Structural Dynamics Behind Clinical Mutants of PncA-Asp12Ala, Pro54Leu, and His57Pro of Mycobacterium tuberculosis Associated With Pyrazinamide Resistance

Breaking barriers: The potential of nanosystems in antituberculosis therapy

Tuberculosis (TB), caused by Mycobacterium tuberculosis, continues to pose a significant threat to global health. The resilience of TB is amplified by a myriad of physical, biological, and biopharmaceutical barriers that challenge conventional therapeutic approaches. This review navigates the intricate landscape of TB treatment, from the stealth of latent infections and the strength of granuloma formations to the daunting specters of drug resistance and altered gene expression. Amidst these challenges, traditional therapies often fail, contending with inconsistent bioavailability, prolonged treatment regimens, and socioeconomic burdens. Nanoscale Drug Delivery Systems (NDDSs) emerge as a promising beacon, ready to overcome these barriers, offering better drug targeting and improved patient adherence. Through a critical approach, we evaluate a spectrum of nanosystems and their efficacy against MTB both in vitro and in vivo. This review advocates for the intensification of research in NDDSs, heralding their potential to reshape the contours of global TB treatment strategies.

In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene

Single nucleotide polymorphisms (SNPs) are one of the most common determinants and potential biomarkers of human disease pathogenesis. SNPs could alter amino acid residues, leading to the loss of structural and functional integrity of the encoded protein. In humans, members of the minichromosome maintenance (MCM) family play a vital role in cell proliferation and have a significant impact on tumorigenesis. Among the MCM members, the molecular mechanism of how missense SNPs of minichromosome maintenance complex component 6 (MCM6) contribute to DNA replication and tumor pathogenesis is underexplored and needs to be elucidated. Hence, a series of sequence and structure-based computational tools were utilized to determine how mutations affect the corresponding MCM6 protein. From the dbSNP database, among 15,009 SNPs in the MCM6 gene, 642 missense SNPs (4.28%), 291 synonymous SNPs (1.94%), and 12,500 intron SNPs (83.28%) were observed. Out of the 642 missense SNPs, 33 were found to be deleterious during the SIFT analysis. Among these, 11 missense SNPs (I123S, R207C, R222C, L449F, V456M, D463G, H556Y, R602H, R633W, R658C, and P815T) were found as deleterious, probably damaging, affective and disease-associated. Then, I123S, R207C, R222C, V456M, D463G, R602H, R633W, and R658C missense SNPs were found to be highly harmful. Six missense SNPs (I123S, R207C, V456M, D463G, R602H, and R633W) had the potential to destabilize the corresponding protein as predicted by DynaMut2. Interestingly, five high-risk mutations (I123S, V456M, D463G, R602H, and R633W) were distributed in two domains (PF00493 and PF14551). During molecular dynamics simulations analysis, consistent fluctuation in RMSD and RMSF values, high Rg and hydrogen bonds in mutant proteins compared to wild-type revealed that these mutations might alter the protein structure and stability of the corresponding protein. Hence, the results from the analyses guide the exploration of the mechanism by which these missense SNPs of the MCM6 gene alter the structural integrity and functional properties of the protein, which could guide the identification of ways to minimize the harmful effects of these mutations in humans.

Screening Marine Microbial Metabolites as Promising Inhibitors of Borrelia garinii: A Structural Docking Approach towards Developing Novel Lyme Disease Treatment

