Machine learning-aided search for ligands of P2Y6 and other P2Y receptors.

The P2Y6 receptor, activated by uridine diphosphate (UDP), is a target for antagonists in inflammatory, neurodegenerative, and metabolic disorders, yet few potent and selective antagonists are known to date. This prompted us to use machine learning as a novel approach to aid ligand discovery, with pharmacological evaluation at three P2YR subtypes: initially P2Y6 and subsequently P2Y1 and P2Y14. Relying on extensive published data for P2Y6R agonists, we generated and validated an array of classification machine learning model using the algorithms deep learning (DL), adaboost classifier (ada), Bernoulli NB (bnb), k-nearest neighbors (kNN) classifier, logistic regression (lreg), random forest classifier (rf), support vector classification (SVC), and XGBoost (XGB) classifier models, and the common consensus was applied to molecular selection of 21 diverse structures. Compounds were screened using human P2Y6R-induced functional calcium transients in transfected 1321N1 astrocytoma cells and fluorescent binding inhibition at closely related hP2Y14R expressed in CHO cells. The hit compound ABBV-744, an experimental anticancer drug with a 6-methyl-7-oxo-6,7-dihydro-1H-pyrrolo[2,3-c]pyridine scaffold, had multifaceted interactions with the P2YR family: hP2Y6R inhibition in a non-surmountable fashion, suggesting that noncompetitive antagonism, and hP2Y1R enhancement, but not hP2Y14R binding inhibition. Other machine learning-selected compounds were either weak (experimental anti-asthmatic drug AZD5423 with a phenyl-1H-indazole scaffold) or inactive in inhibiting the hP2Y6R. Experimental drugs TAK-593 and GSK1070916 (100 µM) inhibited P2Y14R fluorescent binding by 50% and 38%, respectively, and all other compounds by < 20%. Thus, machine learning has led the way toward revealing previously unknown modulators of several P2YR subtypes that have varied effects.

New 2-Ethylthio-4-methylaminoquinazoline derivatives inhibiting two subunits of cytochrome bc1 in Mycobacterium tuberculosis.

The emergence of multi-drug (MDR-TB) and extensively-drug resistant tuberculosis (XDR-TB) is a major threat to the global management of tuberculosis (TB) worldwide. New chemical entities are of need to treat drug-resistant TB. In this study, the mode of action of new, potent quinazoline derivatives was investigated against Mycobacterium tuberculosis (M. tb). Four derivatives 11626141, 11626142, 11626252 and 11726148 showed good activity (MIC ranging from 0.02-0.09 µg/mL) and low toxicity (TD50 ≥ 5µg/mL) in vitro against M. tb strain H37Rv and HepG2 cells, respectively. 11626252 was the most selective compound from this series. Quinazoline derivatives were found to target cytochrome bc1 by whole-genome sequencing of mutants selected with 11626142. Two resistant mutants harboured the transversion T943G (Trp312Gly) and the transition G523A (Gly175Ser) in the cytochrome bc1 complex cytochrome b subunit (QcrB). Interestingly, a third mutant QuinR-M1 contained a mutation in the Rieske iron-sulphur protein (QcrA) leading to resistance to quinazoline and other QcrB inhibitors, the first report of cross-resistance involving QcrA. Modelling of both QcrA and QcrB revealed that all three resistance mutations are located in the stigmatellin pocket, as previously observed for other QcrB inhibitors such as Q203, AX-35, and lansoprazole sulfide (LPZs). Further analysis of the mode of action in vitro revealed that 11626252 exposure leads to ATP depletion, a decrease in the oxygen consumption rate and also overexpression of the cytochrome bd oxidase in M. tb. Our findings suggest that quinazoline-derived compounds are a new and attractive chemical entity for M. tb drug development targeting two separate subunits of the cytochrome bc1 complex.

Machine Learning Models for Mycobacterium tuberculosisIn Vitro Activity: Prediction and Target Visualization.

