Learning from the past for TB drug discovery in the future

Structure-activity relationship mediated molecular insights of DprE1 inhibitors: A Comprehensive Review

Emerging threats of multi-drug resistant (MDR), extensively drug-resistant (XDR), and totally drug-resistant (TDR) tuberculosis led to the discovery of a novel target which was entitled Decaprenylphosphoryl-β-D-ribose 2'-epimerase (DprE1) enzyme. DprE1 is composed of two isoforms, decaprenylphosphoryl-β-D-ribose oxidase (DprE1) and decaprenylphosphoryl-D-2-keto erythro pentose reductase (DprE2). The enzymes, DprE1 and DprE2, regulate the two-step epimerization process to form DPA (Decaprenylphosphoryl arabinose) from DPX (Decaprenylphosphoryl-D-ribose), which is the sole precursor in the cell wall synthesis of arabinogalactan (AG) and lipoarabinomannan (LAM). Target-based and whole-cell-based screening played an imperative role in the identification of the druggable target, DprE1, whereas the druggability of the DprE2 enzyme is not proved yet. To date, diverse scaffolds of heterocyclic and aromatic ring systems have been reported as DprE1 inhibitors based on their interaction mode, i.e. covalent, and non-covalent inhibitors. This review describes the structure-activity relationship (SAR) of reported covalent and non-covalent inhibitors to enlighten about the crucial pharmacophoric features required for DprE1 inhibition, along with in-silico studies which characterize the amino acid residues responsible for covalent and non-covalent interactions.Communicated by Ramaswamy H. Sarma.

NOS2/miR-493-5p Signaling Regulates in the LPS-Induced Inflammatory Response in the RAW264.7 Cells

Tuberculosis (TB) is a fatal infectious disease; however, the molecular mechanisms underlying the pathogenicity of TB remain elusive. The present study aims to identify potential biomarkers associated with Mycobacterium tuberculosis (M.tb) infection by using integrated bioinformatics and in vitro validation studies. GSE50050, GSE78706, and GSE108844 data from the gene expression omnibus (GEO) database were downloaded to identify differentially expressed genes (DEGs). The functions of DEGs were further subjected to gene ontology (GO) and KEGG pathway analysis. The hub genes from the DEGs were determined based on the protein-protein interaction (PPI) network analysis. Finally, the hub genes were experimentally validated using the in vitro functional studies. A total of 26 common DEGs were identified among GSE50050, GSE78706, and GSE108844. The functional enrichment analysis showed that the common DEGs were associated with cytokines response and TB pathways. The PPI network analysis identified nine hub genes. Further in vitro studies showed that nitric oxide synthase 2 (NOS2) was up-regulated in RAW264.7 cells upon lipopolysaccharides (LPS) stimulation, which was accompanied by increased inflammatory cytokines release. Furthermore, NOS2 was found to be a target of miR-493-5p, which was confirmed by luciferase reporter assay. NOS2 was repressed by miR-493-5p overexpression and was up-regulated after miR-493-5p inhibition in RAW264.7 cells. The rescue experiments showed that LPS-induced increase in the inflammatory cytokines of the RAW264.7 cells was significantly attenuated by NOS2 knockdown and miR-493-5p overexpression. Collectively, our results for the first time demonstrated that NOS2/miR-493-5p signaling pathway may potentially involve in the inflammatory response during bacterial infection such as M. tb infection.

Machine learning approaches in diagnosing tuberculosis through biomarkers - A systematic review

Biomarker-based tests may facilitate Tuberculosis (TB) diagnosis, accelerate treatment initiation, and thus improve outcomes. This review synthesizes the literature on biomarker-based detection for TB diagnosis using machine learning. The systematic review approach follows the PRISMA guideline. Articles were sought using relevant keywords from Web of Science, PubMed, and Scopus, resulting in 19 eligible studies after a meticulous screening. All the studies were found to have focused on the supervised learning approach, with Support Vector Machine (SVM) and Random Forest emerging as the top two algorithms, with the highest accuracy, sensitivity and specificity reported to be 97.0%, 99.2%, and 98.0%, respectively. Further, protein-based biomarkers were widely explored, followed by gene-based such as RNA sequence and, Spoligotypes. Publicly available datasets were observed to be popularly used by the studies reviewed whilst studies targeting specific cohorts such as HIV patients or children gathering their own data from healthcare facilities, leading to smaller datasets. Of these, most studies used the leave one out cross validation technique to mitigate overfitting. The review shows that machine learning is increasingly assessed in research to improve TB diagnosis through biomarkers, as promising results were shown in terms of model's detection performance. This provides insights on the possible application of machine learning approaches to diagnose TB using biomarkers as opposed to the traditional methods that can be time consuming. Low-middle income settings, where access to basic biomarkers could be provided as compared to sputum-based tests that are not always available, could be a major application of such models.

