C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms

Zebrafish drug screening identifies candidate therapies for neuroprotection after spontaneous intracerebral haemorrhage

Despite the global health burden, treatment of spontaneous intracerebral haemorrhage (ICH) is largely supportive and translation of specific medical therapies has not been successful. Zebrafish larvae offer a unique platform for drug screening to rapidly identify neuroprotective compounds following ICH. We applied the Spectrum Library compounds to zebrafish larvae acutely after ICH to screen for decreased brain cell death and identified 150 successful drugs. Candidates were then evaluated for possible indications with other cardiovascular diseases. Six compounds were identified including two angiotensin converting enzyme inhibitors (ACE-I). Ramipril and quinapril were further assessed to confirm a significant 55% reduction in brain cell death. Proteomic analysis revealed potential mechanisms of neuroprotection. Using the INTERACT2 clinical trial dataset, we demonstrate a significant reduction in the adjusted odds of an unfavourable shift in the modified Rankin Scale at 90 days for patients receiving an ACE-I after ICH (vs. no ACE-I; odds ratio 0.80; 95% confidence interval 0.68-0.95; P=0.009). The zebrafish larval model of spontaneous ICH can be used as a reliable drug screening platform, and has identified therapeutics which may offer neuroprotection.

Development and characterization of anti-fibrotic natural compound similars with improved effectivity

Cardiac fibroblasts constitute the major cell type of the murine and human heart. Once activated, they contribute to an excessive deposition of extracellular matrix (ECM) leading to cardiac fibrosis and subsequently organ dysfunction. With the exception of the pulmonary drugs, nintedanib and pirfenidone, drugs specifically targeting anti-fibrotic pathways are scarce. We recently performed large library screenings of natural occurring compounds and identified first lead structures with anti-fibrotic properties in vitro and in vivo. In line, we now aimed to improve efficacy of these anti-fibrotic lead structures by combining in vitro validation studies and in silico prediction. Next to this combined approach, we performed large OMICs-multi-panel-based mechanistic studies. Applying human cardiac fibroblasts (HCF), we analysed 26 similars of the initially identified anti-fibrotic lead molecules bufalin and lycorine and determined anti-proliferative activity and potential toxicity in an array of in vitro and ex vivo studies. Of note, even at lower concentrations, certain similars were more effective at inhibiting HCF proliferation than nintedanib and pirfenidone. Additionally, selected similars showed low cytotoxicity on human iPS-derived cardiomyocytes and anti-fibrotic gene regulation in human ex vivo living myocardial slices. Further, array and RNA sequencing studies of coding and non-coding RNAs in treated HCFs revealed strong anti-fibrotic properties, especially with the lycorine similar lyco-s (also known as homoharringtonine), that led to a nearly complete shutdown of ECM production at concentrations 100-fold lower than the previously identified anti-fibrotic compound lycorine without inducing cellular toxicity. We thus identified a new natural compound similar with strong anti-fibrotic properties in human cardiac fibroblasts and human living heart tissue potentially opening new anti-fibrotic treatment strategies.

Drug Discovery of Spinal Muscular Atrophy (SMA) from the Computational Perspective: A Comprehensive Review

Spinal muscular atrophy (SMA), one of the leading inherited causes of child mortality, is a rare neuromuscular disease arising from loss-of-function mutations of the survival motor neuron 1 (SMN1) gene, which encodes the SMN protein. When lacking the SMN protein in neurons, patients suffer from muscle weakness and atrophy, and in the severe cases, respiratory failure and death. Several therapeutic approaches show promise with human testing and three medications have been approved by the U.S. Food and Drug Administration (FDA) to date. Despite the shown promise of these approved therapies, there are some crucial limitations, one of the most important being the cost. The FDA-approved drugs are high-priced and are shortlisted among the most expensive treatments in the world. The price is still far beyond affordable and may serve as a burden for patients. The blooming of the biomedical data and advancement of computational approaches have opened new possibilities for SMA therapeutic development. This article highlights the present status of computationally aided approaches, including in silico drug repurposing, network driven drug discovery as well as artificial intelligence (AI)-assisted drug discovery, and discusses the future prospects.

Histone deacetylase (HDAC) inhibitors and doxorubicin combinations target both breast cancer stem cells and non-stem breast cancer cells simultaneously

PURPOSE

Breast cancer stem cells (CSCs) are a small subpopulation of cancer cells that have high capability for self-renewal, differentiation, and tumor initiation. CSCs are resistant to chemotherapy and radiotherapy, and are responsible for cancer recurrence and metastasis.

