Drug repurposing screen to identify inhibitors of the RNA polymerase (nsp12) and helicase (nsp13) from SARS-CoV-2 replication and transcription complex.

Coronaviruses contain one of the largest genomes among the RNA viruses, coding for 14-16 non-structural proteins (nsp) that are involved in proteolytic processing, genome replication and transcription, and four structural proteins that build the core of the mature virion. Due to conservation across coronaviruses, nsps form a group of promising drug targets as their inhibition directly affects viral replication and, therefore, progression of infection. A minimal but fully functional replication and transcription complex was shown to be formed by one RNA-dependent RNA polymerase (nsp12), one nsp7, two nsp8 accessory subunits, and two helicase (nsp13) enzymes. Our approach involved, targeting nsp12 and nsp13 to allow multiple starting point to interfere with virus infection progression. Here we report a combined in-vitro repurposing screening approach, identifying new and confirming reported SARS-CoV-2 nsp12 and nsp13 inhibitors.

Limited high-throughput screening compatibility of the phenuivirus cap-binding domain.

Bunyaviruses constitute a large and diverse group of viruses encompassing many emerging pathogens, such as Rift Valley fever virus (family Phenuiviridae), with public and veterinary health relevance but with very limited medical countermeasures are available. For the development of antiviral strategies, the identification and validation of virus-specific targets would be of high value. The cap-snatching mechanism is an essential process in the life cycle of bunyaviruses to produce capped mRNAs, which are then recognized and translated into viral proteins by the host cell translation machinery. Cap-snatching involves cap-binding as well as endonuclease functions and both activities have been demonstrated to be druggable in related influenza viruses. Here, we explore the suitability of the phenuivirus cap-binding function as a target in medium- and high-throughput drug discovery approaches. We developed a range of in vitro assays aiming to detect the interaction between the cap-binding domain (CBD) and the analogue of its natural cap-ligand m7GTP. However, constricted by its shallow binding pocket and low affinity for m7GTP, we conclude that the CBD has limited small molecule targeting potential using classical in vitro drug discovery approaches.

Drug repurposing for the treatment of COVID-19: Targeting nafamostat to the lungs by a liposomal delivery system.

Despite tremendous global efforts since the beginning of the COVID-19 pandemic, still only a limited number of prophylactic and therapeutic options are available. Although vaccination is the most effective measure in preventing morbidity and mortality, there is a need for safe and effective post-infection treatment medication. In this study, we explored a pipeline of 21 potential candidates, examined in the Calu-3 cell line for their antiviral efficacy, for drug repurposing. Ralimetinib and nafamostat, clinically used drugs, have emerged as attractive candidates. Due to the inherent limitations of the selected drugs, we formulated targeted liposomes suitable for both systemic and intranasal administration. Non-targeted and targeted nafamostat liposomes (LipNaf) decorated with an Apolipoprotein B peptide (ApoB-P) as a specific lung-targeting ligand were successfully developed. The developed liposomal formulations of nafamostat were found to possess favorable physicochemical properties including nano size (119-147 nm), long-term stability of the normally rapidly degrading compound in aqueous solution, negligible leakage from the liposomes upon storage, and a neutral surface charge with low polydispersity index (PDI). Both nafamostat and ralimetinib liposomes showed good cellular uptake and lack of cytotoxicity, and non-targeted LipNaf demonstrated enhanced accumulation in the lungs following intranasal (IN) administration in non-infected mice. LipNaf retained its anti-SARS-CoV 2 activity in Calu 3 cells with only a modest decrease, exhibiting complete inhibition at concentrations >100 nM. IN, but not intraperitoneal (IP) treatment with targeted LipNaf resulted in a trend to reduced viral load in the lungs of K18-hACE2 mice compared to targeted empty Lip. Nevertheless, upon removal of outlier data, a statistically significant 1.9-fold reduction in viral load was achieved. This observation further highlights the importance of a targeted delivery into the respiratory tract. In summary, we were able to demonstrate a proof-of-concept of drug repurposing by liposomal formulations with anti-SARS-CoV-2 activity. The biodistribution and bioactivity studies with LipNaf suggest an IN or inhalation route of administration for optimal therapeutic efficacy.