Tricyclic SpiroLactams Kill Mycobacteria In Vitro and In Vivo by Inhibiting Type II NADH Dehydrogenases

It is critical that novel classes of antituberculosis drugs are developed to combat the increasing burden of infections by multidrug-resistant strains. To identify such a novel class of antibiotics, a chemical library of unique 3-D bioinspired molecules was explored revealing a promising, mycobacterium specific Tricyclic SpiroLactam (TriSLa) hit. Chemical optimization of the TriSLa scaffold delivered potent analogues with nanomolar activity against replicating and nonreplicating Mycobacterium tuberculosis. Characterization of isolated TriSLa-resistant mutants, and biochemical studies, found TriSLas to act as allosteric inhibitors of type II NADH dehydrogenases (Ndh-2 of the electron transport chain), resulting in an increase in bacterial NADH/NAD⁺ ratios and decreased ATP levels. TriSLas are chemically distinct from other inhibitors of Ndh-2 but share a dependence for fatty acids for activity. Finally, in vivo proof-of-concept studies showed TriSLas to protect zebrafish larvae from Mycobacterium marinum infection, suggesting a vulnerability of Ndh-2 inhibition in mycobacterial infections.

Recent advances in oxazolidinones as antituberculosis agents

Tuberculosis (TB) is an infectious and fatal disease caused by Mycobacterium tuberculosis (Mtb) and remains a serious public health threat; therefore, the development of new antitubercular agents is a priority for the World Health Organization's End TB strategy and the United Nations' Sustainable Development Goals to eradicate TB. Oxazolidinones are a class of synthetic antibacterial agents with a distinct mode of action developed for the treatment of Gram-positive bacterial infections. Many oxazolidinones exhibit good activity against Mtb, and some are currently in clinical trials for multidrug-resistant TB and extensively drug-resistant TB therapy. In this review, the mechanism of action, activity and toxicity of oxazolidinones and recent progress in the research and development of oxazolidinones as anti-TB agents are summarized.

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.

Synthesis and Antimycobacterial Activity of 3-Phenyl-1H-indoles

Tuberculosis has been described as a global health crisis since the 1990s, with an estimated 1.4 million deaths in the last year. Herein, a series of 20 1H-indoles were synthesized and evaluated as in vitro inhibitors of Mycobacterium tuberculosis (Mtb) growth. Furthermore, the top hit compounds were active against multidrug-resistant strains, without cross-resistance with first-line drugs. Exposing HepG2 and Vero cells to the molecules for 72 h showed that one of the evaluated structures was devoid of apparent toxicity. In addition, this 3-phenyl-1H-indole showed no genotoxicity signals. Finally, time-kill and pharmacodynamic model analyses demonstrated that this compound has bactericidal activity at concentrations close to the Minimum Inhibitory Concentration, coupled with a strong time-dependent behavior. To the best of our knowledge, this study describes the activity of 3-phenyl-1H-indole against Mtb for the first time.

Natural products from Brazilian biodiversity identified as potential inhibitors of PknA and PknB of M. tuberculosis using molecular modeling tools

Mycobacterium tuberculosis was discovered in 1882 by Robert Koch but, since its discovery, the tuberculosis (TB) epidemic has endured, being one of the top 10 causes of death worldwide. Drug-resistant TB continues to be a public health threat and bioactive compounds with a new mode of action (MoA) are needed to overcome this. Since natural products are described as important sources for the development of new drugs, the objective of this work was to identify potential ligands from Brazilian natural products (NPs) for M. tuberculosis targets using molecular modeling tools. Using chemogenomics we identified the Serine/Threonine Protein Kinase PknB as a putative target for 13 NPs from a database from Brazilian biodiversity (NuBBE). Literature data supported further investigation of NuBBE105, NuBBE598, NuBBE936, NuBBE964, NuBBE1045, and NuBBE1180 by molecular docking and dynamics. Key interactions were observed with PknB and simulations confirmed stability and favorable binding energies. Considering structural similarity with PknB, we further explored binding of the NPs to PknA, critical for M. tuberculosis survival, and all of them resembled important interactions with the enzyme, showing stable and favorable binding energies, whilst van der Waals interactions seem to play a key role for binding to PknA and PknB. NuBBE936 and NuBBE1180 have already had their antimycobacterial activity reported and our results can provide a basis for their MoA. Finally, the other NPs which have not been tested against M. tuberculosis deserve further investigation, aiming at the discovery of antimycobacterial drug candidates with innovative MoA.