Tuberculosis (TB) is a major global health challenge, with approximately 1.4 million deaths per year. There is still a need to develop novel treatments for patients infected with Mycobacterium tuberculosis (Mtb). There have been many large-scale phenotypic screens that have led to the identification of thousands of new compounds. Yet, there is very limited investment in TB drug discovery which points to the need for new methods to increase the efficiency of drug discovery against Mtb. We have used machine learning approaches to learn from the public Mtb data, resulting in many data sets and models with robust enrichment and hit rates leading to the discovery of new active compounds. Recently, we have curated predominantly small-molecule Mtb data and developed new machine learning classification models with 18 886 molecules at different activity cutoffs. We now describe the further validation of these Bayesian models using a library of over 1000 molecules synthesized as part of EU-funded New Medicines for TB and More Medicines for TB programs. We highlight molecular features which are enriched in these active compounds. In addition, we provide new regression and classification models that can be used for scoring compound libraries or used to design new molecules. We have also visualized these molecules in the context of known molecular targets and identified clusters in chemical property space, which may aid in future target identification efforts. Finally, we are also making these data sets publicly available, representing a significant increase to the available Mtb inhibition data in the public domain.

Multiple approaches to repurposing drugs for neuroblastoma.

Neuroblastoma (NB) is the second leading extracranial solid tumor of early childhood with about two-thirds of cases presenting before the age of 5, and accounts for roughly 15 percent of all pediatric cancer fatalities in the United States. Treatments against NB are lacking, resulting in a low survival rate in high-risk patients. A repurposing approach using already approved or clinical stage compounds can be used for diseases for which the patient population is small, and the commercial market limited. We have used Bayesian machine learning, in vitro cell assays, and combination analysis to identify molecules with potential use for NB. We demonstrated that pyronaridine (SH-SY5Y IC50 1.70 µM, SK-N-AS IC50 3.45 µM), BAY 11-7082 (SH-SY5Y IC50 0.85 µM, SK-N-AS IC50 1.23 µM), niclosamide (SH-SY5Y IC50 0.87 µM, SK-N-AS IC50 2.33 µM) and fingolimod (SH-SY5Y IC50 4.71 µM, SK-N-AS IC50 6.11 µM) showed cytotoxicity against NB. As several of the molecules are approved drugs in the US or elsewhere, they may be repurposed more readily for NB treatment. Pyronaridine was also tested in combinations in SH-SY5Y cells and demonstrated an antagonistic effect with either etoposide or crizotinib. Whereas when crizotinib and etoposide were combined with each other they had a synergistic effect in these cells. We have also described several analogs of pyronaridine to explore the structure-activity relationship against cell lines. We describe multiple molecules demonstrating cytotoxicity against NB and the further evaluation of these molecules and combinations using other NB cells lines and in vivo models will be important in the future to assess translational potential.

Cryo-EM structure of pleconaril-resistant rhinovirus-B5 complexed to the antiviral OBR-5-340 reveals unexpected binding site.

Viral inhibitors, such as pleconaril and vapendavir, target conserved regions in the capsids of rhinoviruses (RVs) and enteroviruses (EVs) by binding to a hydrophobic pocket in viral capsid protein 1 (VP1). In resistant RVs and EVs, bulky residues in this pocket prevent their binding. However, recently developed pyrazolopyrimidines inhibit pleconaril-resistant RVs and EVs, and computational modeling has suggested that they also bind to the hydrophobic pocket in VP1. We studied the mechanism of inhibition of pleconaril-resistant RVs using RV-B5 (1 of the 7 naturally pleconaril-resistant rhinoviruses) and OBR-5-340, a bioavailable pyrazolopyrimidine with proven in vivo activity, and determined the 3D-structure of the protein-ligand complex to 3.6 Å with cryoelectron microscopy. Our data indicate that, similar to other capsid binders, OBR-5-340 induces thermostability and inhibits viral adsorption and uncoating. However, we found that OBR-5-340 attaches closer to the entrance of the pocket than most other capsid binders, whose viral complexes have been studied so far, showing only marginal overlaps of the attachment sites. Comparing the experimentally determined 3D structure with the control, RV-B5 incubated with solvent only and determined to 3.2 Å, revealed no gross conformational changes upon OBR-5-340 binding. The pocket of the naturally OBR-5-340-resistant RV-A89 likewise incubated with OBR-5-340 and solved to 2.9 Å was empty. Pyrazolopyrimidines have a rigid molecular scaffold and may thus be less affected by a loss of entropy upon binding. They interact with less-conserved regions than known capsid binders. Overall, pyrazolopyrimidines could be more suitable for the development of new, broadly active inhibitors.

