Synthesis and Structure-Activity relationship of 1-(5-isoquinolinesulfonyl)piperazine analogues as inhibitors of Mycobacterium tuberculosis IMPDH

Benzylurea Protects hPDLFs Against LPS-Induced Mitochondrial Dysfunction Through MTCH2

OBJECTIVE

The aim of this study is to explore the mechanism of benzylurea in the inflammatory injury of human periodontal ligament fibroblasts (hPDLFs).

METHODS

An inflammation model of hPDLFs was established using LPS. Nuclear transport of nuclear transcription factor-κB (NF-κB), secretion of cytokines, and the morphology and distribution of F-actin were determined. Mitochondrial function was assessed by measuring mitochondrial membrane potential (MMP), mitochondrial permeability transition pore (mPTP), and reactive oxygen species (ROS) levels. The expression of mitochondrial carrier homolog 2 (MTCH2) and Cytochrome b5 type B (CYB5B) was detected.

RESULTS

Benzylurea alleviated the effects of lipopolysaccharide (LPS) on the proliferation and apoptosis of hPDLFs. It reduced the release of inflammatory cytokines and inhibited NF-κB nuclear translocation. Benzylurea improved mitochondrial function by regulating MMP and preventing excessive mPTP opening. Furthermore, LPS elevated the expression of MTCH2 and reduced the expression of CYB5B in hPDLFs. However, these effects can be inhibited by benzylurea. The altered expression of MTCH2 directly affected CYB5B expression, the release of inflammatory cytokines, and the activation of nuclear translocation of NF-κB.

CONCLUSION

CYB5B may act as an effector of MTCH2, with benzylurea enhancing mitochondrial function and protecting hPDLFs from LPS-induced injury through MTCH2.

Discovery of potent dihydro-oxazinoquinolinone inhibitors of GuaB for the treatment of tuberculosis

Tuberculosis is the leading cause of death from an infectious disease, and is caused by Mycobacterium tuberculosis (M.tb). More than 1 billion people worldwide are thought to harbor an M.tb infection. The multidrug therapy that represents the current standard of care requires a minimum of four months of dosing and drug resistant Mycobacterium tuberculosis treatment regimens are significantly longer. Inosine-5'-monophosphate dehydrogenase (GuaB) is the enzyme that performs the rate-limiting step in de novo guanine nucleotide biosynthesis that is critical for growth and viability of bacteria including M.tb. The development of a novel antibiotic that inhibits GuaB could combine with existing therapies in novel ways and thereby contribute to effective therapeutic regimens for the treatment of tuberculosis. Here we describe the discovery of structurally distinct small molecule GuaB inhibitors that are potent against M.tb H37Ra and H37Rv strains and have desirable safety and ADME profiles.

ResMAP-a saturation mutagenesis platform enabling parallel profiling of target-specific resistance-conferring mutations in Plasmodium

New and improved drugs are required for the treatment and ultimate eradication of malaria. The efficacy of front-line therapies is now threatened by emerging drug resistance; thus, new tools to support the development of drugs with a lower propensity for resistance are needed. Here, we describe the development of a RESistance Mapping And Profiling (ResMAP) platform for the identification of resistance-conferring mutations in Plasmodium drug targets. Proof-of-concept studies focused on interrogating the antimalarial drug target, Plasmodium falciparum lysyl tRNA synthetase (PfKRS). Saturation mutagenesis was used to construct a plasmid library encoding all conceivable mutations within a 20-residue span at the base of the PfKRS ATP-binding pocket. The superior transfection efficiency of Plasmodium knowlesi was exploited to generate a high coverage parasite library expressing PfKRS bearing all possible amino acid changes within this region of the enzyme. The selection of the library with PfKRS inhibitors, cladosporin and DDD01510706, successfully identified multiple resistance-conferring substitutions. Genetic validation of a subset of these mutations confirmed their direct role in resistance, with computational modeling used to dissect the structural basis of resistance. The application of ResMAP to inform the development of resistance-resilient antimalarials of the future is discussed.

