Docking-based virtual screening of known drugs against murE of Mycobacterium tuberculosis towards repurposing for TB

Potential Repurposed Drug Candidates for Tuberculosis Treatment: Progress and Update of Drugs Identified in Over a Decade

The devastating impact of Tuberculosis (TB) has been a menace to mankind for decades. The World Health Organization (WHO) End TB Strategy aims to reduce TB mortality up to 95% and 90% of overall TB cases worldwide, by 2035. This incessant urge will be achieved with a breakthrough in either a new TB vaccine or novel drugs with higher efficacy. However, the development of novel drugs is a laborious process involving a timeline of almost 20-30 years with huge expenditure; on the other hand, repurposing previously approved drugs is a viable technique for overcoming current bottlenecks in the identification of new anti-TB agents. The present comprehensive review discusses the progress of almost all the repurposed drugs that have been identified to the present day (∼100) and are in the development or clinical testing phase against TB. We have also emphasized the efficacy of repurposed drugs in combination with already available frontline anti-TB medications along with the scope of future investigations. This study would provide the researchers a detailed overview of nearly all identified anti-TB repurposed drugs and may assist them in selecting the lead compounds for further in vivo/clinical research.

Tuberculosis drug discovery: Progression and future interventions in the wake of emerging resistance

The emergence of drug resistance continues to afflict TB control where drug resistant strains have become a global health concern. Contrary to drug-sensitive TB, the treatment of MDR/XDR-TB is more complicated requiring the administration of second-line drugs that are inefficient than the first line drugs and are associated with greater side effects. The emergence of drug resistant Mtb strains had coincided with an innovation void in the field of drug discovery of anti-mycobacterials. However, the approval of bedaquiline and delamanid recently for use in MDR/XDR-TB has given an impetus to the TB drug discovery. The review discusses the drug discovery efforts in the field of tuberculosis with a focus on the strategies adopted and challenges confronted by TB research community. Here, we discuss the diverse clinical candidates in the current TB drug discovery pipeline. There is an urgent need to combat the current TB menace through multidisciplinary approaches and strategies making use of the recent advances in understanding the molecular biology and pathogenesis of Mtb. The review highlights the recent advances in drug discovery, with the host directed therapeutics and nanoparticles-drug delivery coming up as important tools to fight tuberculosis in the future.

Exploiting the glycan receptor-binding site of PltB subunit in salmonella typhi toxin for novel inhibitors: An in-silico approach

Salmonella typhi (S. typhi), a gram-negative bacterium responsible for gastroenteritis - typhoid - has continually evolved into drug-resistant strains with the most recent being the haplotype H58 strain. The haplotype H58 strain has spread across the globe causing outbreaks in countries such as Pakistan, Zimbabwe, and several underdeveloped regions located in parts of Asia, Central and Southern Africa. Treatment by conventional antibiotics is gradually failing as recorded in the affected countries, including Nigeria and Barcelona - Spain. Therefore, the research presented herein aims to identify novel compounds targeting the typhoid toxin of S. typhi which is responsible for several virulence factors associated with typhoid. In-silico methods that include virtual screening, molecular dynamics (MD) and computation of binding free energies were utilized. Our research identified furan derivatives as top-scoring lead compounds from a database of more than 1,5 million compounds curated from the ZINC20 database. Post docking analysis and trajectory analysis post-MD simulations showed that π - π interactions are vital to holding the ligand within the receptor pocket whereas hydrophobic and Van der Waals interactions are crucial for the overall bonding. Through docking, MD simulations and free energy computations, we hypothesize that ZINC000114543311, ZINC000794380763 and ZINC000158992484 (docking scores of -9.06, -8.20 and -8.12 in conjunction with ΔG values of -64.691, -63.670 and -59.024 kcal/mol, respectively) bear a great potential to pave the way to fighting antibiotic resistance for typhoid in both humans and animals. The compounds presented here can also be used as lead materials for designing other compounds targeting the Salmonella typhi toxin.

Antiviral fungal metabolites and some insights into their contribution to the current COVID-19 pandemic

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak, which started in late 2019, drove the scientific community to conduct innovative research to contain the spread of the pandemic and to care for those already affected. Since then, the search for new drugs that are effective against the virus has been strengthened. Featuring a relatively low cost of production under well-defined methods of cultivation, fungi have been providing a diversity of antiviral metabolites with unprecedented chemical structures. In this review, we present viral RNA infections highlighting SARS-CoV-2 morphogenesis and the infectious cycle, the targets of known antiviral drugs, and current developments in this area such as drug repurposing. We also explored the metabolic adaptability of fungi during fermentation to produce metabolites active against RNA viruses, along with their chemical structures, and mechanisms of action. Finally, the state of the art of research on SARS-CoV-2 inhibitors of fungal origin is reported, highlighting the metabolites selected by docking studies.

