Deciphering Isoniazid Drug Resistance Mechanisms on Dimeric Mycobacterium tuberculosis KatG via Post-molecular Dynamics Analyses Including Combined Dynamic Residue Network Metrics

Evaluation of AAICare®-TB sequence analysis tool for accurate diagnosis of drug-resistant tuberculosis: A comparative study with TB-Profiler and Mykrobe

A rapid and comprehensive drug susceptibility test is essential for eliminating drug resistant tuberculosis. Next generation sequencing (NGS) based susceptibility testing is being explored as a potential substitute for the conventional phenotypic and genotypic testing methods. However, the adoption of NGS based genotypic susceptibility testing depends on the availability of simple, accurate and efficient analysis tools. This preliminary study aimed to evaluate the performance of a Mycobacterium tuberculosis (Mtb) genome analysis pipeline, AAICare®-TB, for susceptibility prediction, in comparison to two widely used gDST prediction tools, TB-Profiler and Mykrobe. This study was performed in a National Reference Laboratory in India on presumptive drug-resistant tuberculosis (DR-TB) isolates. Whole genome sequences of the 120 cultured isolates were obtained through Illumina sequencing on a MiSeq platform. Raw sequences were simultaneously analysed using the three tools. Susceptibility prediction reports thus generated, were compared to estimate the total concordance and discordance. WHO mutation catalogue (1st edition, 2021) was used as the reference standard for categorizing the mutations. In this study, AAICare®-TB was able to predict drug resistance status for First Line (Streptomycin, Isoniazid, Rifampicin, Ethambutol and Pyrazinamide) and Second Line drugs (Fluoroquinolones, Second Line Injectables and Ethionamide) in 93 samples along with lineage and hetero-resistance as per the WHO guidelines.

Plant antibacterials: The challenges and opportunities

Nature possesses an inexhaustible reservoir of agents that could serve as alternatives to combat the growing threat of antimicrobial resistance (AMR). While some of the most effective drugs for treating bacterial infections originate from natural sources, they have predominantly been derived from fungal and bacterial species. However, a substantial body of literature is available on the promising antibacterial properties of plant-derived compounds. In this comprehensive review, we address the major challenges associated with the discovery and development of plant-derived antimicrobial compounds, which have acted as obstacles preventing their clinical use. These challenges encompass limited sourcing, the risk of agent rediscovery, suboptimal drug metabolism, and pharmacokinetics (DMPK) properties, as well as a lack of knowledge regarding molecular targets and mechanisms of action, among other pertinent issues. Our review underscores the significance of these challenges and their implications in the quest for the discovery and development of effective plant-derived antimicrobial agents. Through a critical examination of the current state of research, we give valuable insights that will advance our understanding of these classes of compounds, offering potential solutions to the global crisis of AMR. © 2017 Elsevier Inc. All rights reserved.

Progressive computational approaches to facilitate decryption of allosteric mechanism and drug discovery

Allostery is a ubiquitous biological phenomenon where perturbation at topologically distal areas of a protein serves as a trigger to fine-tune the orthosteric site and thus regulate protein function. The investigation of allosteric regulation greatly enhances our understanding of human diseases and broadens avenue for drug discovery. For decades, owing to the difficulty in allostery characterization through serendipitous experimental screening, researchers have developed several innovative computational approaches, which proves to accelerate the elucidation of allostery. Herein, we review the state-of-the-art advance of computational methodologies for allostery study, with particular emphasis on promising trends emerging over the past two years. We expect this review will outline the latest landscape of allostery study and inspire researchers to further facilitate this field.