ADAMTS-7 Modulates Atherosclerotic Plaque Formation by Degradation of TIMP-1.

BACKGROUND: The ADAMTS7 locus was genome-wide significantly associated with coronary artery disease. Lack of the ECM (extracellular matrix) protease ADAMTS-7 (A disintegrin and metalloproteinase-7) was shown to reduce atherosclerotic plaque formation. Here, we sought to identify molecular mechanisms and downstream targets of ADAMTS-7 mediating the risk of atherosclerosis. METHODS: Targets of ADAMTS-7 were identified by high-resolution mass spectrometry of atherosclerotic plaques from Apoe-/- and Apoe-/-Adamts7-/- mice. ECM proteins were identified using solubility profiling. Putative targets were validated using immunofluorescence, in vitro degradation assays, coimmunoprecipitation, and Förster resonance energy transfer-based protein-protein interaction assays. ADAMTS7 expression was measured in fibrous caps of human carotid artery plaques. RESULTS: In humans, ADAMTS7 expression was higher in caps of unstable as compared to stable carotid plaques. Compared to Apoe-/- mice, atherosclerotic aortas of Apoe-/- mice lacking Adamts-7 (Apoe-/-Adamts7-/-) contained higher protein levels of Timp-1 (tissue inhibitor of metalloprotease-1). In coimmunoprecipitation experiments, the catalytic domain of ADAMTS-7 bound to TIMP-1, which was degraded in the presence of ADAMTS-7 in vitro. ADAMTS-7 reduced the inhibitory capacity of TIMP-1 at its canonical target MMP-9 (matrix metalloprotease-9). As a downstream mechanism, we investigated collagen content in plaques of Apoe-/- and Apoe-/-Adamts7-/- mice after a Western diet. Picrosirius red staining of the aortic root revealed less collagen as a readout of higher MMP-9 activity in Apoe-/- as compared to Apoe-/- Adamts7-/- mice. To facilitate high-throughput screening for ADAMTS-7 inhibitors with the aim of decreasing TIMP-1 degradation, we designed a Förster resonance energy transfer-based assay targeting the ADAMTS-7 catalytic site. CONCLUSIONS: ADAMTS-7, which is induced in unstable atherosclerotic plaques, decreases TIMP-1 stability reducing its inhibitory effect on MMP-9, which is known to promote collagen degradation and is likewise associated with coronary artery disease. Disrupting the interaction of ADAMTS-7 and TIMP-1 might be a strategy to increase collagen content and plaque stability for the reduction of atherosclerosis-related events.

Pharmacophore-Based Machine Learning Model To Predict Ligand Selectivity for E3 Ligase Binders.

E3 ligases are enzymes that play a critical role in ubiquitin-mediated protein degradation and are involved in various cellular processes. Pharmacophore analysis is a useful approach for predicting E3 ligase binding selectivity, which involves identifying key chemical features necessary for a ligand to interact with a specific protein target cavity. While pharmacophore analysis is not always sufficient to accurately predict ligand binding affinity, it can be a valuable tool for filtering and/or designing focused libraries for screening campaigns. In this study, we present a fast and an inexpensive approach using a pharmacophore fingerprinting scheme known as ErG, which is used in a multi-class machine learning classification model. This model can assign the correct E3 ligase binder to its known E3 ligase and predict the probability of each molecule to bind to different E3 ligases. Practical applications of this approach are demonstrated on commercial libraries such as Asinex for the rational design of E3 ligase binders. The scripts and data associated with this study can be found on GitHub at https://github.com/Fraunhofer-ITMP/E3_binder_Model.

FAIR in action - a flexible framework to guide FAIRification.

