Tetrahydropyrazolo[1,5-a]Pyrimidine-3-Carboxamide and N-Benzyl-6′,7′-Dihydrospiro[Piperidine-4,4′-Thieno[3,2-c]Pyran] analogues with bactericidal efficacy against Mycobacterium tuberculosis targeting MmpL3

Mycobacterium tuberculosis is a major human pathogen and the causative agent for the pulmonary disease, tuberculosis (TB). Current treatment programs to combat TB are under threat due to the emergence of multi-drug and extensively-drug resistant TB. As part of our efforts towards the discovery of new anti-tubercular leads, a number of potent tetrahydropyrazolo[1,5-a]pyrimidine-3-ca​rboxamide(THPP) and N-benzyl-6′,7′-dihydrospiro[piperidine-4,​4′-thieno[3,2-c]pyran](Spiro) analogues were recently identified against Mycobacterium tuberculosis and Mycobacterium bovis BCG through a high-throughput whole-cell screening campaign. Herein, we describe the attractive in vitro and in vivo anti-tubercular profiles of both lead series. The generation of M. tuberculosis spontaneous mutants and subsequent whole genome sequencing of several resistant mutants identified single mutations in the essential mmpL3 gene. This ‘genetic phenotype’ was further confirmed by a ‘chemical phenotype’, whereby M. bovis BCG treated with both the THPP and Spiro series resulted in the accumulation of trehalose monomycolate. In vivo efficacy evaluation of two optimized THPP and Spiro leads showed how the compounds were able to reduce >2 logs bacterial cfu counts in the lungs of infected mice

Predictive models for anti-tubercular molecules using machine learning on high-throughput biological screening datasets

<p>Abstract</p> <p>Background</p> <p>Tuberculosis is a contagious disease caused by <it>Mycobacterium tuberculosis </it>(Mtb), affecting more than two billion people around the globe and is one of the major causes of morbidity and mortality in the developing world. Recent reports suggest that Mtb has been developing resistance to the widely used anti-tubercular drugs resulting in the emergence and spread of multi drug-resistant (MDR) and extensively drug-resistant (XDR) strains throughout the world. In view of this global epidemic, there is an urgent need to facilitate fast and efficient lead identification methodologies. Target based screening of large compound libraries has been widely used as a fast and efficient approach for lead identification, but is restricted by the knowledge about the target structure. Whole organism screens on the other hand are target-agnostic and have been now widely employed as an alternative for lead identification but they are limited by the time and cost involved in running the screens for large compound libraries. This could be possibly be circumvented by using computational approaches to prioritize molecules for screening programmes.</p> <p>Results</p> <p>We utilized physicochemical properties of compounds to train four supervised classifiers (Naïve Bayes, Random Forest, J48 and SMO) on three publicly available bioassay screens of Mtb inhibitors and validated the robustness of the predictive models using various statistical measures.</p> <p>Conclusions</p> <p>This study is a comprehensive analysis of high-throughput bioassay data for anti-tubercular activity and the application of machine learning approaches to create target-agnostic predictive models for anti-tubercular agents.</p

Identification of Novel Mt-Guab2 Inhibitor Series Active against M. tuberculosis

Tuberculosis (TB) remains a leading cause of mortality worldwide. With the emergence of multidrug resistant TB, extensively drug resistant TB and HIV-associated TB it is imperative that new drug targets be identified. The potential of Mycobacterium tuberculosis inosine monophosphate dehydrogenase (IMPDH) as a novel drug target was explored in the present study. IMPDH exclusively catalyzes the conversion of inosine monophosphate (IMP) to xanthosine monophosphate (XMP) in the presence of the cofactor nicotinamide adenine dinucleotide (NAD+). Although the enzyme is a dehydrogenase, the enzyme does not catalyze the reverse reaction i.e. the conversion of XMP to IMP. Unlike other bacteria, M. tuberculosis harbors three IMPDH-like genes, designated as Mt-guaB1, Mt-guaB2 and Mt-guaB3 respectively. Of the three putative IMPDH's, we previously confirmed that Mt-GuaB2 was the only functional ortholog by characterizing the enzyme kinetically. Using an in silico approach based on designed scaffolds, a series of novel classes of inhibitors was identified. The inhibitors possess good activity against M. tuberculosis with MIC values in the range of 0.4 to 11.4 µg mL−1. Among the identified ligands, two inhibitors have nanomolar Kis against the Mt-GuaB2 enzyme

Biochemical and structural characterization of mycobacterial aspartyl-tRNA synthetase AspS, a promising TB drug target.

The human pathogen Mycobacterium tuberculosis is the causative agent of pulmonary tuberculosis (TB), a disease with high worldwide mortality rates. Current treatment programs are under significant threat from multi-drug and extensively-drug resistant strains of M. tuberculosis, and it is essential to identify new inhibitors and their targets. We generated spontaneous resistant mutants in Mycobacterium bovis BCG in the presence of 10× the minimum inhibitory concentration (MIC) of compound 1, a previously identified potent inhibitor of mycobacterial growth in culture. Whole genome sequencing of two resistant mutants revealed in one case a single nucleotide polymorphism in the gene aspS at 535GAC>535AAC (D179N), while in the second mutant a single nucleotide polymorphism was identified upstream of the aspS promoter region. We probed whole cell target engagement by overexpressing either M. bovis BCG aspS or Mycobacterium smegmatis aspS, which resulted in a ten-fold and greater than ten-fold increase, respectively, of the MIC against compound 1. To analyse the impact of inhibitor 1 on M. tuberculosis AspS (Mt-AspS) activity we over-expressed, purified and characterised the kinetics of this enzyme using a robust tRNA-independent assay adapted to a high-throughput screening format. Finally, to aid hit-to-lead optimization, the crystal structure of apo M. smegmatis AspS was determined to a resolution of 2.4 Å