5-<i>tert</i>-Butyl-<i>N</i>-pyrazol-4-yl-4,5,6,7-tetrahydrobenzo[<i>d</i>]isoxazole-3-carboxamide Derivatives as Novel Potent Inhibitors of <i>Mycobacterium tuberculosis</i> Pantothenate Synthetase: Initiating a Quest for New Antitubercular Drugs

Pantothenate synthetase (PS) is one of the potential new antimicrobial targets that may also be useful for the treatment of the nonreplicating persistent forms of Mycobacterium tuberculosis. In this Letter we present a series of 5-tert-butyl-N-pyrazol-4-yl-4,5,6,7-tetrahydrobenzo[d]isoxazole-3-carboxamide derivatives as novel potent Mycobacterium tuberculosis PS inhibitors, their in silico molecular design, synthesis, and inhibitory activity

Structure−Activity Relationships for a Series of Quinoline-Based Compounds Active against Replicating and Nonreplicating <i>Mycobacterium tuberculosis</i>

Tuberculosis (TB) remains as a global pandemic that is aggravated by a lack of health care, the spread of HIV, and the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) strains. New anti-TB drugs are urgently required to shorten the long 6−12 month treatment regimen and to battle drug-resistant Mtb strains. We have identified several potent quinoline-based anti-TB compounds, bearing an isoxazole containing side-chain. The most potent compounds, 7g and 13, exhibited submicromolar activity against the replicating bacteria (R-TB), with minimum inhibitory concentrations (MICs) of 0.77 and 0.95 μM, respectively. In general, these compounds also had micromolar activity against the nonreplicating persistent bacteria (NRP-TB) and did not show toxicity on Vero cells up to 128 μM concentration. Compounds 7g and 13 were shown to retain their anti-TB activity against rifampin, isoniazid, and streptomycin resistant Mtb strains. The results suggest that quinoline−isoxazole-based anti-TB compounds are promising leads for new TB drug development

Synthesis, Biological Evaluation, and Structure−Activity Relationships for 5-[(<i>E</i>)-2-Arylethenyl]-3-isoxazolecarboxylic Acid Alkyl Ester Derivatives as Valuable Antitubercular Chemotypes

Tuberculosis (TB), mostly caused by Mycobacterium tuberculosis (Mtb), is one of the leading causes of death from infectious disease worldwide. Its coinfection with HIV and the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) strains have further worsened the TB pandemic. Despite its global impact, TB is considered a neglected disease and no new anti-TB therapeutics have been introduced over the last four decades. The nonreplicating persistent form of TB (NRP-TB) is responsible for the length of the treatment and is the putative cause of treatment failure. Therefore, new anti-TB agents, which are active against both the replicating form of Mtb (R-TB) and NRP-TB, are urgently needed. Herein, we report the synthesis and structure−activity relationships (SAR) of a series of 5-[(E)-2-arylethenyl]-3-isoxazolecarboxylic acid alkyl esters as potent anti-TB agents. Several compounds had submicromolar minimum inhibitory concentrations (MIC) against R-TB and were active against NRP-TB in the low micromolar range, thus representing attractive lead compounds for the possible development of new anti-TB agents

Rational Design of 5-Phenyl-3-isoxazolecarboxylic Acid Ethyl Esters as Growth Inhibitors of <i>Mycobacterium tuberculosis</i>. A Potent and Selective Series for Further Drug Development

