Inhibitors of pantothenate synthetase of Mycobacterium tuberculosis - a medicinal chemist perspective

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.

Expanding FTMap for Fragment-Based Identification of Pharmacophore Regions in Ligand Binding Sites

The knowledge of ligand binding hot spots and of the important interactions within such hot spots is crucial for the design of lead compounds in the early stages of structure-based drug discovery. The computational solvent mapping server FTMap can reliably identify binding hot spots as consensus clusters, free energy minima that bind a variety of organic probe molecules. However, in its current implementation, FTMap provides limited information on regions within the hot spots that tend to interact with specific pharmacophoric features of potential ligands. E-FTMap is a new server that expands on the original FTMap protocol. E-FTMap uses 119 organic probes, rather than the 16 in the original FTMap, to exhaustively map binding sites, and identifies pharmacophore features as atomic consensus sites where similar chemical groups bind. We validate E-FTMap against a set of 109 experimentally derived structures of fragment-lead pairs, finding that highly ranked pharmacophore features overlap with the corresponding atoms in both fragments and lead compounds. Additionally, comparisons of mapping results to ensembles of bound ligands reveal that pharmacophores generated with E-FTMap tend to sample highly conserved protein-ligand interactions. E-FTMap is available as a web server at https://eftmap.bu.edu.

Mycobacterium tuberculosis: Pathogenesis and therapeutic targets

Tuberculosis (TB) remains a significant public health concern in the 21st century, especially due to drug resistance, coinfection with diseases like immunodeficiency syndrome (AIDS) and coronavirus disease 2019, and the lengthy and costly treatment protocols. In this review, we summarize the pathogenesis of TB infection, therapeutic targets, and corresponding modulators, including first-line medications, current clinical trial drugs and molecules in preclinical assessment. Understanding the mechanisms of Mycobacterium tuberculosis (Mtb) infection and important biological targets can lead to innovative treatments. While most antitubercular agents target pathogen-related processes, host-directed therapy (HDT) modalities addressing immune defense, survival mechanisms, and immunopathology also hold promise. Mtb's adaptation to the human host involves manipulating host cellular mechanisms, and HDT aims to disrupt this manipulation to enhance treatment effectiveness. Our review provides valuable insights for future anti-TB drug development efforts.

Lead identification against Mycobacterium tuberculosis using highly enriched active molecules against pantothenate synthetase

The Pantothenate synthetase (PS) from the Mycobacterium tuberculosis (Mtb) holds a crucial role in the survival and robust proliferation of bacteria through its catalysis of coenzyme A and acyl carrier protein synthesis. The present study undertook the PS drug target in complex with a co-crystallized ligand and subjected it to docking and virtual screening approaches. The experimental design encompassed three discrete datasets: an active dataset featuring 136 compounds, an inactive dataset comprising 56 compounds, and a decoys dataset curated from the zinc library, comprising an extensive compilation of approximately 53,000 compounds. The compounds' binding energies were observed to be in the range of -5 to ∼-14 kcal/mol. Additionally, binding energy results were further refined through Enrichment Factor analysis (EF). EF is a new statistical approach which uses the scores obtained from docking-based virtual screening and predicts the precision of the scoring function. Remarkably, the Enrichment Factor (EF) analysis produced exceptionally favorable outcomes, attaining an EF of approximately 49% within the uppermost 1% fraction of the compound distribution. Finally, a total of eight compounds, evenly distributed between the active dataset and the decoys dataset, emerged as potent inhibitors of the Pantothenate synthetase (PS) enzyme. The analysis of inhibition constants and binding energy revealed a notable correlation, with an r-squared value (r2) of 0.912 between the two parameters. Furthermore, the shortlisted compounds were subjected to 100 ns MD simulation to determine their stability and dynamics behavior. The decoy compounds that have been identified, exhibiting properties comparable to the active compounds, are postulated as potential candidates for targeting the Pantothenate synthetase (PS) enzyme to treat Mtb infection. Nevertheless, in the pursuit of a comprehensive investigation, it is advisable to undertake additional experimental validation as a component of the subsequent study.Communicated by Ramaswamy H. Sarma.