The COVID-19 pandemic has highlighted the need for FAIR (Findable, Accessible, Interoperable, and Reusable) data more than any other scientific challenge to date. We developed a flexible, multi-level, domain-agnostic FAIRification framework, providing practical guidance to improve the FAIRness for both existing and future clinical and molecular datasets. We validated the framework in collaboration with several major public-private partnership projects, demonstrating and delivering improvements across all aspects of FAIR and across a variety of datasets and their contexts. We therefore managed to establish the reproducibility and far-reaching applicability of our approach to FAIRification tasks.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The notion that data should be Findable, Accessible, Interoperable and Reusable, according to the FAIR Principles, has become a global norm for good data stewardship and a prerequisite for reproducibility. Nowadays, FAIR guides data policy actions and professional practices in the public and private sectors. Despite such global endorsements, however, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an open, online resource of hands-on recipes for "FAIR doers" in the Life Sciences. Created by researchers and data managers professionals in academia, (bio)pharmaceutical companies and information service industries, the FAIR Cookbook covers the key steps in a FAIRification journey, the levels and indicators of FAIRness, the maturity model, the technologies, the tools and the standards available, as well as the skills required, and the challenges to achieve and improve data FAIRness. Part of the ELIXIR ecosystem, and recommended by funders, the FAIR Cookbook is open to contributions of new recipes.

Mpox Knowledge Graph: a comprehensive representation embedding chemical entities and associated biology of Mpox.

Summary: The outbreak of Mpox virus (MPXV) infection in May 2022 is declared a global health emergency by WHO. A total of 84 330 cases have been confirmed as of 5 January 2023 and the numbers are on the rise. The MPXV pathophysiology and its underlying mechanisms are unfortunately not yet understood. Likewise, the knowledge of biochemicals and drugs used against MPXV and their downstream effects is sparse. In this work, using Knowledge Graph (KG) representations we have depicted chemical and biological aspects of MPXV. To achieve this, we have collected and rationally assembled several biological study results, assays, drug candidates and pre-clinical evidence to form a dynamic and comprehensive network. The KG is compliant with FAIR annotations allowing seamless transformation and integration to/with other formats and infrastructures. Availability and implementation: The programmatic scripts for Mpox KG are publicly available at https://github.com/Fraunhofer-ITMP/mpox-kg. It is hosted publicly at https://doi.org/10.18119/N9SG7D. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

DHFR Inhibitors Display a Pleiotropic Anti-Viral Activity against SARS-CoV-2: Insights into the Mechanisms of Action.

During the COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Based on previous data on methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly attributed to the intrinsic anti-metabolic activity of these drugs, but also to a specific anti-viral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, pralatrexate and trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.

Validation of TREK1 ion channel activators as an immunomodulatory and neuroprotective strategy in neuroinflammation.

Modulation of two-pore domain potassium (K2P) channels has emerged as a novel field of therapeutic strategies as they may regulate immune cell activation and metabolism, inflammatory signals, or barrier integrity. One of these ion channels is the TWIK-related potassium channel 1 (TREK1). In the current study, we report the identification and validation of new TREK1 activators. Firstly, we used a modified potassium ion channel assay to perform high-throughput-screening of new TREK1 activators. Dose-response studies helped to identify compounds with a high separation between effectiveness and toxicity. Inside-out patch-clamp measurements of Xenopus laevis oocytes expressing TREK1 were used for further validation of these activators regarding specificity and activity. These approaches yielded three substances, E1, B3 and A2 that robustly activate TREK1. Functionally, we demonstrated that these compounds reduce levels of adhesion molecules on primary human brain and muscle endothelial cells without affecting cell viability. Finally, we studied compound A2 via voltage-clamp recordings as this activator displayed the strongest effect on adhesion molecules. Interestingly, A2 lacked TREK1 activation in the tested neuronal cell type. Taken together, this study provides data on novel TREK1 activators that might be employed to pharmacologically modulate TREK1 activity.

PEMT: a patent enrichment tool for drug discovery.