Lyme disease caused by the Borrelia species is a growing health concern in many parts of the world. Current treatments for the disease may have side effects, and there is also a need for new therapies that can selectively target the bacteria. Pathogens responsible for Lyme disease include B. burgdorferi, B. afzelii, and B. garinii. In this study, we employed structural docking-based screening to identify potential lead-like inhibitors against the bacterium. We first identified the core essential genome fraction of the bacterium, using 37 strains. Later, we screened a library of lead-like marine microbial metabolites (n = 4730) against the arginine deiminase (ADI) protein of Borrelia garinii. This protein plays a crucial role in the survival of the bacteria, and inhibiting it can kill the bacterium. The prioritized lead compounds demonstrating favorable binding energies and interactions with the active site of ADI were then evaluated for their drug-like and pharmacokinetic parameters to assess their suitability for development as drugs. Results from molecular dynamics simulation (100 ns) and other scoring parameters suggest that the compound CMNPD18759 (common name: aureobasidin; IUPAC name: 2-[(4R,6R)-4,6-dihydroxydecanoyl]oxypropan-2-yl (3S,5R)-3,5-dihydroxydecanoate) holds promise as a potential drug candidate for the treatment of Lyme disease, caused by B. garinii. However, further experimental studies are needed to validate the efficacy and safety of this compound in vivo.

Exploring of pyrazinamidase recombinant activity from PZA-sensitive and resistant Mycobacterium tuberculosis expressed in Escherichia coli BL21 (DE3)

The mutations of pncA gene encoding pyrazinamidase/PZase in Mycobacterium tuberculosis are often associated with pyrazinamide/PZA resistance. The H and R1 isolates showed significant phenotypic differences to PZA. The H isolate was PZA sensitive, but R1 was PZA resistant up to 100 ug/ml. The paper reports the pncA profile for both isolates and the activity of their protein expressed in Escherichia coli BL21(DE3). The 0.6 kb of each pncA genes have been subcloned successfully into the 5.4 kb pET30a vector and formed the pET30a-pncA recombinant with a size of 6.0 kb. The pncAR1 profile exhibited base mutations, but not for pncAH against to pncA from the PZA-sensitive M. tuberculosis H37RV published in Genbank ID: 888260. Three mutations were found in pncAR1, ie T41C, G419A, and A535G that subsequently changed amino acids of Cys14Arg, Arg140His and Ser179Gly in its protein level. The mutant PZase R1 that expressed as a 21 kDa protein in E. coli Bl21(DE3) lost 32% of its performance in activating PZA drug to pyrazinoic acid/POA compared to the wild-type PZase H. The mutation in the pncAR1 gene that followed by the decreasing of its PZase activity underlies the emergence of pyrazinamide resistance in the clinical isolate. Structural studies for the R1 mutant PZase protein should be further developed to reveal more precise drug resistance mechanisms and design more effective TB drugs.

Oxazoline/amide derivatives against M. tuberculosis: experimental, biological and computational investigations

Tuberculosis (TB) is a treatable contagious disease that continuously kills approximately 2 million people yearly. Different oxazoline/amide derivatives were synthesized, and their anti-tuberculosis activity was performed against different strains of Mtb. This study designed the anti-Mtb compounds based on amide and oxazoline, two different structural moieties. The compounds were further synthesized and characterized by spectral techniques. Their anti-Tb activity was evaluated against strain (M. tuberculosis: H37Rv). Selectivity and binding affinity of all synthesized compounds (2a-2e, 3a-3e) against PanK in Mtb were investigated through molecular docking. Molecular dynamics simulation studies for the promising compounds 2d and 3e were performed for 100 ns. The stability of these complexes was assessed by calculating the root mean square deviation, solvent-accessible surface area, and gyration radius relative to their parent structures. Additionally, free energy of binding calculations were performed. Among all synthesized compounds, 2d and 3e had comparable antitubercular activity against standard drug, validated by their computational and biological study.