New antituberculosis (anti-TB) drugs are urgently needed to shorten the 6−12 month treatment regimen and especially to battle drug-resistant Mycobacterium tuberculosis (Mtb) strains. In this study, we have continued our efforts to develop isoxazole-based anti-TB compounds by applying rational drug design approach. The biological activity and the structure−activity relationships (SAR) for a designed series of 5-phenyl-3-isoxazolecarboxylic acid ethyl ester derived anti-TB compounds were investigated. Several compounds were found to exhibit nanomolar activity against the replicating bacteria (R-TB) and low micromolar activity against the nonreplicating bacteria (NRP-TB). The series showed excellent selectivity toward Mtb, and in general, no cytotoxicity was observed in Vero cells (IC50 > 128 μM). Notably, selected compounds also retained their activity against isoniazid (INH), rifampin (RMP), and streptomycin (SM) resistant Mtb strains. Hence, benzyloxy, benzylamino, and phenoxy derivatives of 5-phenyl-3-isoxazolecarboxylic acid ethyl esters represent a highly potent, selective, and versatile series of anti-TB compounds and as such present attractive lead compounds for further TB drug development

Structure−Activity Relationships for a Series of Quinoline-Based Compounds Active against Replicating and Nonreplicating <i>Mycobacterium tuberculosis</i>

Tuberculosis (TB) remains as a global pandemic that is aggravated by a lack of health care, the spread of HIV, and the emergence of multidrug-resistant TB (MDR-TB) and extensively drug-resistant TB (XDR-TB) strains. New anti-TB drugs are urgently required to shorten the long 6−12 month treatment regimen and to battle drug-resistant Mtb strains. We have identified several potent quinoline-based anti-TB compounds, bearing an isoxazole containing side-chain. The most potent compounds, 7g and 13, exhibited submicromolar activity against the replicating bacteria (R-TB), with minimum inhibitory concentrations (MICs) of 0.77 and 0.95 μM, respectively. In general, these compounds also had micromolar activity against the nonreplicating persistent bacteria (NRP-TB) and did not show toxicity on Vero cells up to 128 μM concentration. Compounds 7g and 13 were shown to retain their anti-TB activity against rifampin, isoniazid, and streptomycin resistant Mtb strains. The results suggest that quinoline−isoxazole-based anti-TB compounds are promising leads for new TB drug development

Enhancing Hit Identification in Mycobacterium tuberculosis Drug Discovery Using Validated Dual-Event Bayesian Models

High-throughput screening (HTS) in whole cells is widely pursued to find compounds active against Mycobacterium tuberculosis (Mtb) for further development towards new tuberculosis (TB) drugs. Hit rates from these screens, usually conducted at 10 to 25 mu M concentrations, typically range from less than 1% to the low single digits. New approaches to increase the efficiency of hit identification are urgently needed to learn from past screening data. The pharmaceutical industry has for many years taken advantage of computational approaches to optimize compound libraries for in vitro testing, a practice not fully embraced by academic laboratories in the search for new TB drugs. Adapting these proven approaches, we have recently built and validated Bayesian machine learning models for predicting compounds with activity against Mtb based on publicly available large-scale HTS data from the Tuberculosis Antimicrobial Acquisition Coordinating Facility. We now demonstrate the largest prospective validation to date in which we computationally screened 82,403 molecules with these Bayesian models, assayed a total of 550 molecules in vitro, and identified 124 actives against Mtb. Individual hit rates for the different datasets varied from 15-28%. We have identified several FDA approved and late stage clinical candidate kinase inhibitors with activity against Mtb which may represent starting points for further optimization. The computational models developed herein and the commercially available molecules derived from them are now available to any group pursuing Mtb drug discovery