IMPORTANCE

An increase in treatment failures for malaria highlights an urgent need for new tools to understand and minimize the spread of drug resistance. We describe the development of a RESistance Mapping And Profiling (ResMAP) platform for the identification of resistance-conferring mutations in Plasmodium spp, the causative agent of malaria. Saturation mutagenesis was used to generate a mutation library containing all conceivable mutations for a region of the antimalarial-binding site of a promising drug target, Plasmodium falciparum lysyl tRNA synthetase (PfKRS). Screening of this high-coverage library with characterized PfKRS inhibitors revealed multiple resistance-conferring substitutions including several clinically relevant mutations. Genetic validation of these mutations confirmed resistance of up to 100-fold and computational modeling dissected their role in drug resistance. We discuss potential applications of this data including the potential to design compounds that can bypass the most serious resistance mutations and future resistance surveillance.

Identification of CXCR4 inhibitors as a key therapeutic small molecule in renal fibrosis

The final stage of almost all chronic kidney diseases is renal fibrosis. Simple wounds or persistent inflammation can cause tissue inflammation, which, in the case of the kidney, results in scarring. Vascular sclerosis, tubulointerstitial fibrosis and glomerular fibrosis are all types of kidney fibrosis. Renal damage and fibrosis are caused by elevated expression of CXCR4. This study aimed to identify possible pharmacological agents which could bind to and inhibit isoform I of CXCR4 and determine their strength of interactions. The I-TASSER, Galaxyweb and Robetta were used to predict and refine the structure of the CXCR4 protein. ModBase was used to improve the loops, and then the quality was evaluated by using the ERRAT value (92.15) and Ramachandran plot. The improved 3D structure was subjected to small molecule database docking using Maestro (from Schrodinger) and the glide module. GROMACS was used to simulate molecules with the three top low glide scores and the best ADME properties. The best glide score was achieved by ligand ID 4990 (-11.5). Simulations, free energy landscape and residue decomposition analysis revealed that 4990 interacted more consistently with CXCR4 than the other two small molecules.Communicated by Ramaswamy H. Sarma.

Repurposing Study of 4-Acyl-1-phenylaminocarbonyl-2-substituted-piperazine Derivatives as Potential Anticancer Agents-In Vitro Evaluation against Breast Cancer Cells

Breast cancer is the most common type of cancer in women. Although current treatments can increase patient survival, they are rarely curative when the disease is advanced (metastasis). Therefore, there is an urgent need to develop new cytotoxic drugs with a high selectivity toward cancer cells. Since repurposing approved drugs for cancer therapy has been a successful strategy in recent years, in this study, we screened a library of antiviral piperazine-derived compounds as anticancer agents. The compounds included a piperazine ring and aryl urea functions, which are privileged structures present in several anti-breast cancer drugs. The selective cytotoxic activity of a set of thirty-four 4-acyl-2-substituted piperazine urea derivatives against MCF7 breast cancer cells and MCF 10A normal breast cells was determined. Compounds 31, 32, 35, and 37 showed high selective anticancer activity against breast cancer cells and were also tested against another common type of cancer, non-small cell lung cancer (A549 lung cancer cells versus MRC-5 lung normal cells). Compounds 35 and 37 also showed selectivity against lung cancer cells. These results suggest that compounds 35 and 37 may be promising hit compounds for the development of new anticancer agents.

The roles of HDAC with IMPDH and mTOR with JAK as future targets in the treatment of rheumatoid arthritis with combination therapy

Various studies have shown that cytokines are important regulators in rheumatoid arthritis (RA). In synovial inflammation alteration of the enzyme HDAC, IMPDH enzyme, mTOR pathway, and JAK pathway increase cytokine level. These increased cytokine levels are responsible for the inflammation in RA. Inflammation is a physiological and normal reaction of the immune system against dangerous stimuli such as injury and infection. The cytokine-based approach improves the treatment of RA. To reach this goal, various researchers and scientists are working more aggressively by using a combination approach. The present review of combination therapy provides essential evidence about the possible synergistic effect of combinatorial agents. We have focused on the effects of HDAC inhibitor with IMPDH inhibitor and mTOR inhibitor with JAK inhibitor in combination for the treatment of RA. Combining various targeted strategies can be helpful for the treatment of RA.