Global status of phenotypic pyrazinamide resistance in Mycobacterium tuberculosis clinical isolates: an updated systematic review and meta-analysis

Pyrazinamide (PZA) is an essential first-line tuberculosis drug for its unique mechanism of action active against multidrug-resistant-TB (MDR-TB). Thus, the aim of updated meta-analysis was to estimate the PZA weighted pooled resistance (WPR) rate in M. tuberculosis isolates based on publication date and WHO regions. We systematically searched the related reports in PubMed, Scopus, and Embase (from January 2015 to July 2022). Statistical analyses were performed using STATA software. The 115 final reports in the analysis investigated phenotypic PZA resistance data. The WPR of PZA was 57% (95% CI 48-65%) in MDR-TB cases. According to the WHO regions, the higher WPRs of PZA were reported in the Western Pacific (32%; 95% CI 18-46%), South East Asian region (37%; 95% CI 31-43%), and the Eastern Mediterranean (78%; 95% CI 54-95%) among any-TB patients, high risk of MDR-TB patients, and MDR-TB patients, respectively. A negligible increase in the rate of PZA resistance were showed in MDR-TB cases (55% to 58%). The rate of PZA resistance has been rising in recent years among MDR-TB cases, underlines the essential for both standard and novel drug regimens development.

Supervised screening of Tecovirimat-like compounds as potential inhibitors for the monkeypox virus E8L protein

Monkeypox virus (MPXV) is a budding public health threat worldwide, and there lacks a personalized drug availability to treat MPXV infections. Tecovirimat, an antiviral drug against pox viruses, is recently confirmed to be effective against the MPXV in vitro using nanomolar concentrations. Therefore, the current study considers Tecovirimat as a reference compound for a machine learning-based guided screening to scan bioactive compounds from the DrugBank with similar chemical features or moieties as the Tecovirimat to inhibit the MPXV E8L surface binding protein. We used AlphaFold2 to model the E8L's 3D structure, followed by the conformational activity investigation of shortlisted drugs through computational structural biology approaches, including molecular docking and molecular dynamics simulations. As a result, we have shortlisted five drugs named ABX-1431, Alflutinib, Avacopan, Caspitant, and Darapalib that effectively engage the MPXV surface binding protein. Furthermore, the affinity of the proposed drugs is relatively higher than the Tecovirimat by having higher docking scores, establishing more hydrogen and hydrophobic bonds, engaging key residues in the target's structure, and exhibiting stable molecular dynamics.Communicated by Ramaswamy H. Sarma.

Combination of furosemide, gold, and dopamine as a potential therapy for breast cancer

Breast cancer is one of the leading causes of death in women worldwide. Initially, it develops in the epithelium of the ducts or lobules of the breast glandular tissues with limited growth and the potential to metastasize. It is a highly heterogeneous malignancy; however, the common molecular mechanisms could help identify new targeted drugs for treating its subtypes. This study uses computational drug repositioning approaches to explore fresh drug candidates for breast cancer treatment. We also implemented reversal gene expression and gene expression-based signatures to explore novel drug candidates computationally. The drug activity profiles and related gene expression changes were acquired from the DrugBank, PubChem, and LINCS databases, and then in silico drug screening, molecular dynamics (MD) simulation, replica exchange MD simulations, and simulated annealing molecular dynamics (SAMD) simulations were conducted to discover and verify the valid drug candidates. We have found that compounds like furosemide, gold, and dopamine showed significant outcomes. Furthermore, the expression of genes related to breast cancer was observed to be reversed by these shortlisted drugs. Therefore, we postulate that combining furosemide, gold, and dopamine would be a potential combination therapy measurement for breast cancer patients.

Mutational Impacts on the N and C Terminal Domains of the MUC5B Protein: A Transcriptomics and Structural Biology Study

Cholangiocarcinoma (CCA) involves various epithelial tumors historically linked with poor prognosis because of its aggressive sickness course, delayed diagnosis, and limited efficacy of typical chemotherapy in its advanced stages. In-depth molecular profiling has exposed a varied scenery of genomic alterations as CCA's oncogenic drivers. Previous studies have mainly focused on commonly occurring TP53 and KRAS alterations, but there is limited research conducted to explore other vital genes involved in CCA. We retrieved data from The Cancer Genome Atlas (TCGA) to hunt for additional CCA targets and plotted a mutational landscape, identifying key genes and their frequently expressed variants. Next, we performed a survival analysis for all of the top genes to shortlist the ones with better significance. Among those genes, we observed that MUC5B has the most significant p-value of 0.0061. Finally, we chose two missense mutations at different positions in the vicinity of MUC5B N and C terminal domains. These mutations were further subjected to molecular dynamics (MD) simulation, which revealed noticeable impacts on the protein structure. Our study not only reveals one of the highly mutated genes with enhanced significance in CCA but also gives insights into the influence of its variants. We believe these findings are a good asset for understanding CCA from genomics and structural biology perspectives.

