1c (%) were used as instruments for AMPK activation. The primary outcome was the modified Rankin Scale (mRS) score at 3 months following the onset of ischemic stroke, evaluated as a dichotomous variable (3-6 vs. 0-2) and subsequently as an ordinal variable. Summary-level data for the 3-month mRS were obtained from the Genetics of Ischemic Stroke Functional Outcome network, including 6,165 patients with ischemic stroke. The inverse-variance weighted method was used to obtain causal estimates. The alternative MR methods were used for sensitivity analysis.

RESULTS

Genetically predicted AMPK activation was significantly associated with lower odds of poor functional outcome (mRS 3-6 vs. 0-2, odds ratio [OR]: 0.06, 95% confidence interval [CI]: 0.01-0.49, P=0.009). This association was maintained when 3-month mRS was analyzed as an ordinal variable. Similar results were observed in the sensitivity analyses, and there was no evidence of pleiotropy.

CONCLUSION

This MR study provided evidence that AMPK activation by metformin may exert beneficial effects on functional outcome following ischemic stroke.

Primaquine, an antimalarial drug that controls the growth of cryptococcal cells

INTRODUCTION

The treatment of Cryptococcus neoformans with fluconazole and amphotericin B is, at times, characterised by clinical failure. Therefore, this study sought to re-purpose primaquine (PQ) as an anti-Cryptococcus compound.

METHOD

The susceptibility profile of some cryptococcal strains towards PQ was determined using EUCAST guidelines, and PQ's mode of action was examined. In the end, the ability of PQ to enhance in vitro macrophage phagocytosis was also assessed.

RESULTS

We show that PQ had a significant inhibitory effect on the metabolic activity of all tested cryptococcal strains, with 60 µM, defined as MIC₅₀ in this preliminary study, as it reduced the metabolic activity by more than 50%. Moreover, at this concentration, the drug was able to affect mitochondrial function adversely, as treated cells displayed significant (p < 0.05) loss of mitochondrial membrane potential, cytochrome c (cyt c) leakage and overproduction of reactive oxygen species (ROS) when compared to non-treated cells. It is our reasoned summation that the produced ROS targeted the cell walls and cell membranes, inducing observable ultrastructural changes and a significant (p < 0.05) increase in membrane permeability when compared to non-treated cells. Concerning the PQ effect on macrophages, it was noted that it significantly (p < 0.05) enhanced macrophage phagocytic efficiency compared to non-treated macrophages.

CONCLUSION

This preliminary study highlights the potential of PQ to inhibit the in vitro growth of cryptococcal cells. Moreover, PQ could control the proliferation of cryptococcal cells inside macrophages, which they often manipulate in a Trojan horse-like manner.

EZCancerTarget: an open-access drug repurposing and data-collection tool to enhance target validation and optimize international research efforts against highly progressive cancers

The expanding body of potential therapeutic targets requires easily accessible, structured, and transparent real-time interpretation of molecular data. Open-access genomic, proteomic and drug-repurposing databases transformed the landscape of cancer research, but most of them are difficult and time-consuming for casual users. Furthermore, to conduct systematic searches and data retrieval on multiple targets, researchers need the help of an expert bioinformatician, who is not always readily available for smaller research teams. We invite research teams to join and aim to enhance the cooperative work of more experienced groups to harmonize international efforts to overcome devastating malignancies. Here, we integrate available fundamental data and present a novel, open access, data-aggregating, drug repurposing platform, deriving our searches from the entries of Clue.io. We show how we integrated our previous expertise in small-cell lung cancer (SCLC) to initiate a new platform to overcome highly progressive cancers such as triple-negative breast and pancreatic cancer with data-aggregating approaches. Through the front end, the current content of the platform can be further expanded or replaced and users can create their drug-target list to select the clinically most relevant targets for further functional validation assays or drug trials. EZCancerTarget integrates searches from publicly available databases, such as PubChem, DrugBank, PubMed, and EMA, citing up-to-date and relevant literature of every target. Moreover, information on compounds is complemented with biological background information on eligible targets using entities like UniProt, String, and GeneCards, presenting relevant pathways, molecular- and biological function and subcellular localizations of these molecules. Cancer drug discovery requires a convergence of complex, often disparate fields. We present a simple, transparent, and user-friendly drug repurposing software to facilitate the efforts of research groups in the field of cancer research.

Whole blood transcriptomic profiling identifies molecular pathways related to cardiovascular mortality in heart failure

AIMS

Chronic heart failure (CHF) is a systemic syndrome with a poor prognosis and a need for novel therapies. We investigated whether whole blood transcriptomic profiling can provide new mechanistic insights into cardiovascular (CV) mortality in CHF.

METHODS AND RESULTS

Transcriptome profiles were generated at baseline from 944 CHF patients from the BIOSTAT-CHF study, of whom 626 survived and 318 died from a CV cause during a follow-up of 21 months. Multivariable analysis, including adjustment for cell count, identified 1153 genes (6.5%) that were differentially expressed between those that survived or died and strongly related to a validated clinical risk score for adverse prognosis. The differentially expressed genes mainly belonged to five non-redundant pathways: adaptive immune response, proteasome-mediated ubiquitin-dependent protein catabolic process, T-cell co-stimulation, positive regulation of T-cell proliferation, and erythrocyte development. These five pathways were selectively related (RV coefficients >0.20) with seven circulating protein biomarkers of CV mortality (fibroblast growth factor 23, soluble ST2, adrenomedullin, hepcidin, pentraxin-3, WAP 4-disulfide core domain 2, and interleukin-6) revealing an intricate relationship between immune and iron homeostasis. The pattern of survival-associated gene expression matched with 29 perturbagen-induced transcriptome signatures in the iLINCS drug-repurposing database, identifying drugs, approved for other clinical indications, that were able to reverse in vitro the molecular changes associated with adverse prognosis in CHF.