Rv1255c, a dormancy-related transcriptional regulator of TetR family in Mycobacterium tuberculosis, enhances isoniazid tolerance in Mycobacterium smegmatis

Mycobacterium tuberculosis is exposed to diverse stresses inside the host during dormancy. Meanwhile, many metabolic and transcriptional regulatory changes occur, resulting in physiological modifications that help M. tuberculosis to adapt to these stresses. The same physiological changes also cause antibiotic tolerance in dormant M. tuberculosis. However, the transcriptional regulatory mechanism of antibiotic tolerance during dormancy remains unclear. Here, we showed that the expression of Rv1255c, an uncharacterised member of the tetracycline repressor family of transcriptional regulators, is upregulated during different stresses and hypoxia-induced dormancy. Antibiotic tolerance and efflux activities of Mycobacterium smegmatis constitutively expressing Rv1255c were analysed, and interestingly, it showed increased isoniazid tolerance and efflux activity. The intrabacterial isoniazid concentrations were found to be low in M. smegmatis expressing Rv1255c. Moreover, orthologs of the M. tuberculosis katG, gene of the enzyme which activates the first-line prodrug isoniazid, are overexpressed in this strain. Structural analysis of isoforms of KatG enzymes in M. smegmatis identified major amino acid substitutions associated with isoniazid resistance. Thus, we showed that Rv1255c helps M. smegmatis tolerate isoniazid by orchestrating drug efflux machinery. In addition, we showed that Rv1255c also causes overexpression of katG isoform in M. smegmatis which has amino acid substitutions as found in isoniazid-resistant katG in M. tuberculosis.

Exploring natural products library to identify potential inhibitors targeting isoniazid-resistant tuberculosis

Mycobacterium tuberculosis (MTB) causing tuberculosis (TB) infection is a leading source of illness and death in developing nations, and the emergence of drug-resistant TB remains a significant global threat and a challenge in treating the disease. Mutations in the inhA and katG genes are connected to the principal molecular mechanism of isoniazid (INH) resistance, and continuous treatment of INH for more than a decade led to the evolution of INH resistant-TB (inhR-TB). Structure-based drug discovery approaches on traditional natural compounds are the contemporary source to identify significant lead molecules. This work focuses on discovering effective small compounds from natural compound libraries and applying pharmacophore-based virtual screening to filter out the molecules. The best-identified hit complexes were used for molecular dynamics simulations (MDS) to observe their stability and compactness. A three-dimensional e-pharmacophore hypothesis and screening generated 62 hits based on phase fitness scores from the pharmacophore-based virtual screening. Molecular docking experiments in Maestro's GLIDE module indicated that ZINC000002383126 and ASN22022 may be potential inhibitors of inhA and katG (native, inhA mutants S94A, Y158A, Y158F and Y158S and D137S, Y229F, S315T, W321F, and R418L mutants of katG). In addition, MDS analysis indicated that the native and mutant docked complexes of inhA and katG had good stability and remained compact in the binding pocket of the targets. In vitro studies can further validate the compounds that can act as INH competitive inhibitors.Communicated by Ramaswamy H. Sarma.

Human Cytochrome P450 1, 2, 3 Families as Pharmacogenes with Emphases on Their Antimalarial and Antituberculosis Drugs and Prevalent African Alleles

Precision medicine gives individuals tailored medical treatment, with the genotype determining the therapeutic strategy, the appropriate dosage, and the likelihood of benefit or toxicity. Cytochrome P450 (CYP) enzyme families 1, 2, and 3 play a pivotal role in eliminating most drugs. Factors that affect CYP function and expression have a major impact on treatment outcomes. Therefore, polymorphisms of these enzymes result in alleles with diverse enzymatic activity and drug metabolism phenotypes. Africa has the highest CYP genetic diversity and also the highest burden of malaria and tuberculosis, and this review presents current general information on CYP enzymes together with variation data concerning antimalarial and antituberculosis drugs, while focusing on the first three CYP families. Afrocentric alleles such as CYP2A6*17, CYP2A6*23, CYP2A6*25, CYP2A6*28, CYP2B6*6, CYP2B6*18, CYP2C8*2, CYP2C9*5, CYP2C9*8, CYP2C9*9, CYP2C19*9, CYP2C19*13, CYP2C19*15, CYP2D6*2, CYP2D6*17, CYP2D6*29, and CYP3A4*15 are implicated in diverse metabolic phenotypes of different antimalarials such as artesunate, mefloquine, quinine, primaquine, and chloroquine. Moreover, CYP3A4, CYP1A1, CYP2C8, CYP2C18, CYP2C19, CYP2J2, and CYP1B1 are implicated in the metabolism of some second-line antituberculosis drugs such as bedaquiline and linezolid. Drug-drug interactions, induction/inhibition, and enzyme polymorphisms that influence the metabolism of antituberculosis, antimalarial, and other drugs, are explored. Moreover, a mapping of Afrocentric missense mutations to CYP structures and a documentation of their known effects provided structural insights, as understanding the mechanism of action of these enzymes and how the different alleles influence enzyme function is invaluable to the advancement of precision medicine.