METHODS

By utilizing a panel of breast cancer cells and mammospheres culture as cell-based screening platforms, we performed high-throughput chemical library screens to identify agents that are effective against breast CSCs and non-CSCs. The hit molecules were paired with conventional chemotherapy to evaluate the combinatorial treatment effects on breast CSCs and non-CSCs.

RESULTS

We identified a total of 193 inhibitors that effectively targeting both breast CSCs and non-CSCs. We observed that histone deacetylase inhibitors (HDACi) synergized conventional chemotherapeutic agents (i.e., doxorubicin and cisplatin) in targeting breast CSCs and non-CSCs simultaneously. Further analyses revealed that quisinostat, a potent inhibitor for class I and II HDACs, potentiated doxorubicin-induced cytotoxicity in both breast CSCs and non-CSCs derived from the basal-like (MDA-MB-468 and HCC38), mesenchymal-like (MDA-MB-231), and luminal-like breast cancer (MCF-7). It was also observed that the basal-like breast CSCs and non-CSCs were more sensitive to the co-treatment of quisinostat with doxorubicin compared to that of the luminal-like breast cancer subtype.

CONCLUSION

In conclusion, this study demonstrates the potential of HDACi as therapeutic options, either as monotherapy or in combination with chemotherapeutics against refractory breast cancer.

Bioengineering tools for the production of pharmaceuticals: current perspective and future outlook

The bioengineering tools have significant advantages through less time-consuming and utilized as a promising stage for the production of pharmaceutical bioproducts under the single platform. This review highlighted the advantages and current improvement in the plant, animal and microbial bioengineering tools and outlines feasible approaches by biological and process's bioengineering levels for advancing the economic feasibility of pharmaceutical's production. The critical analysis results revealed that system biology and synthetic biology along with advanced bioengineering tools like transcriptome, proteome, metabolome and nano bioengineering tools have shown a promising impact on the development of pharmaceutical's bioproducts. Tools to overcome and resolve the accompanying encounters of pharmaceutical's production that include nano bioengineering tools are also discussed. As a summary and prospect, it also gives new insight into the challenges and possible breakthrough of the development of pharmaceutical's bioproducts through bioengineering tools.

Medium-Throughput Detection of Hsp90/Cdc37 Protein-Protein Interaction Inhibitors Using a Split Renilla Luciferase-Based Assay

The protein-folding chaperone Hsp90 enables the maturation and stability of various oncogenic signaling proteins and is thus pursued as a cancer drug target. Folding in particular of protein kinases is assisted by the co-chaperone Cdc37. Several inhibitors against the Hsp90 ATP-binding site have been developed. However, they displayed significant toxicity in clinical trials. By contrast, the natural product conglobatin A has an exceptionally low toxicity in mice. It targets the protein-protein interface (PPI) of Hsp90 and Cdc37, suggesting that interface inhibitors have an interesting drug development potential. In order to identify inhibitors of the Hsp90/Cdc37 PPI, we have established a mammalian cell lysate-based, medium-throughput amenable split Renilla luciferase assay. This assay employs N-terminal and C-terminal fragments of Renilla luciferase fused to full-length human Hsp90 and Cdc37, respectively. We expect that our assay will allow for the identification of novel Hsp90/Cdc37 interaction inhibitors. Such tool compounds will help to evaluate whether the toxicity profile of Hsp90/Cdc37 PPI inhibitors is in general more favorable than that of ATP-competitive Hsp90 inhibitors. Further development of such tool compounds may lead to new classes of Hsp90 inhibitors with applications in cancer and other diseases.

Defining subpopulations of differential drug response to reveal novel target populations

Personalised medicine has predominantly focused on genetically altered cancer genes that stratify drug responses, but there is a need to objectively evaluate differential pharmacology patterns at a subpopulation level. Here, we introduce an approach based on unsupervised machine learning to compare the pharmacological response relationships between 327 pairs of cancer therapies. This approach integrated multiple measures of response to identify subpopulations that react differently to inhibitors of the same or different targets to understand mechanisms of resistance and pathway cross-talk. MEK, BRAF, and PI3K inhibitors were shown to be effective as combination therapies for particular BRAF mutant subpopulations. A systematic analysis of preclinical data for a failed phase III trial of selumetinib combined with docetaxel in lung cancer suggests potential indications in pancreatic and colorectal cancers with KRAS mutation. This data-informed study exemplifies a method for stratified medicine to identify novel cancer subpopulations, their genetic biomarkers, and effective drug combinations.