New Drugs and Novel Cellular Targets against Tuberculosis.

Mycobacterium tuberculosis (Mtb) is the etiological agent of tuberculosis (TB), one of the most life-threatening communicable diseases, which causes 10 million new cases each year and results in an estimated 1 [...].

Pipeline of anti-Mycobacterium abscessus small molecules: Repurposable drugs and promising novel chemical entities.

The Mycobacterium abscessus complex is a group of emerging pathogens that are difficult to treat. There are no effective drugs for successful M. abscessus pulmonary infection therapy, and existing drug regimens recommended by the British or the American Thoracic Societies are associated with poor clinical outcomes. Therefore, novel antibacterial drugs are urgently needed to contain this global threat. The current anti-M. abscessus small-molecule drug development process can be enhanced by two parallel strategies-discovery of compounds from new chemical classes and commercial drug repurposing. This review focuses on recent advances in the finding of novel small-molecule agents, and more particularly focuses on the activity, mode of action and structure-activity relationship of promising inhibitors from five different chemical classes-benzimidazoles, indole-2-carboxamides, benzothiazoles, 4-piperidinoles, and oxazolidionones. We further discuss some other interesting small molecules, such as thiacetazone derivatives and benzoboroxoles, that are in the early stages of drug development, and summarize current knowledge about the efficacy of repurposable drugs, such as rifabutin, tedizolid, bedaquiline, and others. We finally review targets of therapeutic interest in M. abscessus that may be worthy of future drug and adjunct therapeutic development.

Diazadispiroalkane Derivatives Are New Viral Entry Inhibitors.

Herpesviruses are widespread and can cause serious illness. Many currently available antiviral drugs have limited effects, result in rapid development of resistance, and often exhibit dose-dependent toxicity. Especially for human cytomegalovirus (HCMV), new well-tolerated compounds with novel mechanisms of action are urgently needed. In this study, we characterized the antiviral activity of two new diazadispiroalkane derivatives, 11826091 and 11826236. These two small molecules exhibited strong activity against low-passage-number HCMV. Pretreatment of cell-free virus with these compounds greatly reduced infection. Time-of-addition assays where 11826091 or 11826236 was added to cells before infection, before and during infection, or during or after infection demonstrated an inhibitory effect on early steps of infection. Interestingly, 11826236 had an effect by addition to cells after infection. Results from entry assays showed the major effect to be on attachment. Only 11826236 had a minimal effect on penetration comparable to heparin. Further, no effect on virus infection was found for cell lines with a defect in heparan sulfate expression or lacking all surface glycosaminoglycans, indicating that these small molecules bind to heparan sulfate on the cell surface. To test this further, we extended our analyses to pseudorabies virus (PrV), a member of the Alphaherpesvirinae, which is known to use cell surface heparan sulfate for initial attachment via nonessential glycoprotein C (gC). While infection with PrV wild type was strongly impaired by 11826091 or 11826236, as with heparin, a mutant lacking gC was unaffected by either treatment, demonstrating that primary attachment to heparan sulfate via gC is targeted by these small molecules.

Development of Machine Learning Models and the Discovery of a New Antiviral Compound against Yellow Fever Virus.

Yellow fever (YF) is an acute viral hemorrhagic disease transmitted by infected mosquitoes. Large epidemics of YF occur when the virus is introduced into heavily populated areas with high mosquito density and low vaccination coverage. The lack of a specific small molecule drug treatment against YF as well as for homologous infections, such as zika and dengue, highlights the importance of these flaviviruses as a public health concern. With the advancement in computer hardware and bioactivity data availability, new tools based on machine learning methods have been introduced into drug discovery, as a means to utilize the growing high throughput screening (HTS) data generated to reduce costs and increase the speed of drug development. The use of predictive machine learning models using previously published data from HTS campaigns or data available in public databases, can enable the selection of compounds with desirable bioactivity and absorption, distribution, metabolism, and excretion profiles. In this study, we have collated cell-based assay data for yellow fever virus from the literature and public databases. The data were used to build predictive models with several machine learning methods that could prioritize compounds for in vitro testing. Five molecules were prioritized and tested in vitro from which we have identified a new pyrazolesulfonamide derivative with EC50 3.2 µM and CC50 24 µM, which represents a new scaffold suitable for hit-to-lead optimization that can expand the available drug discovery candidates for YF.

