Discovery of a Novel Inhibitor Structure of Mycobacterium tuberculosis Isocitrate Lyase

The global distribution of the macrolide esterase EstX from the alpha/beta hydrolase superfamily

Macrolide antibiotics, pivotal in clinical therapeutics, are confronting resistance challenges mediated by enzymes like macrolide esterases, which are classified into Ere-type and the less studied Est-type. In this study, we provide the biochemical confirmation of EstX, an Est-type macrolide esterase that initially identified as unknown protein in the 1980s. EstX is capable of hydrolyzing four 16-membered ring macrolides, encompassing both veterinary (tylosin, tidipirosin, and tilmicosin) and human-use (leucomycin A5) antibiotics. It uses typical catalytic triad (Asp233-His261-Ser102) from alpha/beta hydrolase superfamily for ester bond hydrolysis. Further genomic context analysis suggests that the dissemination of estX is likely facilitated by mobile genetic elements such as integrons and transposons. The global distribution study indicates that bacteria harboring the estX gene, predominantly pathogenic species like Escherichia coli, Salmonella enterica, and Klebsiella pneumoniae, are prevalent in 74 countries across 6 continents. Additionally, the emergence timeline of the estX gene suggests its proliferation may be linked to the overuse of macrolide antibiotics. The widespread prevalence and dissemination of Est-type macrolide esterase highlight an urgent need for enhanced monitoring and in-depth research, underlining its significance as an escalating public health issue.

Identification of a Novel Chitinase from Bacillus paralicheniformis: Gene Mining, Sequence Analysis, and Enzymatic Characterization

In this study, a novel strain for degrading chitin was identified as Bacillus paralicheniformis HL37, and the key chitinase CH1 was firstly mined through recombinant expression in Bacillus amyloliquefaciens HZ12. Subsequently, the sequence composition and catalytic mechanism of CH1 protein were analyzed. The molecular docking indicated that the triplet of Asp526, Asp528, and Glu530 was a catalytic active center. The enzymatic properties analysis revealed that the optimal reaction temperature and pH was 65 °C and 6.0, respectively. Especially, the chitinase activity showed no significant change below 55 °C and it could maintain over 60% activity after exposure to 85 °C for 30 min. Moreover, the optimal host strain and signal peptide were obtained to enhance the expression of chitinase CH1 significantly. As far as we know, it was the first time finding the highly efficient chitin-degrading enzymes in B. paralicheniformis, and detailed explanations were provided on the catalytic mechanism and enzymatic properties on CH1.

Exploring optimal drug targets through subtractive proteomics analysis and pangenomic insights for tailored drug design in tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.

In silico drug design strategies for discovering novel tuberculosis therapeutics

INTRODUCTION

Tuberculosis remains a significant concern in global public health due to its intricate biology and propensity for developing antibiotic resistance. Discovering new drugs is a protracted and expensive endeavor, often spanning over a decade and incurring costs in the billions. However, computer-aided drug design (CADD) has surfaced as a nimbler and more cost-effective alternative. CADD tools enable us to decipher the interactions between therapeutic targets and novel drugs, making them invaluable in the quest for new tuberculosis treatments.

AREAS COVERED

In this review, the authors explore recent advancements in tuberculosis drug discovery enabled by in silico tools. The main objectives of this review article are to highlight emerging drug candidates identified through in silico methods and to provide an update on the therapeutic targets associated with Mycobacterium tuberculosis.

EXPERT OPINION

These in silico methods have not only streamlined the drug discovery process but also opened up new horizons for finding novel drug candidates and repositioning existing ones. The continued advancements in these fields hold great promise for more efficient, ethical, and successful drug development in the future.

Identification of potent inhibitors targeting Tribolium castaneum GSTe2 via structure-based screening and molecular dynamics simulation

Red flour beetle, Tribolium castaneum, has a major negative impact during storage of agricultural products and reveals the negative impacts on human health. Insect-specific epsilon glutathione S-transferase (GSTs) which requires reduced glutathione (GSH) as an essential substrate not only develop insecticide resistance but also play important role in insect metamorphosis. Inhibition of the insect metamorphosis and the development of insecticide resistance could play an important role in pest control, so T. castaneum GSTe2 (TcGSTe2) in our previous study could be an important target protein for this purpose. This study aimed to find a potential TcGSTe2 inhibitors through in silico mothods, including molecular modeling, molecular docking, ADMET assay, followed by molecular dynamics (MD) simulation, principal component analysis and MM/PBSA analysis. The results showed that ZINC000169293362 and ZINC000095566957 were selected as potential TcGSTe2 inhibitors with high-binding affinity and without any toxicity from 3618 of GSH-like compounds obtained from ZINC database. MD simulation results revealed that TcGSTe2-ZINC000169293362 had more stability than that of reference GSH. Moreover, TcGSTe2-ZINC000169293362 and TcGSTe2-ZINC000095566957 showed lower binding free energy (-27.53 ± 0.16 kcal/mol and -18.83 ± 0.15 kcal/mol, respectively) compared with TcGSTe2-GSH (-8.90 ± 0.30 kcal/mol). This study could provide new insight into reduction of insecticide resistance and be used to design new inhibitors of insect GSTs.Communicated by Ramaswamy H. Sarma.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

Integrated Bioinformatics-Based Subtractive Genomics Approach to Decipher the Therapeutic Drug Target and Its Possible Intervention against Brucellosis

Brucella suis, one of the causative agents of brucellosis, is Gram-negative intracellular bacteria that may be found all over the globe and it is a significant facultative zoonotic pathogen found in livestock. It may adapt to a phagocytic environment, reproduce, and develop resistance to harmful environments inside host cells, which is a crucial part of the Brucella life cycle making it a worldwide menace. The molecular underpinnings of Brucella pathogenicity have been substantially elucidated due to comprehensive methods such as proteomics. Therefore, we aim to explore the complete Brucella suis proteome to prioritize the novel proteins as drug targets via subtractive proteo-genomics analysis, an effort to conjecture the existence of distinct pathways in the development of brucellosis. Consequently, 38 unique metabolic pathways having 503 proteins were observed while among these 503 proteins, the non-homologs (n = 421), essential (n = 350), drug-like (n = 114), virulence (n = 45), resistance (n = 42), and unique to pathogen proteins were retrieved from Brucella suis. The applied subsequent hierarchical shortlisting resulted in a protein, i.e., isocitrate lyase, that may act as potential drug target, which was finalized after the extensive literature survey. The interacting partners for these shortlisted drug targets were identified through the STRING database. Moreover, structure-based studies were also performed on isocitrate lyase to further analyze its function. For that purpose, ~18,000 ZINC compounds were screened to identify new potent drug candidates against isocitrate lyase for brucellosis. It resulted in the shortlisting of six compounds, i.e., ZINC95543764, ZINC02688148, ZINC20115475, ZINC04232055, ZINC04231816, and ZINC04259566 that potentially inhibit isocitrate lyase. However, the ADMET profiling showed that all compounds fulfill ADMET properties except for ZINC20115475 showing positive Ames activity; whereas, ZINC02688148, ZINC04259566, ZINC04232055, and ZINC04231816 showed hepatoxicity while all compounds were observed to have no skin sensitization. In light of these parameters, we recommend ZINC95543764 compound for further experimental studies. According to the present research, which uses subtractive genomics, proteins that might serve as therapeutic targets and potential lead options for eradicating brucellosis have been narrowed down.