C-1 Substituted isoquinolines potentiate the antimycobacterial activity of rifampicin and ethambutol

Introduction

The emergence of extensively drug-resistant strains of Mycobacterium tuberculosis threatens decades of progress in the treatment of a disease which remains one of the leading infectious causes of death worldwide. The development of novel antimycobacterial compounds is therefore essential to reinforce the existing antitubercular drug discovery pipeline. There is also interest in new compounds which can synergize with existing antitubercular drugs and can be deployed as part of a combination therapy. This strategy could serve to delay the emergence of resistance to first-line anti-tuberculosis drugs and increase their efficacy against resistant strains of tuberculosis. Previous research has established that several C-1 substituted tetrahydroisoquinolines have antimycobacterial activity. Here we sought to expand our understanding of their antimycobacterial structure activity relationships and their potential to act as adjunct therapies alongside existing antitubercular drugs.

Methods

Three chemical series were synthesised and assayed for their antimycobacterial potency, mammalian cell toxicity, inhibition of whole-cell efflux and synergism with isoniazid, rifampicin, and ethambutol.

Results

Several compounds were found to inhibit the growth of mycobacteria. Potent inhibitors of whole-cell efflux were also identified, as well as compounds which exhibited synergism with rifampicin and ethambutol.

Conclusions

Structure-activity relationships were identified for antimycobacterial potency, improved selectivity, whole cell efflux inhibition and synergism. Potent whole-cell efflux inhibitors and synergistic compounds were identified, suggesting potential development as adjuncts to existing anti-tuberculosis chemotherapy.

Using Graph-Based Signatures to Guide Rational Antibody Engineering

Antibodies are essential experimental and diagnostic tools and as biotherapeutics have significantly advanced our ability to treat a range of diseases. With recent innovations in computational tools to guide protein engineering, we can now rationally design better antibodies with improved efficacy, stability, and pharmacokinetics. Here, we describe the use of the mCSM web-based in silico suite, which uses graph-based signatures to rapidly identify the structural and functional consequences of mutations, to guide rational antibody engineering to improve stability, affinity, and specificity.

A d-Phenylalanine-Benzoxazole Derivative Reveals the Role of the Essential Enzyme Rv3603c in the Pantothenate Biosynthetic Pathway of Mycobacterium tuberculosis

New drugs and new targets are urgently needed to treat tuberculosis. We discovered that d-phenylalanine-benzoxazole Q112 displays potent antibacterial activity against Mycobacterium tuberculosis (Mtb) in multiple media and in macrophage infections. A metabolomic profiling indicates that Q112 has a unique mechanism of action. Q112 perturbs the essential pantothenate/coenzyme A biosynthetic pathway, depleting pantoate while increasing ketopantoate, as would be expected if ketopantoate reductase (KPR) were inhibited. We searched for alternative KPRs, since the enzyme annotated as PanE KPR is not essential in Mtb. The ketol-acid reductoisomerase IlvC catalyzes the KPR reaction in the close Mtb relative Corynebacterium glutamicum, but Mtb IlvC does not display KPR activity. We identified the essential protein Rv3603c as an orthologue of PanG KPR and demonstrated that a purified recombinant Rv3603c has KPR activity. Q112 inhibits Rv3603c, explaining the metabolomic changes. Surprisingly, pantothenate does not rescue Q112-treated bacteria, indicating that Q112 has an additional target(s). Q112-resistant strains contain loss-of-function mutations in the twin arginine translocase TatABC, further underscoring Q112's unique mechanism of action. Loss of TatABC causes a severe fitness deficit attributed to changes in nutrient uptake, suggesting that Q112 resistance may derive from a decrease in uptake.