CONCLUSION

Systematic modelling of the whole blood protein-coding transcriptome defined molecular pathways that provide a link between clinical risk factors and adverse CV prognosis in CHF, identifying both established and new potential therapeutic targets.

Minocycline treatment improves proteostasis during Drosophila aging via autophagy mediated by FOXO and Hsp70

Minocycline is a semi-synthetic tetracycline derivative antibiotic that has been examined for its non-antibiotic properties, such as anti-inflammatory, tumor-suppressive, and neuroprotective effects. In this study, we found that feeding minocycline to Drosophila improves proteostasis during organismal aging. Poly-ubiquitinated protein aggregates increase in the flight muscles as flies age, which are reduced in response to minocycline feeding. Minocycline feeding increases the expression of several autophagy genes and the activity of the autophagy/lysosomal pathway in Drosophila muscles. Interestingly, mutant flies lacking either FOXO or Hsp70 showed increased levels of poly-ubiquitinated protein aggregates with reduced autophagy/lysosomal activity, which was not reversed by minocycline feeding. Our findings suggest that minocycline may improve proteostasis in aging tissues via FOXO-Hsp70 axis, which highlights the multifaceted effects of minocycline as a therapeutic agent in age-associated features.

A comprehensive review on promising anti-viral therapeutic candidates identified against main protease from SARS-CoV-2 through various computational methods

Background

The COVID-19 pandemic caused by SARS-CoV-2 has shown an exponential trend of infected people across the planet. Crediting its virulent nature, it becomes imperative to identify potential therapeutic agents against the deadly virus. The 3-chymotrypsin-like protease (3CLpro) is a cysteine protease which causes the proteolysis of the replicase polyproteins to generate functional proteins, which is a crucial step for viral replication and infection. Computational methods have been applied in recent studies to identify promising inhibitors against 3CLpro to inhibit the viral activity.

Main body of the abstract

This review provides an overview of promising drug/lead candidates identified so far against 3CLpro through various in silico approaches such as structure-based virtual screening (SBVS), ligand-based virtual screening (LBVS) and drug-repurposing/drug-reprofiling/drug-retasking. Further, the drugs have been classified according to their chemical structures or biological activity into flavonoids, peptides, terpenes, quinolines, nucleoside and nucleotide analogues, protease inhibitors, phenalene and antibiotic derivatives. These are then individually discussed based on the various structural parameters namely estimated free energy of binding (ΔG), key interacting residues, types of intermolecular interactions and structural stability of 3CLpro-ligand complexes obtained from the results of molecular dynamics (MD) simulations.

Conclusion

The review provides comprehensive information of potential inhibitors identified through several computational methods thus far against 3CLpro from SARS-CoV-2 and provides a better understanding of their interaction patterns and dynamic states of free and ligand-bound 3CLpro structures.

Docking simulation between HIV peptidase inhibitors and Trypanosoma cruzi aspartyl peptidase

Objective

The low investment in research, diagnosis and treatment are factors that contribute to the continuity of Chagas’ disease as a neglected tropical diseases (NTDs). In this context, the repositioning of drugs represents a useful strategy, in the search for new chemotherapeutic approaches for NTDs. HIV aspartic peptidase inhibitors (HIV IPs) are good candidates for drug repurposing. Here, we modeled the three dimensional structure of an aspartyl peptidase of Trypanosoma cruzi, the causative agent of Chagas’ disease, aligned it to the HIV aspartyl peptidase and performed docking binding assays with the HIV PIs.

Results

The 3D structure confirmed the presence of acid aspartic residues, which are critical to enzyme activity. The docking experiment revealed that HIV IPs bind to the active site of the enzyme, being ritonavir and lopinavir the ones with greater affinity. Benznidazole presented the worst binding affinity, this drug is currently used in Chagas’ disease treatment and was included as negative control. These results together with previous data on the trypanocidal effect of the HIV PIs support the hypothesis that a T. cruzi aspartyl peptidase can be the intracellular target of these inhibitors. However, the direct demonstration of the inhibition of T. cruzi aspartyl peptidase activity by HIV PIs is still a goal to be persuaded.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3927-z) contains supplementary material, which is available to authorized users.

Repurposing Ivacaftor for treatment of Staphylococcus aureus infections

Drug repurposing of non-antimicrobials is a novel method to augment a seriously depleted drug pipeline for targeting drug-resistant pathogens. This article highlights the potent antimicrobial activity of Ivacaftor against Staphylococcus aureus, including vancomycin- and other multidrug-resistant strains. The potent activity of Ivacaftor in vivo is also demonstrated in a murine neutropenic thigh infection model. Taken together, these results support the potential of Ivacaftor as an antimicrobial agent for the treatment of staphylococcal infections.