Discovering potent inhibitors against the Mpro of the SARS-CoV-2. A medicinal chemistry approach

The global pandemic caused by a single-stranded RNA (ssRNA) virus known as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is still at its peak, with new cases being reported daily. Although the vaccines have been administered on a massive scale, the frequent mutations in the viral gene and resilience of the future strains could be more problematic. Therefore, new compounds are always needed to be available for therapeutic approaches. We carried out the present study to discover potential drug compounds against the SARS-CoV-2 main protease (Mpro). A total of 16,000 drug-like small molecules from the ChemBridge database were virtually screened to obtain the top hits. As a result, 1032 hits were selected based on their docking scores. Next, these structures were prepared for molecular docking, and each small molecule was docked into the active site of the Mpro. Only compounds with solid interactions with the active site residues and the highest docking score were subjected to molecular dynamics (MD) simulation. The post-simulation analyses were carried out using the in-built GROMACS tools to gauge the stability, flexibility, and compactness. Principal component analysis (PCA) and hydrogen bonding were also calculated to observe trends and affinity of the drugs towards the target. Among the five top compounds, C1, C3, and C6 revealed strong interaction with the target's active site and remained highly stable throughout the simulation. We believe the predicted compounds in this study could be potential inhibitors in the natural system and can be utilized in designing therapeutic strategies against the SARS-CoV-2.

Design of a Multi-Epitopes Vaccine against Hantaviruses: An Immunoinformatics and Molecular Modelling Approach

Hantaviruses are negative-sense, enveloped, single-stranded RNA viruses of the family Hantaviridae. In recent years, rodent-borne hantaviruses have emerged as novel zoonotic viruses posing a substantial health issue and socioeconomic burden. In the current research, a reverse vaccinology approach was applied to design a multi-epitope-based vaccine against hantavirus. A set of 340 experimentally reported epitopes were retrieved from Virus Pathogen Database and Analysis Resource (ViPR) and subjected to different analyses such as antigenicity, allergenicity, solubility, IFN gamma, toxicity, and virulent checks. Finally, 10 epitopes which cleared all the filters used were linked with each other through specific GPGPG linkers to construct a multi-antigenic epitope vaccine. The designed vaccine was then joined to three different adjuvants-TLR4-agonist adjuvant, β-defensin, and 50S ribosomal protein L7/L12-using an EAAAK linker to boost up immune-stimulating responses and check the potency of vaccine with each adjuvant. The designed vaccine structures were modelled and subjected to error refinement and disulphide engineering to enhance their stability. To understand the vaccine binding affinity with immune cell receptors, molecular docking was performed between the designed vaccines and TLR4; the docked complex with a low level of global energy was then subjected to molecular dynamics simulations to validate the docking results and dynamic behaviour. The docking binding energy of vaccines with TLR4 is -29.63 kcal/mol (TLR4-agonist), -3.41 kcal/mol (β-defensin), and -11.03 kcal/mol (50S ribosomal protein L7/L12). The systems dynamics revealed all three systems to be highly stable with a root-mean-square deviation (RMSD) value within 3 Å. To test docking predictions and determine dominant interaction energies, binding free energies of vaccine(s)-TLR4 complexes were calculated. The net binding energy of the systems was as follows: TLR4-agonist vaccine with TLR4 (MM-GBSA, -1628.47 kcal/mol and MM-PBSA, -37.75 kcal/mol); 50S ribosomal protein L7/L12 vaccine with TLR4 complex (MM-GBSA, -194.62 kcal/mol and MM-PBSA, -150.67 kcal/mol); β-defensin vaccine with TLR4 complex (MM-GBSA, -9.80 kcal/mol and MM-PBSA, -42.34 kcal/mol). Finally, these findings may aid experimental vaccinologists in developing a very potent hantavirus vaccine.

