Drug repurposing screening validated by experimental assays identifies two clinical drugs targeting SARS-CoV-2 main protease

The COVID-19 pandemic prompted several drug repositioning initiatives with the aim to rapidly deliver pharmacological candidates able to reduce SARSCoV- 2 dissemination and mortality. A major issue shared by many of the in silico studies addressing the discovery of compounds or drugs targeting SARS-CoV- 2 molecules is that they lacked experimental validation of the results. Here we present a computer-aided drug-repositioning campaign against the indispensable SARS-CoV-2 main protease (MPro or 3CLPro) that involved the development of ligand-based ensemble models and the experimental testing of a small subset of the identified hits. The search method explored random subspaces of molecular descriptors to obtain linear classifiers. The best models were then combined by selective ensemble learning to improve their predictive power. Both the individual models and the ensembles were validated by retrospective screening, and later used to screen the DrugBank, Drug Repurposing Hub and Sweetlead libraries for potential inhibitors of MPro. From the 4 in silico hits assayed, atpenin and tinostamustine inhibited MPro (IC50 1 μM and 4 μM, respectively) but not the papain-like protease of SARSCoV- 2 (drugs tested at 25 μM). Preliminary kinetic characterization suggests that tinostamustine and atpenin inhibit MPro by an irreversible and acompetitive mechanisms, respectively. Both drugs failed to inhibit the proliferation of SARSCoV- 2 in VERO cells. The virtual screening method reported here may be a powerful tool to further extent the identification of novel MPro inhibitors. Furthermore, the confirmed MPro hits may be subjected to optimization or retrospective search strategies to improve their molecular target and anti-viral potency.Laboratorio de Investigación y Desarrollo de Bioactivo

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis

New therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of multidrug-resistant (MDR) and extensively drug-resistant (XDR) forms of the disease, which remain a serious public health challenge worldwide1, 2. The most urgent clinical need is to discover potent agents capable of reducing the duration of MDR and XDR tuberculosis therapy with a success rate comparable to that of current therapies for drug-susceptible tuberculosis. The last decade has seen the discovery of new agent classes for the management of tuberculosis3, 4, 5, several of which are currently in clinical trials6, 7, 8. However, given the high attrition rate of drug candidates during clinical development and the emergence of drug resistance, the discovery of additional clinical candidates is clearly needed. Here, we report on a promising class of imidazopyridine amide (IPA) compounds that block Mycobacterium tuberculosis growth by targeting the respiratory cytochrome bc1 complex. The optimized IPA compound Q203 inhibited the growth of MDR and XDR M. tuberculosis clinical isolates in culture broth medium in the low nanomolar range and was efficacious in a mouse model of tuberculosis at a dose less than 1 mg per kg body weight, which highlights the potency of this compound. In addition, Q203 displays pharmacokinetic and safety profiles compatible with once-daily dosing. Together, our data indicate that Q203 is a promising new clinical candidate for the treatment of tuberculosis

Garbage in, garbage out: how reliable training data improved a virtual screening approach against SARS-CoV-2 MPro

Introduction: The identification of chemical compounds that interfere with SARS-CoV-2 replication continues to be a priority in several academic and pharmaceutical laboratories. Computational tools and approaches have the power to integrate, process and analyze multiple data in a short time. However, these initiatives may yield unrealistic results if the applied models are not inferred from reliable data and the resulting predictions are not confirmed by experimental evidence.Methods: We undertook a drug discovery campaign against the essential major protease (MPro) from SARS-CoV-2, which relied on an in silico search strategy –performed in a large and diverse chemolibrary– complemented by experimental validation. The computational method comprises a recently reported ligand-based approach developed upon refinement/learning cycles, and structure-based approximations. Search models were applied to both retrospective (in silico) and prospective (experimentally confirmed) screening.Results: The first generation of ligand-based models were fed by data, which to a great extent, had not been published in peer-reviewed articles. The first screening campaign performed with 188 compounds (46 in silico hits and 100 analogues, and 40 unrelated compounds: flavonols and pyrazoles) yielded three hits against MPro (IC50 ≤ 25 μM): two analogues of in silico hits (one glycoside and one benzo-thiazol) and one flavonol. A second generation of ligand-based models was developed based on this negative information and newly published peer-reviewed data for MPro inhibitors. This led to 43 new hit candidates belonging to different chemical families. From 45 compounds (28 in silico hits and 17 related analogues) tested in the second screening campaign, eight inhibited MPro with IC50 = 0.12–20 μM and five of them also impaired the proliferation of SARS-CoV-2 in Vero cells (EC50 7–45 μM).Discussion: Our study provides an example of a virtuous loop between computational and experimental approaches applied to target-focused drug discovery against a major and global pathogen, reaffirming the well-known “garbage in, garbage out” machine learning principle