Expanding the activity spectrum of antiviral agents

Broad-spectrum antivirals (BSAs) are agents that inhibit replication of several human viruses. Here, we review 108 approved, investigational, and experimental BSAs, for which safety profiles in humans are available. The most effective and tolerable BSAs could reinforce the arsenal of available antiviral therapeutics pending the results of further pre-clinical and clinical studies.

Computational Identification of Inhibitors Using QSAR Approach Against Nipah Virus

Nipah virus (NiV) caused several outbreaks in Asian countries including the latest one from Kerala state of India. There is no drug available against NiV till now, despite its urgent requirement. In the current study, we have provided a computational one-stop solution for NiV inhibitors. We have developed the first “anti-Nipah” web resource, which comprising of a data repository, prediction method, and data visualization module. The database contains of 313 (181 unique) chemicals extracted from research articles and patents, which were tested for different strains of NiV isolated from various outbreaks. Moreover, the quantitative structure–activity relationship (QSAR) based regression predictors were developed using chemicals having half maximal inhibitory concentration (IC₅₀). Predictive models were accomplished using support vector machine employing 10-fold cross validation technique. The overall predictor showed the Pearson's correlation coefficient of 0.82 on training/testing dataset. Likewise, it also performed equally well on the independent validation dataset. The robustness of the predictive model was confirmed by applicability domain (William's plot) and scatter plot between actual and predicted efficiencies. Further, the data visualization module from chemical clustering analysis displayed the diversity in the NiV inhibitors. Therefore, this web platform would be of immense help to the researchers working in developing effective inhibitors against NiV. The user-friendly web server is freely available on URL: http://bioinfo.imtech.res.in/manojk/antinipah/.

Novel activities of safe-in-human broad-spectrum antiviral agents

According to the WHO, there is an urgent need for better control of viral diseases. Re-positioning existing safe-in-human antiviral agents from one viral disease to another could play a pivotal role in this process. Here, we reviewed all approved, investigational and experimental antiviral agents, which are safe in man, and identified 59 compounds that target at least three viral diseases. We tested 55 of these compounds against eight different RNA and DNA viruses. We found novel activities for dalbavancin against echovirus 1, ezetimibe against human immunodeficiency virus 1 and Zika virus, as well as azacitidine, cyclosporine, minocycline, oritavancin and ritonavir against Rift valley fever virus. Thus, the spectrum of antiviral activities of existing antiviral agents could be expanded towards other viral diseases.

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339 approved, investigational and experimental safe-in-human antivirals were identified.

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59 compounds, which target ≥3 viral diseases, were selected.

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55 of the 59 compounds were tested against 8 RNA and DNA viruses.

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7 compounds were found to possess novel antiviral activities.

Drug Target Commons 2.0: a community platform for systematic analysis of drug-target interaction profiles

Drug Target Commons (DTC) is a web platform (database with user interface) for community-driven bioactivity data integration and standardization for comprehensive mapping, reuse and analysis of compound-target interaction profiles. End users can search, upload, edit, annotate and export expert-curated bioactivity data for further analysis, using an application programmable interface, database dump or tab-delimited text download options. To guide chemical biology and drug-repurposing applications, DTC version 2.0 includes updated clinical development information for the compounds and target gene-disease associations, as well as cancer-type indications for mutant protein targets, which are critical for precision oncology developments.

Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions

Knowledge of the full target space of bioactive substances, approved and investigational drugs as well as chemical probes, provides important insights into therapeutic potential and possible adverse effects. The existing compound-target bioactivity data resources are often incomparable due to non-standardized and heterogeneous assay types and variability in endpoint measurements. To extract higher value from the existing and future compound target-profiling data, we implemented an open-data web platform, named Drug Target Commons (DTC), which features tools for crowd-sourced compound-target bioactivity data annotation, standardization, curation, and intra-resource integration. We demonstrate the unique value of DTC with several examples related to both drug discovery and drug repurposing applications and invite researchers to join this community effort to increase the reuse and extension of compound bioactivity data.

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DTC is a crowd-sourcing-based web platform to annotate drug-target bioactivity data

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The open environment improves data harmonization for drug repurposing applications

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DTC offers a comprehensive, reproducible, and sustainable bioactivity knowledge base