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.

Structural and Genomic Insights Into Pyrazinamide Resistance in Mycobacterium tuberculosis Underlie Differences Between Ancient and Modern Lineages

Resistance to drugs used to treat tuberculosis disease (TB) continues to remain a public health burden, with missense point mutations in the underlying Mycobacterium tuberculosis bacteria described for nearly all anti-TB drugs. The post-genomics era along with advances in computational and structural biology provide opportunities to understand the interrelationships between the genetic basis and the structural consequences of M. tuberculosis mutations linked to drug resistance. Pyrazinamide (PZA) is a crucial first line antibiotic currently used in TB treatment regimens. The mutational promiscuity exhibited by the pncA gene (target for PZA) necessitates computational approaches to investigate the genetic and structural basis for PZA resistance development. We analysed 424 missense point mutations linked to PZA resistance derived from ∼35K M. tuberculosis clinical isolates sourced globally, which comprised the four main M. tuberculosis lineages (Lineage 1-4). Mutations were annotated to reflect their association with PZA resistance. Genomic measures (minor allele frequency and odds ratio), structural features (surface area, residue depth and hydrophobicity) and biophysical effects (change in stability and ligand affinity) of point mutations on pncA protein stability and ligand affinity were assessed. Missense point mutations within pncA were distributed throughout the gene, with the majority (>80%) of mutations with a destabilising effect on protomer stability and on ligand affinity. Active site residues involved in PZA binding were associated with multiple point mutations highlighting mutational diversity due to selection pressures at these functionally important sites. There were weak associations between genomic measures and biophysical effect of mutations. However, mutations associated with PZA resistance showed statistically significant differences between structural features (surface area and residue depth), but not hydrophobicity score for mutational sites. Most interestingly M. tuberculosis lineage 1 (ancient lineage) exhibited a distinct protein stability profile for mutations associated with PZA resistance, compared to modern lineages.

Bringing Structural Implications and Deep Learning-Based Drug Identification for KRAS Mutants

Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten Rat Sarcoma (KRAS) harboring codons 13 and 61 mutations. The objective for this study is to search for clinically important codon 61 mutations and analyze how they affect the protein structural dynamics. Additionally, a deep-learning approach is used to carry out a similarity search for potential compounds that might have a comparatively better affinity. Public databases like The Cancer Genome Atlas and Genomic Data Commons were accessed for obtaining the data regarding mutations that are associated with colon cancer. Multiple analysis such as genomic alteration landscape, survival analysis, and systems biology-based kinetic simulations were carried out to predict dynamic changes for the selected mutations. Additionally, a molecular dynamics simulation of 100 ns for all the seven shortlisted codon 61 mutations have been conducted, which revealed noticeable deviations. Finally, the deep learning-based predicted compounds were docked with the KRAS 3D conformer, showing better affinity and good docking scores as compared to the already existing drugs. Taking together the outcomes of systems biology and molecular dynamics, it is observed that the reported mutations in the SII region are highly detrimental as they have an immense impact on the protein sensitive sites' native conformation and overall stability. The drugs reported in this study show increased performance and are encouraged to be used for further evaluation regarding the situation that ascends as a result of KRAS mutations.