Targeting Non-Replicating Mycobacterium tuberculosis and Latent Infection: Alternatives and Perspectives (Mini-Review).

Latent tuberculosis infection (LTBI) represents a major challenge to curing TB disease. Current guidelines for LTBI management include only three older drugs and their combinations-isoniazid and rifamycins (rifampicin and rifapentine). These available control strategies have little impact on latent TB elimination, and new specific therapeutics are urgently needed. In the present mini-review, we highlight some of the alternatives that may potentially be included in LTBI treatment recommendations and a list of early-stage prospective small molecules that act on drug targets specific for Mycobacterium tuberculosis latency.

PEGylated mucus-penetrating nanocrystals for lung delivery of a new FtsZ inhibitor against Burkholderia cenocepacia infection.

C109 is a potent but poorly soluble FtsZ inhibitor displaying promising activity against Burkholderia cenocepacia, a high-risk pathogen for cystic fibrosis (CF) sufferers. To harness C109 for inhalation, we developed nanocrystal-embedded dry powders for inhalation suspension consisting in C109 nanocrystals stabilized with D-α-tocopheryl polyethylene glycol 1000 succinate (TPGS) embedded in hydroxypropyl-ß-cyclodextrin (CD). The powders could be safely re-dispersed in water for in vitro aerosolization. Owing to the presence of a PEG shell, the rod shape and the peculiar aspect ratio, C109 nanocrystals were able to diffuse through artificial CF mucus. The promising technological features were completed by encouraging in vitro/in vivo effects. The formulations displayed no toxicity towards human bronchial epithelial cells and were active against planktonic and sessile B. cenocepacia strains. The efficacy of C109 nanosuspensions in combination with piperacillin was confirmed in a Galleria mellonella infection model, strengthening their potential for combined therapy of B. cenocepacia lung infections.

The Evolution of Pleconaril: Modified O-Alkyl Linker Analogs Have Biological Activity towards Coxsackievirus B3 Nancy.

Coxsackieviruses type B are one of the most common causes of mild upper respiratory and gastrointestinal illnesses. At the time of writing, there are no approved drugs for effective antiviral treatment for Coxsackieviruses type B. We used the core-structure of pleconaril, a well-known antienteroviral drug candidate, for the synthesis of novel compounds with O-propyl linker modifications. Some original compounds with 4 different linker patterns, such as sulfur atom, ester, amide, and piperazine, were synthesized according to five synthetic schemes. The cytotoxicity and bioactivity of 14 target compounds towards Coxsackievirus B3 Nancy were examined. Based on the results, the values of 50% cytotoxic dose (CC50), 50% virus-inhibiting dose (IC50), and selectivity index (SI) were calculated for each compound. Several of the novel synthesized derivatives exhibited a strong anti-CVB3 activity (SI > 20 to > 200). These results open up new possibilities for synthesis of further new selective anticoxsackievirus compounds.

Countermeasure against bright-light attack on superconducting nanowire single-photon detector in quantum key distribution.

We present an active anti-latching system for superconducting nanowire single-photon detectors. We experimentally test it against a bright-light attack, previously used to compromise security of quantum key distribution. Although our system detects continuous blinding, the detector is shown to be partially blindable and controllable by specially tailored sequences of bright pulses. Improvements to the countermeasure are suggested.

Controlling single-photon detector ID210 with bright light.

We experimentally demonstrate that a single-photon detector ID210 commercially available from ID Quantique is vulnerable to blinding and can be fully controlled by bright illumination. In quantum key distribution, this vulnerability can be exploited by an eavesdropper to perform a faked-state attack giving her full knowledge of the key without being noticed. We consider the attack on standard BB84 protocol and a subcarrier-wave scheme and outline a possible countermeasure.

Multiple Machine Learning Comparisons of HIV Cell-based and Reverse Transcriptase Data Sets.