Identification of the Seaweed Metabolites as Potential Anti-tubercular Agents Against Human Pantothenate synthetase: An In Silico Approach

Tuberculosis is the disease which is caused due to the contagion of Mycobacterium tuberculosis. The multidrug resistance Mycobacterium tuberculosis is the main hassle in the treatment of this worldwide health threats. Pantothenate synthase is a legitimate goal for rational drug designing against Mycobacterium tuberculosis. The enzyme is most active in the presence of magnesium or manganese. Marine algal cell wall is rich in sulfated polysaccharides such as fucoidans (brown algae), κ-carrageenans (red algae), and ulvan (green algae) with various favorable biological activities such as anticoagulant, antiviral, antioxidative, anticancer, and immunomodulating activities. In this study, we have modeled binding modes of selected known anti-tubercular compounds and different solvent extract against pantothenate synthase using advanced docking program AutoDock 4.2 tool. In our current study, in silico experiments were carried out to determine if fucoidan, κ-carrageenan, and ulvan sulfated polysaccharides could be a potential target against PANc (pantothenate synthetase), with the goal of identifying potential inhibitors as anti-TB leads targeting PANc for further wet lab validation. Two bioactive compounds were docked to the Mtb pantothenate synthetase protein binding site, with docking scores ranging from - 5.57 to - 2.73. κ-carrageenan had the best pose and docking score, with a Ligand fit score of - 5.815. Ulvan did not dock with the protein. The molecular dynamics simulations were conducted with substrate and ligand bounded fucoidan and κ-carrageenan for 150 ns and the protein Mtb pantothenate synthetase showed a stable conformation in the simulation, with tight amino acid contributions binding to the ligand molecule. RMSD characterizes the conformation and stability of protein ligand complexes, with higher fluctuations indicating low stability and minimal low-level fluctuations indicating equilibration and stability. The graph for RMSF shows significant peaks due to fluctuations in active site regions and other peaks indicating the adaptation of the ligand molecule to the protein binding pocket. From the molecular dynamics study, it is clear that the compounds are having good binding affinity in the active site. The root mean square deviation, root mean square fluctuations, and radius of gyration are supportive evidences which helped us to conclude that the compounds κ-carrageenan and fucoidan are suitable lead molecules for inhibiting pantothenate synthetase. Based on these evidences, the natural compounds from seaweeds can be tested clinically either alone or in combinations against the protein, which could facilitate the designing or the synthesis of new lead molecules as drugs against the tuberculosis.

In Silico Subtractive Proteomics and Molecular Docking Approaches for the Identification of Novel Inhibitors against Streptococcus pneumoniae Strain D39

Streptococcus pneumoniae is a notorious Gram-positive pathogen present asymptomatically in the nasophayrnx of humans. According to the World Health Organization (W.H.O), pneumococcus causes approximately one million deaths yearly. Antibiotic resistance in S. pneumoniae is raising considerable concern around the world. There is an immediate need to address the major issues that have arisen as a result of persistent infections caused by S. pneumoniae. In the present study, subtractive proteomics was used in which the entire proteome of the pathogen consisting of 1947 proteins is effectively decreased to a finite number of possible targets. Various kinds of bioinformatics tools and software were applied for the discovery of novel inhibitors. The CD-HIT analysis revealed 1887 non-redundant sequences from the entire proteome. These non-redundant proteins were submitted to the BLASTp against the human proteome and 1423 proteins were screened as non-homologous. Further, databases of essential genes (DEGG) and J browser identified almost 171 essential proteins. Moreover, non-homologous, essential proteins were subjected in KEGG Pathway Database which shortlisted six unique proteins. In addition, the subcellular localization of these unique proteins was checked and cytoplasmic proteins were chosen for the druggability analysis, which resulted in three proteins, namely DNA binding response regulator (SPD_1085), UDP-N-acetylmuramate-L-alanine Ligase (SPD_1349) and RNA polymerase sigma factor (SPD_0958), which can act as a promising potent drug candidate to limit the toxicity caused by S. pneumoniae. The 3D structures of these proteins were predicted by Swiss Model, utilizing the homology modeling approach. Later, molecular docking by PyRx software 0.8 version was used to screen a library of phytochemicals retrieved from PubChem and ZINC databases and already approved drugs from DrugBank database against novel druggable targets to check their binding affinity with receptor proteins. The top two molecules from each receptor protein were selected based on the binding affinity, RMSD value, and the highest conformation. Finally, the absorption, distribution, metabolism, excretion, and toxicity (ADMET) analyses were carried out by utilizing the SWISS ADME and Protox tools. This research supported the discovery of cost-effective drugs against S. pneumoniae. However, more in vivo/in vitro research should be conducted on these targets to investigate their pharmacological efficacy and their function as efficient inhibitors.