Airborne Antituberculosis Activity of <i>Eucalyptus citriodora</i> Essential Oil

The rapid emergence of multi- and extensively drug-resistant tuberculosis (MDR/XDR-TB) has created a pressing public health problem, which mostly affects regions with HIV/AIDS prevalence and represents a new constraint in the already challenging disease management of tuberculosis (TB). The present work responds to the need to reduce the number of contagious MDR/XRD-TB patients, protect their immediate environment, and interrupt the rapid spread by laying the groundwork for an inhalation therapy based on anti-TB-active constituents of the essential oil (EO) of Eucalyptus citriodora. In order to address the metabolomic complexity of EO constituents and active principles in botanicals, this study applied biochemometrics, a 3-D analytical approach that involves high-resolution CCC fractionation, GC-MS analysis, bioactivity measurements, and chemometric analysis. Thus, 32 airborne anti-TB-active compounds were identified in E. citriodora EO: the monoterpenes citronellol (1), linalool (3), isopulegol (5), and α-terpineol (7) and the sesquiterpenoids spathulenol (11), β-eudesmol (23), and τ-cadinol (25). The impact of the interaction of multiple components in EOs was studied using various artificial mixtures (AMxs) of the active monoterpenes 1, 2, and 5 and the inactive eucalyptol (33). Both neat 1 and the AMx containing 1, 2, and 33 showed airborne TB inhibition of >90%, while the major E. citriodora EO component, 2, was only weakly active, at 18% inhibition

Searching for New Cures for Tuberculosis: Design, Synthesis, and Biological Evaluation of 2-Methylbenzothiazoles

The actual development and clinical use of new therapeutics for tuberculosis (TB) have remained stagnant for years because of the complexity of the disease process, the treatment of which at present requires the administration of drug combinations over a 6 month period. There is thus an urgent need for the discovery and development of novel, more active, and less toxic anti-TB agents. In this study, we report on the chemistry and biology of a series of potent 5-(2-methylbenzothiazol-5-yloxymethyl)isoxazole-3-carboxamide derivatives, which proved to be active against replicating Mycobacterium tuberculosis (Mtb) H37Rv. The most potent compounds 7j and 7s were found to inhibit Mtb growth at micromolar concentrations, with MIC values of 1.4 and 1.9 μM, respectively. Impressively, all active compounds were nontoxic toward Vero cells (IC50 > 128 μM). Moreover, the best of these compounds were also tested against protozoan parasites, and some of these compounds were found to show activity, especially against Plasmodium falciparum. These studies thus suggest that certain 2-methylbenzothiazole based compounds may serve as promising lead scaffolds for further elaboration as anti-TB drugs and as possible antimalaria drugs

Enhancing Hit Identification in <i>Mycobacterium tuberculosis</i> Drug Discovery Using Validated Dual-Event Bayesian Models

<div><p>High-throughput screening (HTS) in whole cells is widely pursued to find compounds active against <i>Mycobacterium tuberculosis</i> (<i>Mtb</i>) for further development towards new tuberculosis (TB) drugs. Hit rates from these screens, usually conducted at 10 to 25 µM concentrations, typically range from less than 1% to the low single digits. New approaches to increase the efficiency of hit identification are urgently needed to learn from past screening data. The pharmaceutical industry has for many years taken advantage of computational approaches to optimize compound libraries for <i>in vitro</i> testing, a practice not fully embraced by academic laboratories in the search for new TB drugs. Adapting these proven approaches, we have recently built and validated Bayesian machine learning models for predicting compounds with activity against <i>Mtb</i> based on publicly available large-scale HTS data from the Tuberculosis Antimicrobial Acquisition Coordinating Facility. We now demonstrate the largest prospective validation to date in which we computationally screened 82,403 molecules with these Bayesian models, assayed a total of 550 molecules <i>in vitro</i>, and identified 124 actives against <i>Mtb</i>. Individual hit rates for the different datasets varied from 15–28%. We have identified several FDA approved and late stage clinical candidate kinase inhibitors with activity against <i>Mtb</i> which may represent starting points for further optimization. The computational models developed herein and the commercially available molecules derived from them are now available to any group pursuing <i>Mtb</i> drug discovery.</p></div

Mean (SD) leave one out and leave out 50%<b>×</b>100 cross validation of <i>Mtb</i> Bayesian models (ROC = receiver operator characteristic).

<p>Mean (SD) leave one out and leave out 50%<b>×</b>100 cross validation of <i>Mtb</i> Bayesian models (ROC = receiver operator characteristic).</p