The Enzymatic Activity of Inosine 5'-Monophosphate Dehydrogenase May Not Be a Vulnerable Target for Staphylococcus aureus Infections

Many bacterial pathogens, including Staphylococcus aureus, require inosine 5'-monophosphate dehydrogenase (IMPDH) for infection, making this enzyme a promising new target for antibiotics. Although potent selective inhibitors of bacterial IMPDHs have been reported, relatively few have displayed antibacterial activity. Here we use structure-informed design to obtain inhibitors of S. aureus IMPDH (SaIMPDH) that have potent antibacterial activity (minimal inhibitory concentrations less than 2 μM) and low cytotoxicity in mammalian cells. The physicochemical properties of the most active compounds were within typical Lipinski/Veber space, suggesting that polarity is not a general requirement for achieving antibacterial activity. Five compounds failed to display activity in mouse models of septicemia and abscess infection. Inhibitor-resistant S. aureus strains readily emerged in vitro. Resistance resulted from substitutions in the cofactor/inhibitor binding site of SaIMPDH, confirming on-target antibacterial activity. These mutations decreased the binding of all inhibitors tested, but also decreased catalytic activity. Nonetheless, the resistant strains had comparable virulence to wild-type bacteria. Surprisingly, strains expressing catalytically inactive SaIMPDH displayed only a mild virulence defect. Collectively these observations question the vulnerability of the enzymatic activity of SaIMPDH as a target for the treatment of S. aureus infections, suggesting other functions of this protein may be responsible for its role in infection.

Tuberculosis: An Update on Pathophysiology, Molecular Mechanisms of Drug Resistance, Newer Anti-TB Drugs, Treatment Regimens and Host- Directed Therapies

Human tuberculosis (TB) is primarily caused by Mycobacterium tuberculosis (Mtb) that inhabits inside and amidst immune cells of the host with adapted physiology to regulate interdependent cellular functions with intact pathogenic potential. The complexity of this disease is attributed to various factors such as the reactivation of latent TB form after prolonged persistence, disease progression specifically in immunocompromised patients, advent of multi- and extensivelydrug resistant (MDR and XDR) Mtb strains, adverse effects of tailor-made regimens, and drug-drug interactions among anti-TB drugs and anti-HIV therapies. Thus, there is a compelling demand for newer anti-TB drugs or regimens to overcome these obstacles. Considerable multifaceted transformations in the current TB methodologies and molecular interventions underpinning hostpathogen interactions and drug resistance mechanisms may assist to overcome the emerging drug resistance. Evidently, recent scientific and clinical advances have revolutionised the diagnosis, prevention, and treatment of all forms of the disease. This review sheds light on the current understanding of the pathogenesis of TB disease, molecular mechanisms of drug-resistance, progress on the development of novel or repurposed anti-TB drugs and regimens, host-directed therapies, with particular emphasis on underlying knowledge gaps and prospective for futuristic TB control programs.

Combining structure and genomics to understand antimicrobial resistance

Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.

An appraisal of anti-mycobacterial activity with structure-activity relationship of piperazine and its analogues: A review

Piperazine, is privileged six membered nitrogen containing heterocyclic ring also known as 1,4-Diazacyclohexane. Consequently, piperazine is a versatile medicinally important scaffold and is an essential core in numerous marketed drugs with diverse pharmacological activities. In recent years several potent molecules containing piperazine as an essential subunit of the structural frame have been reported, especially against Mycobacterium tuberculosis (MTB). Remarkably, a good number of these reported molecules also displayed potential activity against multidrug-resistant (MDR), and extremely drug-resistant (XDR) strains of MTB. In this review, we have made a concerted effort to retrace anti-mycobacterial compounds for the past five decades (1971-2019) specifically where piperazine has been used as a vital building block. This review will benefit medicinal chemists as it elaborates on the design, rationale and structure-activity relationship (SAR) of the reported potent piperazine based anti-TB molecules, which in turn will assist them in addressing the gaps, exploiting the reported strategies and developing safer, selective, and cost-effective anti-mycobacterial agents.

DynaMut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations

Predicting the effect of missense variations on protein stability and dynamics is important for understanding their role in diseases, and the link between protein structure and function. Approaches to estimate these changes have been proposed, but most only consider single‐point missense variants and a static state of the protein, with those that incorporate dynamics are computationally expensive. Here we present DynaMut2, a web server that combines Normal Mode Analysis (NMA) methods to capture protein motion and our graph‐based signatures to represent the wildtype environment to investigate the effects of single and multiple point mutations on protein stability and dynamics. DynaMut2 was able to accurately predict the effects of missense mutations on protein stability, achieving Pearson's correlation of up to 0.72 (RMSE: 1.02 kcal/mol) on a single point and 0.64 (RMSE: 1.80 kcal/mol) on multiple‐point missense mutations across 10‐fold cross‐validation and independent blind tests. For single‐point mutations, DynaMut2 achieved comparable performance with other methods when predicting variations in Gibbs Free Energy (ΔΔG) and in melting temperature (ΔT_m). We anticipate our tool to be a valuable suite for the study of protein flexibility analysis and the study of the role of variants in disease. DynaMut2 is freely available as a web server and API at http://biosig.unimelb.edu.au/dynamut2.