The Mur Enzymes Chink in the Armour of Mycobacterium tuberculosis cell wall

TUBERCULOSIS: (TB) transmitted by Mycobacterium tuberculosis (Mtb) is one of the top 10 causes of death globally. Currently, the widespread occurrence of resistance toward Mtb strains is becoming a significant concern to public health. This scenario exaggerated the need for the discovery of novel targets and their inhibitors. Targeting the "Mtb cell wall peptidoglycan synthesis" is an attractive strategy to overcome drug resistance. Mur enzymes (MurA-MurF) play essential roles in the peptidoglycan synthesis by catalyzing the ligation of key amino acid residues to the stem peptide. These enzymes are unique and confined to the eubacteria and are absent in humans, representing potential targets for anti-tubercular drug discovery. Mtb Mur ligases with the same catalytic mechanism share conserved amino acid regions and structural features that can conceivably exploit for the designing of the inhibitors, which can simultaneously target more than one isoforms (MurC-MurF) of the enzyme. In light of these findings in the current review, we have discussed the recent advances in medicinal chemistry of Mtb Mur enzymes (MurA-MurF) and their inhibitors, offering attractive multi-targeted strategies to combat the problem of drug-resistant in M. tuberculosis.

Inhibitory mechanism of an antifungal drug, caspofungin against amyloid β peptide aggregation: Repurposing via neuroinformatics and an experimental approach

The multifactorial neurological condition called Alzheimer's disease (AD) primarily affects elderly individuals. Despite the calamitous consequences of AD, curative strategies for a regimen to apply remain inadequate as several factors contribute to AD etiology. Drug repurposing is an advance strategy prior to drug discovery as various effective drugs perform through alteration of multiple targets, and the present "poly-pharmacology" can be a curative approach to complex disorders. AD's multifactorial behavior actively encourages the hypothesis for a drug design approach focused on drug repurposing. In this study, we discovered that an antifungal drug, Caspofungin (CAS) is a potent Aβ aggregation inhibitor that displays significantly reduced toxicity associated with AD. Drug reprofiling and REMD simulations demonstrated that CAS interacts with the β-sheet section, known as Aβ amyloid fibrils hotspot. CAS leads to destabilization of β-sheet and, conclusively, in its devaluation. Later, in vitro experiments were acquired in which the fibrillar volume was reduced for CAS-treated Aβ peptide. For the first time ever, this study has determined an antifungal agent as the Aβ amyloid aggregation's potent inhibitor. Several efficient sequence-reliant potent inhibitors can be developed in future against the amyloid aggregation for different amyloid peptide by the processing and conformational optimization of CAS.

DockingApp RF: A State-of-the-Art Novel Scoring Function for Molecular Docking in a User-Friendly Interface to AutoDock Vina

Motivation: Bringing a new drug to the market is expensive and time-consuming. To cut the costs and time, computer-aided drug design (CADD) approaches have been increasingly included in the drug discovery pipeline. However, despite traditional docking tools show a good conformational space sampling ability, they are still unable to produce accurate binding affinity predictions. This work presents a novel scoring function for molecular docking seamlessly integrated into DockingApp, a user-friendly graphical interface for AutoDock Vina. The proposed function is based on a random forest model and a selection of specific features to overcome the existing limits of Vina’s original scoring mechanism. A novel version of DockingApp, named DockingApp RF, has been developed to host the proposed scoring function and to automatize the rescoring procedure of the output of AutoDock Vina, even to nonexpert users. Results: By coupling intermolecular interaction, solvent accessible surface area features and Vina’s energy terms, DockingApp RF’s new scoring function is able to improve the binding affinity prediction of AutoDock Vina. Furthermore, comparison tests carried out on the CASF-2013 and CASF-2016 datasets demonstrate that DockingApp RF’s performance is comparable to other state-of-the-art machine-learning- and deep-learning-based scoring functions. The new scoring function thus represents a significant advancement in terms of the reliability and effectiveness of docking compared to AutoDock Vina’s scoring function. At the same time, the characteristics that made DockingApp appealing to a wide range of users are retained in this new version and have been complemented with additional features.

Drug targets for COVID-19 therapeutics: Ongoing global efforts

The current global pandemic COVID-19 caused by the SARS-CoV-2 virus has already inflicted insurmountable damage both to the human lives and global economy. There is an immediate need for identification of effective drugs to contain the disastrous virus outbreak. Global efforts are already underway at a war footing to identify the best drug combination to address the disease. In this review, an attempt has been made to understand the SARS-CoV-2 life cycle, and based on this information potential druggable targets against SARS-CoV-2 are summarized. Also, the strategies for ongoing and future drug discovery against the SARS-CoV-2 virus are outlined. Given the urgency to find a definitive cure, ongoing drug repurposing efforts being carried out by various organizations are also described. The unprecedented crisis requires extraordinary efforts from the scientific community to effectively address the issue and prevent further loss of human lives and health.