MOTIVATION: Drug discovery practitioners in industry and academia use semantic tools to extract information from online scientific literature to generate new insights into targets, therapeutics and diseases. However, due to complexities in access and analysis, patent-based literature is often overlooked as a source of information. As drug discovery is a highly competitive field, naturally, tools that tap into patent literature can provide any actor in the field an advantage in terms of better informed decision-making. Hence, we aim to facilitate access to patent literature through the creation of an automatic tool for extracting information from patents described in existing public resources. RESULTS: Here, we present PEMT, a novel patent enrichment tool, that takes advantage of public databases like ChEMBL and SureChEMBL to extract relevant patent information linked to chemical structures and/or gene names described through FAIR principles and metadata annotations. PEMT aims at supporting drug discovery and research by establishing a patent landscape around genes of interest. The pharmaceutical focus of the tool is mainly due to the subselection of International Patent Classification codes, but in principle, it can be used for other patent fields, provided that a link between a concept and chemical structure is investigated. Finally, we demonstrate a use-case in rare diseases by generating a gene-patent list based on the epidemiological prevalence of these diseases and exploring their underlying patent landscapes. AVAILABILITY AND IMPLEMENTATION: PEMT is an open-source Python tool and its source code and PyPi package are available at https://github.com/Fraunhofer-ITMP/PEMT and https://pypi.org/project/PEMT/, respectively. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Easy access to α-ketoamides as SARS-CoV-2 and MERS Mpro inhibitors via the PADAM oxidation route.

SARS-CoV-2 caused worldwide the current outbreak called COVID-19. Despite multiple countermeasures implemented, there is an urgent global need for new potent and efficient antiviral drugs against this pathogen. In this context, the main protease (Mpro) of SARS-CoV-2 is an essential viral enzyme and plays a pivotal role in viral replication and transcription. Its specific cleavage of polypeptides after a glutamine residue has been considered as a key element to design novel antiviral drugs. Herein, we reported the design, synthesis and structure-activity relationships of novel α-ketoamides as covalent reversible inhibitors of Mpro, exploiting the PADAM oxidation route. The reported compounds showed µM to nM activities in enzymatic and in the antiviral cell-based assays against SARS-CoV-2 Mpro. In order to assess inhibitors' binding mode, two co-crystal structures of SARS-CoV-2 Mpro in complex with our inhibitors were solved, which confirmed the covalent binding of the keto amide moiety to the catalytic Cys145 residue of Mpro. Finally, in order to interrogate potential broad-spectrum properties, we assessed a selection of compounds against MERS Mpro where they showed nM inhibitory potency, thus highlighting their potential as broad-spectrum coronavirus inhibitors.

Comprehensive Fragment Screening of the SARS-CoV-2 Proteome Explores Novel Chemical Space for Drug Development.

SARS-CoV-2 (SCoV2) and its variants of concern pose serious challenges to the public health. The variants increased challenges to vaccines, thus necessitating for development of new intervention strategies including anti-virals. Within the international Covid19-NMR consortium, we have identified binders targeting the RNA genome of SCoV2. We established protocols for the production and NMR characterization of more than 80 % of all SCoV2 proteins. Here, we performed an NMR screening using a fragment library for binding to 25 SCoV2 proteins and identified hits also against previously unexplored SCoV2 proteins. Computational mapping was used to predict binding sites and identify functional moieties (chemotypes) of the ligands occupying these pockets. Striking consensus was observed between NMR-detected binding sites of the main protease and the computational procedure. Our investigation provides novel structural and chemical space for structure-based drug design against the SCoV2 proteome.

Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections.