The human immunodeficiency virus (HIV) causes over a million deaths every year and has a huge economic impact in many countries. The first class of drugs approved were nucleoside reverse transcriptase inhibitors. A newer generation of reverse transcriptase inhibitors have become susceptible to drug resistant strains of HIV, and hence, alternatives are urgently needed. We have recently pioneered the use of Bayesian machine learning to generate models with public data to identify new compounds for testing against different disease targets. The current study has used the NIAID ChemDB HIV, Opportunistic Infection and Tuberculosis Therapeutics Database for machine learning studies. We curated and cleaned data from HIV-1 wild-type cell-based and reverse transcriptase (RT) DNA polymerase inhibition assays. Compounds from this database with ≤1 µM HIV-1 RT DNA polymerase activity inhibition and cell-based HIV-1 inhibition are correlated (Pearson r = 0.44, n = 1137, p < 0.0001). Models were trained using multiple machine learning approaches (Bernoulli Naive Bayes, AdaBoost Decision Tree, Random Forest, support vector classification, k-Nearest Neighbors, and deep neural networks as well as consensus approaches) and then their predictive abilities were compared. Our comparison of different machine learning methods demonstrated that support vector classification, deep learning, and a consensus were generally comparable and not significantly different from each other using 5-fold cross validation and using 24 training and test set combinations. This study demonstrates findings in line with our previous studies for various targets that training and testing with multiple data sets does not demonstrate a significant difference between support vector machine and deep neural networks.

Cmr is a redox-responsive regulator of DosR that contributes to M. tuberculosis virulence.

Mycobacterium tuberculosis (MTb) is the causative agent of pulmonary tuberculosis (TB). MTb colonizes the human lung, often entering a non-replicating state before progressing to life-threatening active infections. Transcriptional reprogramming is essential for TB pathogenesis. In vitro, Cmr (a member of the CRP/FNR super-family of transcription regulators) bound at a single DNA site to act as a dual regulator of cmr transcription and an activator of the divergent rv1676 gene. Transcriptional profiling and DNA-binding assays suggested that Cmr directly represses dosR expression. The DosR regulon is thought to be involved in establishing latent tuberculosis infections in response to hypoxia and nitric oxide. Accordingly, DNA-binding by Cmr was severely impaired by nitrosation. A cmr mutant was better able to survive a nitrosative stress challenge but was attenuated in a mouse aerosol infection model. The complemented mutant exhibited a ∼2-fold increase in cmr expression, which led to increased sensitivity to nitrosative stress. This, and the inability to restore wild-type behaviour in the infection model, suggests that precise regulation of the cmr locus, which is associated with Region of Difference 150 in hypervirulent Beijing strains of Mtb, is important for TB pathogenesis.

Mycobacterium abscessus, an Emerging and Worrisome Pathogen among Cystic Fibrosis Patients.

Nontuberculous mycobacteria (NTM) have recently emerged as important pathogens among cystic fibrosis (CF) patients worldwide. Mycobacterium abscessus is becoming the most worrisome NTM in this cohort of patients and recent findings clarified why this pathogen is so prone to this disease. M. abscessus drug therapy takes up to 2 years and its failure causes an accelerated lung function decline. The M. abscessus colonization of lung alveoli begins with smooth strains producing glycopeptidolipids and biofilm, whilst in the invasive infection, "rough" mutants are responsible for the production of trehalose dimycolate, and consequently, cording formation. Human-to-human M. abscessus transmission was demonstrated among geographically separated CF patients by whole-genome sequencing of clinical isolates worldwide. Using a M. abscessus infected CF zebrafish model, it was demonstrated that CFTR (cystic fibrosis transmembrane conductance regulator) dysfunction seems to have a specific role in the immune control of M. abscessus infections only. This pathogen is also intrinsically resistant to many drugs, thanks to its physiology and to the acquisition of new mechanisms of drug resistance. Few new compounds or drug formulations active against M. abscessus are present in preclinical and clinical development, but recently alternative strategies have been investigated, such as phage therapy and the use of ß-lactamase inhibitors.

The antibacterial prodrug activator Rv2466c is a mycothiol-dependent reductase in the oxidative stress response of Mycobacterium tuberculosis.