Investigation of Multi-Subunit Mycobacterium tuberculosis DNA-Directed RNA Polymerase and Its Rifampicin Resistant Mutants

Emerging Mycobacterium tuberculosis (Mtb) resistant strains have continued to limit the efficacies of existing antitubercular therapies. More specifically, mutations in the RNA replicative machinery of Mtb, RNA polymerase (RNAP), have been widely linked to rifampicin (RIF) resistance, which has led to therapeutic failures in many clinical cases. Moreover, elusive details on the underlying mechanisms of RIF-resistance caused by Mtb-RNAP mutations have hampered the development of new and efficient drugs that are able to overcome this challenge. Therefore, in this study we attempt to resolve the molecular and structural events associated with RIF-resistance in nine clinically reported missense Mtb RNAP mutations. Our study, for the first time, investigated the multi-subunit Mtb RNAP complex and findings revealed that the mutations commonly disrupted structural-dynamical attributes that may be essential for the protein's catalytic functions, particularly at the βfork loop 2, β'zinc-binding domain, the β' trigger loop and β'jaw, which in line with previous experimental reports, are essential for RNAP processivity. Complementarily, the mutations considerably perturbed the RIF-BP, which led to alterations in the active orientation of RIF needed to obstruct RNA extension. Consequentially, essential interactions with RIF were lost due to the mutation-induced repositioning with corresponding reductions in the binding affinity of the drug observed in majority of the mutants. We believe these findings will significantly aid future efforts in the discovery of new treatment options with the potential to overcome antitubercular resistance.

Evolutionary progression of collective mutations in Omicron sub-lineages towards efficient RBD-hACE2: Allosteric communications between and within viral and human proteins

The interaction between the Spike (S) protein of SARS-CoV-2 and the human angiotensin converting enzyme 2 (hACE2) is essential for infection, and is a target for neutralizing antibodies. Consequently, selection of mutations in the S protein is expected to be driven by the impact on the interaction with hACE2 and antibody escape. Here, for the first time, we systematically characterized the collective effects of mutations in each of the Omicron sub-lineages (BA.1, BA.2, BA.3 and BA.4) on both the viral S protein receptor binding domain (RBD) and the hACE2 protein using post molecular dynamics studies and dynamic residue network (DRN) analysis. Our analysis suggested that Omicron sub-lineage mutations result in altered physicochemical properties that change conformational flexibility compared to the reference structure, and may contribute to antibody escape. We also observed changes in the hACE2 substrate binding groove in some sub-lineages. Notably, we identified unique allosteric communication paths in the reference protein complex formed by the DRN metrics betweenness centrality and eigencentrality hubs, originating from the RBD core traversing the receptor binding motif of the S protein and the N-terminal domain of the hACE2 to the active site. We showed allosteric changes in residue network paths in both the RBD and hACE2 proteins due to Omicron sub-lineage mutations. Taken together, these data suggest progressive evolution of the Omicron S protein RBD in sub-lineages towards a more efficient interaction with the hACE2 receptor which may account for the increased transmissibility of Omicron variants.