Synthetic molecules as DprE1 inhibitors: A patent review

INTRODUCTION

In recent years, the advent of multidrug-resistant tuberculosis (MDR-TB), the extensively-resistant TB (XDR-TB), and the total drug-resistant-TB (TDR-TB) have led the community to develop new antitubercular molecules. The decaprenylphosphoryl-β-D-ribose-2'-epimerase-1 (DprE1) is an established target to developed new anti-TB drugs. This enzyme is required to synthesize the cell wall of Mycobacterium tuberculosis (Mtb).

AREA COVERED

This patent review focuses on the granted patents and patent applications related to the chemical entities developed as DprE1 inhibitors for TB treatment from the publication year of the BTZ-043 compound patent application (2007) till 30 September 2020.

EXPERT OPINION

The DprE1 has many advantages in the development of new antitubercular molecules, for example, its location in the periplasm of the Mtb cell wall and its absence in the human body. This indicates that the DprE1 inhibitors are selective for Mtb, and their toxic and side effects on the human body may be negligible or small. Accordingly, the use of DprE1 inhibitors may be benefic for patients with drug-resistant bacteria that require long-term medication. Four molecules are in clinical trials, which could become the drugs of the future for TB-therapy.

Physicochemical properties and Mycobacterium tuberculosis transporters: keys to efficacious antitubercular drugs?

Securing novel, safe, and effective medicines to treat Mycobacterium tuberculosis remains an elusive goal, particularly influenced by the largely impervious Mtb envelope that limits exposure and thus efficacy of inhibitors at their cellular and periplasmic targets. The impact of physicochemical properties on pharmacokinetic parameters that govern oral absorption and exposure at sites of infection is considered alongside how these properties influence penetration of the Mtb envelope, with the likely influence of transporter proteins. The findings are discussed to benchmark current drugs and the emerging pipeline, whilst considering tactics for future rational and targeted design strategies, based around emerging data on Mtb transporters and their structures and functions.

Molecule Property Analyses of Active Compounds for Mycobacterium tuberculosis

Tuberculosis (TB) continues to claim the lives of around 1.7 million people per year. Most concerning are the reports of multidrug drug resistance. Paradoxically, this global health pandemic is demanding new therapies when resources and interest are waning. However, continued tuberculosis drug discovery is critical to address the global health need and burgeoning multidrug resistance. Many diverse classes of antitubercular compounds have been identified with activity in vitro and in vivo. Our analyses of over 100 active leads are representative of thousands of active compounds generated over the past decade, suggests that they come from few chemical classes or natural product sources. We are therefore repeatedly identifying compounds that are similar to those that preceded them. Our molecule-centered cheminformatics analyses point to the need to dramatically increase the diversity of chemical libraries tested and get outside of the historic Mtb property space if we are to generate novel improved antitubercular leads.

Biosynthesis of Galactan in Mycobacterium tuberculosis as a Viable TB Drug Target?

While target-based drug design has proved successful in several therapeutic areas, this approach has not yet provided compelling outcomes in the field of antibacterial agents. This statement remains especially true for the development of novel therapeutic interventions against tuberculosis, an infectious disease that is among the top ten leading causes of death globally. Mycobacterial galactan is an important component of the protective cell wall core of the tuberculosis pathogen and it could provide a promising target for the design of new drugs. In this review, we summarize the current knowledge on galactan biosynthesis in Mycobacterium tuberculosis, including landmark findings that led to the discovery and understanding of three key enzymes in this pathway: UDP-galactose mutase, and galactofuranosyl transferases GlfT1 and GlfT2. Moreover, we recapitulate the efforts aimed at their inhibition. The predicted common transition states of the three enzymes provide the lucrative possibility of multitargeting in pharmaceutical development, a favourable property in the mitigation of drug resistance. We believe that a tight interplay between target-based computational approaches and experimental methods will result in the development of original inhibitors that could serve as the basis of a new generation of drugs against tuberculosis.