The rise in antimicrobial resistance (AMR), and increase in treatment-refractory AMR infections, generates an urgent need to accelerate the discovery and development of novel anti-infectives. Preclinical animal models play a crucial role in assessing the efficacy of novel drugs, informing human dosing regimens and progressing drug candidates into the clinic. The Innovative Medicines Initiative-funded "Collaboration for prevention and treatment of MDR bacterial infections" (COMBINE) consortium is establishing a validated and globally harmonized preclinical model to increase reproducibility and more reliably translate results from animals to humans. Toward this goal, in April 2021, COMBINE organized the expert workshop "Advancing toward a standardized murine model to evaluate treatments for AMR lung infections". This workshop explored the conduct and interpretation of mouse infection models, with presentations on PK/PD and efficacy studies of small molecule antibiotics, combination treatments (ß-lactam/ß-lactamase inhibitor), bacteriophage therapy, monoclonal antibodies and iron sequestering molecules, with a focus on the major Gram-negative AMR respiratory pathogens Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii. Here we summarize the factors of variability that we identified in murine lung infection models used for antimicrobial efficacy testing, as well as the workshop presentations, panel discussions and the survey results for the harmonization of key experimental parameters. The resulting recommendations for standard design parameters are presented in this document and will provide the basis for the development of a harmonized and bench-marked efficacy studies in preclinical murine pneumonia model.

Variability of murine bacterial pneumonia models used to evaluate antimicrobial agents.

Antimicrobial resistance has become one of the greatest threats to human health, and new antibacterial treatments are urgently needed. As a tool to develop novel therapies, animal models are essential to bridge the gap between preclinical and clinical research. However, despite common usage of in vivo models that mimic clinical infection, translational challenges remain high. Standardization of in vivo models is deemed necessary to improve the robustness and reproducibility of preclinical studies and thus translational research. The European Innovative Medicines Initiative (IMI)-funded "Collaboration for prevention and treatment of MDR bacterial infections" (COMBINE) consortium, aims to develop a standardized, quality-controlled murine pneumonia model for preclinical efficacy testing of novel anti-infective candidates and to improve tools for the translation of preclinical data to the clinic. In this review of murine pneumonia model data published in the last 10 years, we present our findings of considerable variability in the protocols employed for testing the efficacy of antimicrobial compounds using this in vivo model. Based on specific inclusion criteria, fifty-three studies focusing on antimicrobial assessment against Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii were reviewed in detail. The data revealed marked differences in the experimental design of the murine pneumonia models employed in the literature. Notably, several differences were observed in variables that are expected to impact the obtained results, such as the immune status of the animals, the age, infection route and sample processing, highlighting the necessity of a standardized model.

Cytopathic SARS-CoV-2 screening on VERO-E6 cells in a large-scale repurposing effort.

Worldwide, there are intensive efforts to identify repurposed drugs as potential therapies against SARS-CoV-2 infection and the associated COVID-19 disease. To date, the anti-inflammatory drug dexamethasone and (to a lesser extent) the RNA-polymerase inhibitor remdesivir have been shown to be effective in reducing mortality and patient time to recovery, respectively, in patients. Here, we report the results of a phenotypic screening campaign within an EU-funded project (H2020-EXSCALATE4COV) aimed at extending the repertoire of anti-COVID therapeutics through repurposing of available compounds and highlighting compounds with new mechanisms of action against viral infection. We screened 8702 molecules from different repurposing libraries, to reveal 110 compounds with an anti-cytopathic IC50 < 20 µM. From this group, 18 with a safety index greater than 2 are also marketed drugs, making them suitable for further study as potential therapies against COVID-19. Our result supports the idea that a systematic approach to repurposing is a valid strategy to accelerate the necessary drug discovery process.

Selection of data sets for FAIRification in drug discovery and development: Which, why, and how?

Despite the intuitive value of adopting the Findable, Accessible, Interoperable, and Reusable (FAIR) principles in both academic and industrial sectors, challenges exist in resourcing, balancing long- versus short-term priorities, and achieving technical implementation. This situation is exacerbated by the unclear mechanisms by which costs and benefits can be assessed when decisions on FAIR are made. Scientific and research and development (R&D) leadership need reliable evidence of the potential benefits and information on effective implementation mechanisms and remediating strategies. In this article, we describe procedures for cost-benefit evaluation, and identify best-practice approaches to support the decision-making process involved in FAIR implementation.

Natural Compounds Inhibit SARS-CoV-2 nsp13 Unwinding and ATPase Enzyme Activities.