The Mycobacterium tuberculosis rv2466c gene encodes an oxidoreductase enzyme annotated as DsbA. It has a CPWC active-site motif embedded within its thioredoxin fold domain and mediates the activation of the prodrug TP053, a thienopyrimidine derivative that kills both replicating and nonreplicating bacilli. However, its mode of action and actual enzymatic function in M. tuberculosis have remained enigmatic. In this study, we report that Rv2466c is essential for bacterial survival under H2O2 stress. Further, we discovered that Rv2466c lacks oxidase activity; rather, it receives electrons through the mycothiol/mycothione reductase/NADPH pathway to activate TP053, preferentially via a dithiol-disulfide mechanism. We also found that Rv2466c uses a monothiol-disulfide exchange mechanism to reduce S-mycothiolated mixed disulfides and intramolecular disulfides. Genetic, phylogenetic, bioinformatics, structural, and biochemical analyses revealed that Rv2466c is a novel mycothiol-dependent reductase, which represents a mycoredoxin cluster of enzymes within the DsbA family different from the glutaredoxin cluster to which mycoredoxin-1 (Mrx1 or Rv3198A) belongs. To validate this DsbA-mycoredoxin cluster, we also characterized a homologous enzyme of Corynebacterium glutamicum (NCgl2339) and observed that it demycothiolates and reduces a mycothiol arsenate adduct with kinetic properties different from those of Mrx1. In conclusion, our work has uncovered a DsbA-like mycoredoxin that promotes mycobacterial resistance to oxidative stress and reacts with free mycothiol and mycothiolated targets. The characterization of the DsbA-like mycoredoxin cluster reported here now paves the way for correctly classifying similar enzymes from other organisms.

Structure-Based Drug Design and Characterization of Sulfonyl-Piperazine Benzothiazinone Inhibitors of DprE1 from Mycobacterium tuberculosis.

Macozinone (MCZ) is a tuberculosis (TB) drug candidate that specifically targets the essential flavoenzyme DprE1, thereby blocking synthesis of the cell wall precursor decaprenyl phosphoarabinose (DPA) and provoking lysis of Mycobacterium tuberculosis As part of the MCZ backup program, we exploited structure-guided drug design to produce a new series of sulfone-containing derivatives, 2-sulfonylpiperazin 8-nitro 6-trifluoromethyl 1,3-benzothiazin-4-one, or sPBTZ. These compounds are less active than MCZ but have a better solubility profile, and some derivatives display enhanced stability in microsomal assays. DprE1 was efficiently inhibited by sPBTZ, and covalent adducts with the active-site cysteine residue (C387) were formed. However, despite the H-bonding potential of the sulfone group, no additional bonds were seen in the crystal structure of the sPBTZ-DprE1 complex with compound 11326127 compared to MCZ. Compound 11626091, the most advanced sPBTZ, displayed good antitubercular activity in the murine model of chronic TB but was less effective than MCZ. Nonetheless, further testing of this MCZ backup compound is warranted as part of combination treatment with other TB drugs.

Optimized Background Regimen for Treatment of Active Tuberculosis with the Next-Generation Benzothiazinone Macozinone (PBTZ169).

The efficacy of the standardized four-drug regimen (comprising isoniazid, rifampin, pyrazinamide, and ethambutol) for the treatment of tuberculosis (TB) is menaced by the emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains of Mycobacterium tuberculosis Intensive efforts have been made to develop new antibiotics or to repurpose old drugs, and several of these are currently being evaluated in clinical trials for their antitubercular activity. Among the new candidate drugs is macozinone (MCZ), the piperazine-containing benzothiazinone PBTZ169, which is currently being evaluated in phase I/II clinical trials. Here, we determined the in vitro and in vivo activity of MCZ in combination with a range of anti-TB drugs in order to design a new regimen against active TB. Two-drug combinations with MCZ were tested against M. tuberculosis using checkerboard and CFU enumeration after drug exposure assays. MCZ was observed to have no interactions with all first- and second-line anti-TB drugs. At the MIC of each drug, MCZ with either bedaquiline (BDQ), clofazimine (CLO), delamanid (DMD), or sutezolid (STZ) reduced the bacterial burden by 2 logs compared to that achieved with the drugs alone, indicating synergism. MCZ also displayed synergism with clomiphene (CLM), a potential inhibitor of the undecaprenyl pyrophosphate synthase (UppS) in mycobacteria. For all the other drugs tested in combination with MCZ, no synergistic activity was observed. Neither antagonism nor increased cytotoxicity was found for most combinations, suggesting that MCZ could be added to different TB treatment regimens without any significant adverse effects.