Characterization of pncA Mutations and Prediction of PZA Resistance in Mycobacterium tuberculosis Clinical Isolates From Chongqing, China

Pyrazinamide (PZA) is widely used to treat drug-sensitive or multidrug resistance tuberculosis. However, conventional PZA susceptibility tests of clinical isolates are rather difficult because of the requirement of acid pH. Since resistance to pyrazinamide is primary mediated by mutation of pncA, an alternative way of PZA susceptibility test is to analyze the pyrazinamidase activities of Mycobacterium tuberculosis clinical isolates. Therefore, a database containing the full spectrum of pncA mutations along with pyrazinamidase activities will be beneficial. To characterize mutations of pncA in M. tuberculosis from Chongqing, China, the pncA gene was sequenced and analyzed in 465 clinical isolates. A total of 124 types of mutations were identified in 424 drug-resistant isolates, while no mutation was identified in the 31 pan-susceptible isolates. Ninety-four of the 124 mutations had previously been reported, and 30 new mutations were identified. Based on reported literatures, 294 isolates could be predicted resistant to pyrazinamide. Furthermore, pyrazinamidase activities of the 30 new mutations were tested using the Escherichia coli pncA gene knockout strain. The results showed that 24 of these new mutations (28 isolates) led to loss of pyrazinamidase activity and six (8 isolates) of them did not. Taken together, 322 isolates with pncA mutations could be predicted to be PZA resistant among the 424 drug-resistant isolates tested. Analysis of pncA mutations and their effects on pyrazinamidase activity will not only enrich our knowledge of comprehensive pncA mutations related with PZA resistance but also facilitate rapid molecular diagnosis of pyrazinamide resistance in M. tuberculosis.

Novel Treatments against Mycobacterium tuberculosis Based on Drug Repurposing

Tuberculosis is the leading cause of death, worldwide, due to a bacterial pathogen. This respiratory disease is caused by the intracellular pathogen Mycobacterium tuberculosis and produces 1.5 million deaths every year. The incidence of tuberculosis has decreased during the last decade, but the emergence of MultiDrug-Resistant (MDR-TB) and Extensively Drug-Resistant (XDR-TB) strains of M. tuberculosis is generating a new health alarm. Therefore, the development of novel therapies based on repurposed drugs against MDR-TB and XDR-TB have recently gathered significant interest. Recent evidence, focused on the role of host molecular factors on M. tuberculosis intracellular survival, allowed the identification of new host-directed therapies. Interestingly, the mechanism of action of many of these therapies is linked to the activation of autophagy (e.g., nitazoxanide or imatinib) and other well-known molecular pathways such as apoptosis (e.g., cisplatin and calycopterin). Here, we review the latest developments on the identification of novel antimicrobials against tuberculosis (including avermectins, eltrombopag, or fluvastatin), new host-targeting therapies (e.g., corticoids, fosfamatinib or carfilzomib) and the host molecular factors required for a mycobacterial infection that could be promising targets for future drug development.

Integrated Computational Approaches and Tools forAllosteric Drug Discovery

Understanding molecular mechanisms underlying the complexity of allosteric regulationin proteins has attracted considerable attention in drug discovery due to the benefits and versatilityof allosteric modulators in providing desirable selectivity against protein targets while minimizingtoxicity and other side effects. The proliferation of novel computational approaches for predictingligand-protein interactions and binding using dynamic and network-centric perspectives has ledto new insights into allosteric mechanisms and facilitated computer-based discovery of allostericdrugs. Although no absolute method of experimental and in silico allosteric drug/site discoveryexists, current methods are still being improved. As such, the critical analysis and integration ofestablished approaches into robust, reproducible, and customizable computational pipelines withexperimental feedback could make allosteric drug discovery more efficient and reliable. In this article,we review computational approaches for allosteric drug discovery and discuss how these tools can beutilized to develop consensus workflows for in silico identification of allosteric sites and modulatorswith some applications to pathogen resistance and precision medicine. The emerging realization thatallosteric modulators can exploit distinct regulatory mechanisms and can provide access to targetedmodulation of protein activities could open opportunities for probing biological processes and insilico design of drug combinations with improved therapeutic indices and a broad range of activities.