Comparative Metabolic Pathways Analysis and Subtractive Genomics Profiling to Prioritize Potential Drug Targets Against Streptococcus pneumoniae

Streptococcus pneumoniae is a notorious pathogen that affects ∼450 million people worldwide and causes up to four million deaths per annum. Despite availability of antibiotics (i.e., penicillin, doxycycline, or clarithromycin) and conjugate vaccines (e.g., PCVs), it is still challenging to treat because of its drug resistance ability. The rise of antibiotic resistance in S. pneumoniae is a major source of concern across the world. Computational subtractive genomics is one of the most applied techniques in which the whole proteome of the bacterial pathogen is gradually reduced to a limited number of potential therapeutic targets. Whole-genome sequencing has greatly reduced the time required and provides more opportunities for drug target identification. The goal of this work is to evaluate and analyze metabolic pathways in serotype 14 of S. pneumonia to identify potential drug targets. In the present study, 47 potent drug targets were identified against S. pneumonia by employing the computational subtractive genomics approach. Among these, two proteins are prioritized (i.e., 4-oxalocrotonate tautomerase and Sensor histidine kinase uniquely present in S. pneumonia) as novel drug targets and selected for further structure-based studies. The identified proteins may provide a platform for the discovery of a lead drug candidate that may be capable of inhibiting these proteins and, therefore, could be helpful in minimizing the associated risk related to the drug-resistant S. pneumoniae. Finally, these enzymatic proteins could be of prime interest against S. pneumoniae to design rational targeted therapy.

Design, synthesis and biological evaluation of benzo-[d]-imidazo-[2,1-b]-thiazole and imidazo-[2,1-b]-thiazole carboxamide triazole derivatives as antimycobacterial agents

In the search for new anti-mycobacterial agents, we revealed the importance of imidazo-[2,1-b]-thiazole and benzo-[d]-imidazo-[2,1-b]-thiazole carboxamide derivatives. We designed, in silico ADMET predicted and synthesized four series of novel imidazo-[2,1-b]-thiazole and benzo-[d]-imidazo-[2,1-b]-thiazole carboxamide analogues in combination with piperazine and various 1,2,3 triazoles. All the synthesized derivatives were characterized by ¹H NMR, ¹³C NMR, HPLC and MS spectral analysis and evaluated for in vitro antitubercular activity. The most active benzo-[d]-imidazo-[2,1-b]-thiazole derivative IT10, carrying a 4-nitro phenyl moiety, displayed IC₉₀ of 7.05 μM and IC₅₀ of 2.32 μM against Mycobacterium tuberculosis (Mtb) H37Ra, while no acute cellular toxicity was observed (>128 μM) towards the MRC-5 lung fibroblast cell line. Another benzo-[d]-imidazo-[2,1-b]-thiazole compound, IT06, which possesses a 2,4-dichloro phenyl moiety, also showed significant activity with IC₅₀ 2.03 μM and IC₉₀ 15.22 μM against the tested strain of Mtb. Furthermore, the selected hits showed no activity towards a panel of non-tuberculous mycobacteria (NTM), thus suggesting a selective inhibition of Mtb by the tested imidazo-[2,1-b]-thiazole derivatives over the selected panel of NTM. Molecular docking and dynamics studies were also carried out for the most active compounds IT06 and IT10 in order to understand the putative binding pattern, as well as stability of the protein–ligand complex, against the selected target Pantothenate synthetase of Mtb.

In the search for new anti-mycobacterial agents, we revealed the importance of imidazo-[2,1-b]-thiazole and benzo-[d]-imidazo-[2,1-b]-thiazole carboxamide derivatives.