SARS-CoV-2 infection is still spreading worldwide, and new antiviral therapies are an urgent need to complement the approved vaccine preparations. SARS-CoV-2 nps13 helicase is a validated drug target participating in the viral replication complex and possessing two associated activities: RNA unwinding and 5'-triphosphatase. In the search of SARS-CoV-2 direct antiviral agents, we established biochemical assays for both SARS-CoV-2 nps13-associated enzyme activities and screened both in silico and in vitro a small in-house library of natural compounds. Myricetin, quercetin, kaempferol, and flavanone were found to inhibit the SARS-CoV-2 nps13 unwinding activity at nanomolar concentrations, while licoflavone C was shown to block both SARS-CoV-2 nps13 activities at micromolar concentrations. Mode of action studies showed that all compounds are nsp13 noncompetitive inhibitors versus ATP, while computational studies suggested that they can bind both nucleotide and 5'-RNA nsp13 binding sites, with licoflavone C showing a unique pattern of interaction with nsp13 amino acid residues. Overall, we report for the first time natural flavonoids as selective inhibitors of SARS-CoV-2 nps13 helicase with low micromolar activity.

Drug Repurposing to Target Neuroinflammation and Sensory Neuron-Dependent Pain.

Around 20% of the American population have chronic pain and estimates in other Western countries report similar numbers. This represents a major challenge for global health care systems. Additional problems for the treatment of chronic and persistent pain are the comparably low efficacy of existing therapies, the failure to translate effects observed in preclinical pain models to human patients and related setbacks in clinical trials from previous attempts to develop novel analgesics. Drug repurposing offers an alternative approach to identify novel analgesics as it can bypass various steps of classical drug development. In recent years, several approved drugs were attributed analgesic properties. Here, we review available data and discuss recent findings suggesting that the approved drugs minocycline, fingolimod, pioglitazone, nilotinib, telmisartan, and others, which were originally developed for the treatment of different pathologies, can have analgesic, antihyperalgesic, or neuroprotective effects in preclinical and clinical models of inflammatory or neuropathic pain. For our analysis, we subdivide the drugs into substances that can target neuroinflammation or substances that can act on peripheral sensory neurons, and highlight the proposed mechanisms. Finally, we discuss the merits and challenges of drug repurposing for the development of novel analgesics.

Ibuprofen, Flurbiprofen, Etoricoxib or Paracetamol Do Not Influence ACE2 Expression and Activity In Vitro or in Mice and Do Not Exacerbate In-Vitro SARS-CoV-2 Infection.

SARS-CoV-2 uses the human cell surface protein angiotensin converting enzyme 2 (ACE2) as the receptor by which it gains access into lung and other tissue. Early in the pandemic, there was speculation that a number of commonly used medications-including ibuprofen and other non-steroidal anti-inflammatory drugs (NSAIDs)-have the potential to upregulate ACE2, thereby possibly facilitating viral entry and increasing the severity of COVID-19. We investigated the influence of the NSAIDS with a range of cyclooxygenase (COX)1 and COX2 selectivity (ibuprofen, flurbiprofen, etoricoxib) and paracetamol on the level of ACE2 mRNA/protein expression and activity as well as their influence on SARS-CoV-2 infection levels in a Caco-2 cell model. We also analysed the ACE2 mRNA/protein levels and activity in lung, heart and aorta in ibuprofen treated mice. The drugs had no effect on ACE2 mRNA/protein expression and activity in the Caco-2 cell model. There was no up-regulation of ACE2 mRNA/protein expression and activity in lung, heart and aorta tissue in ibuprofen-treated mice in comparison to untreated mice. Viral load was significantly reduced by both flurbiprofen and ibuprofen at high concentrations. Ibuprofen, flurbiprofen, etoricoxib and paracetamol demonstrated no effects on ACE2 expression or activity in vitro or in vivo. Higher concentrations of ibuprofen and flurbiprofen reduced SARS-CoV-2 replication in vitro.