Why Wait? The Case for Treating Tuberculosis with Inhaled Drugs

The discovery of drugs to treat tuberculosis (TB) was a major medical milestone in the twentieth century. However, from the outset, drug resistance was observed. Currently, of the 10 million people that exhibit TB symptoms each year, 450,000 have multidrug or extensively drug resistant (MDR or XDR) TB. While greater understanding of the host and pathogen (Mycobacterium tuberculosis, Mtb) coupled with scientific ingenuity will lead to new drugs and vaccines, in the meantime 4000 people die daily from TB. Thus, efforts to improve existing TB drugs should also be prioritized. Improved efficacy and decreased dose and associated toxicity of existing drugs would translate to greater compliance, life expectancy and quality of life of Mtb infected individuals. One potential strategy to improve existing drugs is to deliver them by inhalation as aerosols to the lung, the primary site of Mtb infection. Inhaled drugs are used for other pulmonary diseases, but they have yet to be utilized for TB. Inhaled therapies for TB represent an untapped opportunity that the pharmaceutical, clinical and regulatory communities should consider.

Deuteration of BTZ043 Extends the Lifetime of Meisenheimer Intermediates to the Antituberculosis Nitroso Oxidation State

Substituted nitrobenzothiazinones (BTZs) are potent antituberculosis prodrugs that are reductively activated to produce nitroso moieties that form covalent adducts with a cysteine residue of decaprenylphosphoryl-β-d-ribose-2'-oxidase (DprE1) of Mycobacterium tuberculosis (Mtb). The resulting cell wall synthesis inhibition is lethal to Mtb, leading to consideration of development of BTZs for clinical use. The hydride-induced reduction of the nitroaromatic proceeds by reversible formation of the corresponding Meisenheimer complex. Herein we demonstrate that chemical reduction of BTZ043 with NaBD₄ followed by reoxidation incorporates deuterium into the core nitro aromatic warhead. Subsequent reduction of the deuterated species is not affected, but, as expected, reoxidation is slowed by the deuterium isotope effect, thus prolonging the lifetime of the active nitroso oxidation state.

A rapid method for estimation of the efficacy of potential antimicrobials in humans and animals by agar diffusion assay

Drug resistance continues to challenge traditional antimicrobial drugs and limit their clinical utility. This requires us to continue our search for new drug candidates with novel mechanisms of action against infectious diseases. We now describe a simple agar diffusion assay, which can be used as a general method for the rapid detection of antimicrobial activity of drug candidates in animal or human blood plasma for the ultimate prediction of the efficacy of potential drugs prior to clinical trials. We present an example for a clinical candidate against Mycobacterium tuberculosis.

Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery

Tuberculosis is a global health dilemma. In 2016, the WHO reported 10.4 million incidences and 1.7 million deaths. The need to develop new treatments for those infected with Mycobacterium tuberculosis ( Mtb) has led to many large-scale phenotypic screens and many thousands of new active compounds identified in vitro. However, with limited funding, efforts to discover new active molecules against Mtb needs to be more efficient. Several computational machine learning approaches have been shown to have good enrichment and hit rates. We have curated small molecule Mtb data and developed new models with a total of 18,886 molecules with activity cutoffs of 10 μM, 1 μM, and 100 nM. These data sets were used to evaluate different machine learning methods (including deep learning) and metrics and to generate predictions for additional molecules published in 2017. One Mtb model, a combined in vitro and in vivo data Bayesian model at a 100 nM activity yielded the following metrics for 5-fold cross validation: accuracy = 0.88, precision = 0.22, recall = 0.91, specificity = 0.88, kappa = 0.31, and MCC = 0.41. We have also curated an evaluation set ( n = 153 compounds) published in 2017, and when used to test our model, it showed the comparable statistics (accuracy = 0.83, precision = 0.27, recall = 1.00, specificity = 0.81, kappa = 0.36, and MCC = 0.47). We have also compared these models with additional machine learning algorithms showing Bayesian machine learning models constructed with literature Mtb data generated by different laboratories generally were equivalent to or outperformed deep neural networks with external test sets. Finally, we have also compared our training and test sets to show they were suitably diverse and different in order to represent useful evaluation sets. Such Mtb machine learning models could help prioritize compounds for testing in vitro and in vivo.

Efficacy of pyrazinoic acid dry powder aerosols in resolving necrotic and non-necrotic granulomas in a guinea pig model of tuberculosis