Identification of a Novel Therapeutic Target against XDR Salmonella Typhi H58 Using Genomics Driven Approach Followed Up by Natural Products Virtual Screening

Typhoid fever is caused by a pathogenic, rod-shaped, flagellated, and Gram-negative bacterium known as Salmonella Typhi. It features a polysaccharide capsule that acts as a virulence factor and deceives the host immune system by protecting phagocytosis. Typhoid fever remains a major health concern in low and middle-income countries, with an estimated death rate of ~200,000 per annum. However, the situation is exacerbated by the emergence of the extensively drug-resistant (XDR) strain designated as H58 of S. Typhi. The emergence of the XDR strain is alarming, and it poses serious threats to public health due to the failure of the current therapeutic regimen. A relatively newer computational method called subtractive genomics analyses has been widely applied to discover novel and new drug targets against pathogens, particularly drug-resistant ones. The method involves the gradual reduction of the complete proteome of the pathogen, leading to few potential and novel drug targets. Thus, in the current study, a subtractive genomics approach was applied against the Salmonella XDR strain to identify potential drug targets. The current study predicted four prioritized proteins (i.e., Colanic acid biosynthesis acetyltransferase wcaB, Shikimate dehydrogenase aroE, multidrug efflux RND transporter permease subunit MdtC, and pantothenate synthetase panC) as potential drug targets. Though few of the prioritized proteins are treated in the literature as the established drug targets against other pathogenic bacteria, these drug targets are identified here for the first time against S. Typhi (i.e., S. Typhi XDR). The current study aimed at drawing attention to new drug targets against S. Typhi that remain largely unexplored. One of the prioritized drug targets, i.e., Colanic acid biosynthesis acetyltransferase, was predicted as a unique, new drug target against S. Typhi XDR. Therefore, the Colanic acid was further explored using structure-based techniques. Additionally, ~1000 natural compounds were docked with Colanic acid biosynthesis acetyltransferase, resulting in the prediction of seven compounds as potential lead candidates against the S. Typhi XDR strain. The ADMET properties and binding energies via the docking program of these seven compounds characterized them as novel drug candidates. They may potentially be used for the development of future drugs in the treatment of Typhoid fever.

New Investigations with Lupane Type A-Ring Azepane Triterpenoids for Antimycobacterial Drug Candidate Design

Twenty lupane type A-ring azepano-triterpenoids were synthesized from betulin and its related derivatives and their antitubercular activity against Mycobacterium tuberculosis, mono-resistant MTB strains, and nontuberculous strains Mycobacterium abscessus and Mycobacterium avium were investigated in the framework of AToMIc (Anti-mycobacterial Target or Mechanism Identification Contract) realized by the Division of Microbiology and Infectious Diseases, NIAID, National Institute of Health. Of all the tested triterpenoids, 17 compounds showed antitubercular activity and 6 compounds were highly active on the H37Rv wild strain (with MIC 0.5 µM for compound 7), out of which 4 derivatives also emerged as highly active compounds on the three mono-resistant MTB strains. Molecular docking corroborated with a machine learning drug-drug similarity algorithm revealed that azepano-triterpenoids have a rifampicin-like antitubercular activity, with compound 7 scoring the highest as a potential M. tuberculosis RNAP potential inhibitor. FIC testing demonstrated an additive effect of compound 7 when combined with rifampin, isoniazid and ethambutol. Most compounds were highly active against M. avium with compound 14 recording the same MIC value as the control rifampicin (0.0625 µM). The antitubercular ex vivo effectiveness of the tested compounds on THP-1 infected macrophages is correlated with their increased cell permeability. The tested triterpenoids also exhibit low cytotoxicity and do not induce antibacterial resistance in MTB strains.

Design and synthesis of novel quinazolinone-pyrazole derivatives as potential α-glucosidase inhibitors: Structure-activity relationship, molecular modeling and kinetic study

In this study, a new series of quinazolinone-pyrazole hybrids were designed, synthesized and screened for their α-glucosidase inhibitory activity. The results of the in vitro screening indicated that all the molecular hybrids exhibited more inhibitory activity (IC₅₀ values ranging from 60.5 ± 0.3 µM-186.6 ± 20 μM) in comparison to standard acarbose (IC₅₀ = 750.0 ± 10.0 µM). Limited structure-activity relationship suggested that the variation in the inhibitory activities of the compounds affected by different substitutions on phenyl rings of diphenyl pyrazole moiety. The enzyme kinetic studies of the most potent compound 9i revealed that it inhibited α-glucosidase in a competitive mode with a Ki of 56 μM. Molecular docking study was performed to predict the putative binding interaction. As expected, all pharmacophoric moieties used in the initial structure design playing a pivotal role in the interaction with the binding site of the enzyme. In addition, by performing molecular dynamic investigation and MM-GBSA calculation, we investigated the difference in structural perturbation and dynamic behavior that is observed over α-glycosidase in complex with the most active compound and acarbose relative to unbound α-glycosidase enzyme.