α-Glucosidase Inhibitor Can Effectively Inhibit the Risk of Tuberculosis in Patients with Diabetes: A Nested Case-Control Study

Diabetes mellitus (DM) and tuberculosis (TB) are major public health and economic burdens. DM increases Mycobacterium tuberculosis (M.tb) infection rates and treatment durations. This study evaluated the relationship between five classes of oral DM medications and TB infection risk in DM patients. We used longitudinal records from the Taiwan Longitudinal Health Insurance Research Database. DM patients were identified using the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 250 and A code A181. TB patients were identified using ICD-9-CM code 010.x-017.x. Oral DM medications were divided into five classes: sulfonylureas, biguanides, meglitinides, α-glucosidase inhibitors (AGIs), and thiazolidinediones. Users were classified as nonusers, low-concentration users, and high-concentration users. The incidence rate ratio (IRR) was derived using multivariate Poisson regression to calculate the relative risk of TB infection. DM patients using low- and high-concentration AGIs had significantly lower TB infection risks compared with nonusers. The IRRs of the sulfonylureas and AGI users were [CI] 0.693-0.948) and (95% CI 0.651-0.995), respectively. The other four classes of medications exhibited no significant effect on TB infection risk in DM patients. Furthermore, DM patients using high-concentration AGIs had a significantly lower TB infection risk compared with those using low-concentration AGIs (IRR 0.918, 95% CI: 0.854-0.987). We noted a dose-response relationship in the effects of DM medications on TB risk. Accordingly, we suggest that DM patients use AGIs to benefit from their protective effect on TB infection risk.

Repurposed drug candidates for antituberculosis therapy

Antibiotics have been a key part of clinical treatments for more than 70 years. Long-term use of antimicrobial treatments has led to the development of severe bacterial resistance, which has become increasingly serious due to antibiotic abuse, resulting in the treatment of bacterial infections becoming challenging. The repurposing of approved drugs presents a promising strategy to address current bottlenecks in the development of novel antibacterial agents. Drug repurposing is a cost-effective emerging strategy, which aims to treat resistant infectious diseases by identifying known drugs with predicted efficacy for diseases other than the target disease. This strategy has potential in the treatment of tuberculosis (TB), particularly drug-resistant TB. In recent years, a panel of drugs approved for clinical use or clinical trials, such as linezolid, vancomycin and celecoxib, have been found to have anti-TB activities. However, the utility of drug repurposing is limited by the number of candidate compounds and their low activities. The low activities of repurposed drugs have slowed the development of a drug-repurposing strategy for anti-TB drugs. The present review discusses progress in the discovery of new anti-TB agents through drug repurposing since 2014. We also discuss the challenges faced and analyze the innovative ways that are being used to overcome these difficulties. This review may provide a useful guide for researchers in the field of drug repurposing.

In Silico Strategies in Tuberculosis Drug Discovery

Tuberculosis (TB) remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2018. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel TB drugs. Discovering new and more potent antibiotics that target novel TB protein targets is an attractive strategy towards controlling the global TB epidemic. In silico strategies can be applied at multiple stages of the drug discovery paradigm to expedite the identification of novel anti-TB therapeutics. In this paper, we discuss the current TB treatment, emergence of drug resistance, and the effective application of computational tools to the different stages of TB drug discovery when combined with traditional biochemical methods. We will also highlight the strengths and points of improvement in in silico TB drug discovery research, as well as possible future perspectives in this field.

RepTB: a gene ontology based drug repurposing approach for tuberculosis

Tuberculosis (TB) is the world’s leading infectious killer with 1.8 million deaths in 2015 as reported by WHO. It is therefore imperative that alternate routes of identification of novel anti-TB compounds are explored given the time and costs involved in new drug discovery process. Towards this, we have developed RepTB. This is a unique drug repurposing approach for TB that uses molecular function correlations among known drug-target pairs to predict novel drug-target interactions. In this study, we have created a Gene Ontology based network containing 26,404 edges, 6630 drug and 4083 target nodes. The network, enriched with molecular function ontology, was analyzed using Network Based Inference (NBI). The association scores computed from NBI are used to identify novel drug-target interactions. These interactions are further evaluated based on a combined evidence approach for identification of potential drug repurposing candidates. In this approach, targets which have no known variation in clinical isolates, no human homologs, and are essential for Mtb’s survival and or virulence are prioritized. We analyzed predicted DTIs to identify target pairs whose predicted drugs may have synergistic bactericidal effect. From the list of predicted DTIs from RepTB, four TB targets, namely, FolP1 (Dihydropteroate synthase), Tmk (Thymidylate kinase), Dut (Deoxyuridine 5′-triphosphate nucleotidohydrolase) and MenB (1,4-dihydroxy-2-naphthoyl-CoA synthase) may be selected for further validation. In addition, we observed that in some cases there is significant chemical structure similarity between predicted and reported drugs of prioritized targets, lending credence to our approach. We also report new chemical space for prioritized targets that may be tested further. We believe that with increasing drug-target interaction dataset RepTB will be able to offer better predictive value and is amenable for identification of drug-repurposing candidates for other disease indications too.