New therapeutic strategies are needed to treat drug resistant tuberculosis (TB) and to improve treatment for drug sensitive TB. Pyrazinamide (PZA) is a critical component of current first-line TB therapy. However, the rise in PZA-resistant TB cases jeopardizes the future utility of PZA. To address this problem, we used the guinea pig model of TB and tested the efficacy of an inhaled dry powder combination, referred to as Pyrazinoic acid/ester Dry Powder (PDP), which is comprised of pyrazinoic acid (POA), the active moiety of PZA, and pyrazinoic acid ester (PAE), which is a PZA analog. Both POA and PAE have the advantage of being able to act on PZA-resistant Mycobacterium tuberculosis. When used in combination with oral rifampicin (R), inhaled PDP had striking effects on tissue pathology. Effects were observed in lungs, the site of delivery, but also in the spleen and liver indicating both local and systemic effects of inhaled PDP. Tissue granulomas that harbor M. tuberculosis in a persistent state are a hallmark of TB and they pose a challenge for therapy. Compared to other treatments, which preferentially cleared non-necrotic granulomas, R+PDP reduced necrotic granulomas more effectively. The increased ability of R+PDP to act on more recalcitrant necrotic granulomas suggests a novel mechanism of action. The results presented in this report reveal the potential for developing therapies involving POA that are optimized to target necrotic as well as non-necrotic granulomas as a means of achieving more complete sterilization of M. tuberculosis bacilli and preventing disease relapse when therapy ends.

The EU approved antimalarial pyronaridine shows antitubercular activity and synergy with rifampicin, targeting RNA polymerase

The search for compounds with biological activity for many diseases is turning increasingly to drug repurposing. In this study, we have focused on the European Union-approved antimalarial pyronaridine which was found to have in vitro activity against Mycobacterium tuberculosis (MIC 5 μg/mL). In macromolecular synthesis assays, pyronaridine resulted in a severe decrease in incorporation of ¹⁴C-uracil and ¹⁴C-leucine similar to the effect of rifampicin, a known inhibitor of M. tuberculosis RNA polymerase. Surprisingly, the co-administration of pyronaridine (2.5 μg/ml) and rifampicin resulted in in vitro synergy with an MIC 0.0019-0.0009 μg/mL. This was mirrored in a THP-1 macrophage infection model, with a 16-fold MIC reduction for rifampicin when the two compounds were co-administered versus rifampicin alone. Docking pyronaridine in M. tuberculosis RNA polymerase suggested the potential for it to bind outside of the RNA polymerase rifampicin binding pocket. Pyronaridine was also found to have activity against a M. tuberculosis clinical isolate resistant to rifampicin, and when combined with rifampicin (10% MIC) was able to inhibit M. tuberculosis RNA polymerase in vitro. All these findings, and in particular the synergistic behavior with the antitubercular rifampicin, inhibition of RNA polymerase in combination in vitro and its current use as a treatment for malaria, may suggest that pyronaridine could also be used as an adjunct for treatment against M. tuberculosis infection. Future studies will test potential for in vivo synergy, clinical utility and attempt to develop pyronaridine analogs with improved potency against M. tuberculosis RNA polymerase when combined with rifampicin.

Dual Mechanism of Action of 5-Nitro-1,10-Phenanthroline against Mycobacterium tuberculosis

New chemotherapeutic agents with novel mechanisms of action are urgently required to combat the challenge imposed by the emergence of drug-resistant mycobacteria. In this study, a phenotypic whole-cell screen identified 5-nitro-1,10-phenanthroline (5NP) as a lead compound. 5NP-resistant isolates harbored mutations that were mapped to fbiB and were also resistant to the bicyclic nitroimidazole PA-824. Mechanistic studies confirmed that 5NP is activated in an F₄₂₀-dependent manner, resulting in the formation of 1,10-phenanthroline and 1,10-phenanthrolin-5-amine as major metabolites in bacteria. Interestingly, 5NP also killed naturally resistant intracellular bacteria by inducing autophagy in macrophages. Structure-activity relationship studies revealed the essentiality of the nitro group for in vitro activity, and an analog, 3-methyl-6-nitro-1,10-phenanthroline, that had improved in vitro activity and in vivo efficacy in mice compared with that of 5NP was designed. These findings demonstrate that, in addition to a direct mechanism of action against Mycobacterium tuberculosis, 5NP also modulates the host machinery to kill intracellular pathogens.

Emerging Approaches to Tuberculosis Drug Development: At Home in the Metabolome

Once considered a crowning achievement of modern drug development, tuberculosis (TB) chemotherapy has proven increasingly unable to keep pace with the spread of the pandemic and rise of drug resistance. Efforts to revive the TB drug development pipeline have, in the meantime, faltered. Closer analysis reveals key experimental deficiencies that have hindered our ability to 'reverse engineer' knowledge of antibiotic mechanisms into rational drug development. Here, we discuss the emerging potential of metabolomics; the systems level study of small molecule metabolites, to help overcome these gaps and serve as a unique biochemical bridge between the phenotypic properties of chemical compounds and biological targets.