Current advances in the clinical development of anti-tubercular agents

Tuberculosis (TB) is a communicable airborne infectious disease caused by the Mycobacterium tuberculosis (MTB) that primarily affects the lungs, and can disseminate to other parts of the body. MTB is one of the most dangerous pathogens, killing about 1.4 million people annually worldwide. Although the standard treatment of TB is comprised of four anti-TB drugs, the emergence of multidrug-resistant (MDR) and extensive drug-resistant (XDR) strains in the recent past and associated side effects have affected the tailor-made regimens. Notably, existing therapies approved by the World Health Organisation (WHO) can only treat less than 50% of drug-resistant TB. Therefore, an expeditious pace in the TB research is highly needed in search of effective, affordable, least toxic novel drugs with shorter regimens to reach the goals viz. 2020 milestones End TB strategy set by the WHO. Currently, twenty-three drug-like molecules are under investigation in different stages of clinical trials. These newer agents are expected to be effective against the resistant strains. This article summarizes the properties, merits, demerits, and the probability of their success as novel potential therapeutic agents.

Synthesis, molecular docking and molecular dynamic simulation studies of 2-chloro-5-[(4-chlorophenyl)sulfamoyl]-N-(alkyl/aryl)-4-nitrobenzamide derivatives as antidiabetic agents

A series of 2-chloro-5-[(4-chlorophenyl)sulfamoyl]-N-(alkyl/aryl)-4-nitrobenzamide derivatives (5a-5v) has been synthesized and confirmed by physicochemical(R_f, melting point) and spectral means (IR, ¹HNMR, ¹³CNMR). The results of in vitro antidiabetic study against α-glucosidase indicated that compound 5o bearing 2-CH₃-5-NO₂ substituent on phenyl ring was found to be the most active compound against both enzymes. The electron donating (CH₃) group and electron withdrawing (NO₂) group on a phenyl ring highly favoured the inhibitory activity against these enzymes. The docking simulations study revealed that these synthesized compounds displayed hydrogen bonding, electrostatic and hydrophobic interactions with active site residues. The structure activity relationship studies of these compounds were also corroborated with the help of molecular modeling studies. Molecular dynamic simulations have been done for top most active compound for validating its α-glucosidase and α-amylase inhibitory potential, RMSD analysis of ligand protein complex suggested the stability of top most active compound 5o in binding site of target proteins. In silico ADMET results showed that synthesized compounds were found to have negligible toxicity, good solubility and absorption profile as the synthesized compounds fulfilled Lipinski's rule of 5 and Veber's rule.

Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine

Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.

Drug-resistance in Mycobacterium tuberculosis: where we stand

Tuberculosis (TB), an infectious disease caused by the bacterium Mycobacterium tuberculosis (Mtb), has burdened vulnerable populations in modern day societies for decades. Recently, this global health threat has been heightened by the emergence and propagation of multi drug-resistant (MDR) and extensively drug-resistant (XDR) strains of Mtb that are resistant to current treatment regimens. The End-TB strategy, launched by the World Health Organization (WHO), aims to reduce TB-related deaths by 90%. This program encourages universal access to drug susceptibility testing, which is not widely available owing to the lack of laboratory capacity or resources in certain under-resourced areas. Clinical assays are further complicated by the slow growth of Mtb, resulting in the long turn-around time of tests which severely limits their application in guiding a patient's treatment regimen. This review provides a comprehensive overview of current TB treatments, mechanisms of resistance to anti-tubercular drugs and their diagnosis and the current pipeline of drugs targeting drug-resistant TB (DR-TB) with particular attention paid to ways in which drug-resistance is combated.