Repurposing Eltrombopag for Multidrug Resistant Staphylococcus aureus Infections

The continuous rise of antimicrobial resistance urgently demands new therapeutic agents for human health. Drug repurposing is an attractive strategy that could significantly save time delivering new antibiotics to clinics. We screened 182 US Food and Drug Administration (FDA)-approved drugs to identify potential antibiotic candidates against Staphylococcus aureus, a major pathogenic bacterium. This screening revealed the significant antibacterial activity of three small molecule drugs against S. aureus: (1) LDK378 (Ceritinib), an anaplastic lymphoma kinase (ALK) inhibitor for the treatment of lung cancer, (2) dronedarone HCl, an antiarrhythmic drug for the treatment of atrial fibrillation, and (3) eltrombopag, a thrombopoietin receptor agonist for the treatment of thrombocytopenia. Among these, eltrombopag showed the highest potency against not only a drug-sensitive S. aureus strain but also 55 clinical isolates including 35 methicillin-resistant S. aureus (Minimum inhibitory concentration, MIC, to inhibit 50% growth [MIC50] = 1.4–3.2 mg/L). Furthermore, we showed that eltrombopag inhibited bacterial growth in a cell infection model and reduced bacterial loads in infected mice, demonstrating its potential as a new antibiotic agent against S. aureus that can overcome current antibiotic resistance

Dimerization, Oligomerization, and Aggregation of Human Amyotrophic Lateral Sclerosis Copper/Zinc Superoxide Dismutase 1 Protein Mutant Forms in Live Cells

International audienceBackground: Copper/zinc superoxide dismutase (SOD1) genetic mutants are associated with familial amyotrophic lateral sclerosis (ALS). Mutant proteins form abnormal aggregates. Results: We used imaging of live cells to observe SOD1 proteins harboring mutations associated with ALS. Conclusion: SOD1 mutations impair its dimerization, leading to subsequent aggregation. Significance: Analysis of the SOD1 quaternary structure in living human cells correlates with previous biochemical data

High-throughput screening of small-molecules libraries identified antibacterials against clinically relevant multidrug-resistant A. baumannii and K. pneumoniaeResearch in context

Summary: Background: The current pipeline for new antibiotics fails to fully address the significant threat posed by drug-resistant Gram-negative bacteria that have been identified by the World Health Organization (WHO) as a global health priority. New antibacterials acting through novel mechanisms of action are urgently needed. We aimed to identify new chemical entities (NCEs) with activity against Klebsiella pneumoniae and Acinetobacter baumannii that could be developed into a new treatment for drug-resistant infections. Methods: We developed a high-throughput phenotypic screen and selection cascade for generation of hit compounds active against multidrug-resistant (MDR) strains of K. pneumoniae and A. baumannii. We screened compound libraries selected from the proprietary collections of three pharmaceutical companies that had exited antibacterial drug discovery but continued to accumulate new compounds to their collection. Compounds from two out of three libraries were selected using “eNTRy rules” criteria associated with increased likelihood of intracellular accumulation in Escherichia coli. Findings: We identified 72 compounds with confirmed activity against K. pneumoniae and/or drug-resistant A. baumannii. Two new chemical series with activity against XDR A. baumannii were identified meeting our criteria of potency (EC50 ≤50 μM) and absence of cytotoxicity (HepG2 CC50 ≥100 μM and red blood cell lysis HC50 ≥100 μM). The activity of close analogues of the two chemical series was also determined against A. baumannii clinical isolates. Interpretation: This work provides proof of principle for the screening strategy developed to identify NCEs with antibacterial activity against multidrug-resistant critical priority pathogens such as K. pneumoniae and A. baumannii. The screening and hit selection cascade established here provide an excellent foundation for further screening of new compound libraries to identify high quality starting points for new antibacterial lead generation projects. Funding: BMBF and GARDP

Discovery of Q203, a potent clinical candidate for the treatment of tuberculosis.

New prophylactic and therapeutic strategies are needed to combat the tuberculosis pandemic and the spread of extensively-drug resistant form of the disease. During the course of a high-content chemical screen, ImidazoPyridine Amides (IPA) were identified as a promising class of anti-tubercular agents. The optimized IPA compound Q203 inhibits the growth of multi- and extensively-drug resistant clinical isolates of M. tuberculosis in the low nanomolar range. Q203 was efficacious in vivo at a dose below 1mg/kg, making this compound one of the most potent discovered up to date. In addition, it shows pharmacokinetic and safety profiles compatible with once daily dosing. A reverse genetic approach identifies the ubiquinol cytochrome C reductase (QcrB, Rv2196) as the target of Q203. Mode of action studies revealed that Q203 inhibits the process of ATP synthesis in both replicating and hypoxic non-replicating M. tuberculosis. Altogether, our data indicates that Q203 is a promising clinical candidate for the treatment of tuberculosis

Extreme Yield Figures for Universal Strength Criteria

We propose a universal, generally applicable yield criterion that describes a single convex surface in principal stress space encompassing extreme yield figures as convexity limits. The novel criterion is derived phenomenologically exploiting geometrical properties of yield surfaces in principal stress space. It is systematically compared with known yield criteria using different forms of visualization. Using a I1-substitution the criterion is applicable to materials with pressure-sensitive behavior and contains well-known strength criteria. Introducing appropriate parameter restrictions, it can be applied for the modeling of ductile and brittle material behavior. The implementation of the present criterion eliminates the necessity of choosing a specific yield criterion for a particular material. The proposed criterion allows for excellent approximation of experimental data. It is applied to measured data of concrete and provides better accuracy than existing criteria from literature