Dataset Information

Substituted aminopyrimidine protein kinase B (PknB) inhibitors show activity against Mycobacterium tuberculosis.

ABSTRACT: A high-throughput screen against PknB, an essential serine-threonine protein kinase present in Mycobacterium tuberculosis (M. tuberculosis), allowed the identification of an aminoquinazoline inhibitor which was used as a starting point for SAR investigations. Although a significant improvement in enzyme affinity was achieved, the aminoquinazolines showed little or no cellular activity against M. tuberculosis. However, switching to an aminopyrimidine core scaffold and the introduction of a basic amine side chain afforded compounds with nanomolar enzyme binding affinity and micromolar minimum inhibitory concentrations against M. tuberculosis. Replacement of the pyrazole head group with pyridine then allowed equipotent compounds with improved selectivity against a human kinase panel to be obtained.

SUBMITTER: Chapman TM

PROVIDER: S-EPMC3368261 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Substituted aminopyrimidine protein kinase B (PknB) inhibitors show activity against Mycobacterium tuberculosis.

Chapman Timothy M TM Bouloc Nathalie N Buxton Roger S RS Chugh Jasveen J Lougheed Kathryn E A KE Osborne Simon A SA Saxty Barbara B Smerdon Stephen J SJ Taylor Debra L DL Whalley David D

Bioorganic & medicinal chemistry letters 20120314 9

A high-throughput screen against PknB, an essential serine-threonine protein kinase present in Mycobacterium tuberculosis (M. tuberculosis), allowed the identification of an aminoquinazoline inhibitor which was used as a starting point for SAR investigations. Although a significant improvement in enzyme affinity was achieved, the aminoquinazolines showed little or no cellular activity against M. tuberculosis. However, switching to an aminopyrimidine core scaffold and the introduction of a basic ...[more]

PMID: 22469702

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Project description:BACKGROUND: Mycobacterium tuberculosis (M.tb) is the causative agent of tuberculosis, killing ~1.7 million people annually. The remarkable capacity of this pathogen to escape the host immune system for decades and then to cause active tuberculosis disease, makes M.tb a successful pathogen. Currently available anti-mycobacterial therapy has poor compliance due to requirement of prolonged treatment resulting in accelerated emergence of drug resistant strains. Hence, there is an urgent need to identify new chemical entities with novel mechanism of action and potent activity against the drug resistant strains. RESULTS: This study describes novel computational models developed for predicting inhibitors against both replicative and non-replicative phase of drug-tolerant M.tb under carbon starvation stage. These models were trained on highly diverse dataset of 2135 compounds using four classes of binary fingerprint namely PubChem, MACCS, EState, SubStructure. We achieved the best performance Matthews correlation coefficient (MCC) of 0.45 using the model based on MACCS fingerprints for replicative phase inhibitor dataset. In case of non-replicative phase, Hybrid model based on PubChem, MACCS, EState, SubStructure fingerprints performed better with maximum MCC value of 0.28. In this study, we have shown that molecular weight, polar surface area and rotatable bond count of inhibitors (replicating and non-replicating phase) are significantly different from non-inhibitors. The fragment analysis suggests that substructures like hetero_N_nonbasic, heterocyclic, carboxylic_ester, and hetero_N_basic_no_H are predominant in replicating phase inhibitors while hetero_O, ketone, secondary_mixed_amine are preferred in the non-replicative phase inhibitors. It was observed that nitro, alkyne, and enamine are important for the molecules inhibiting bacilli residing in both the phases. In this study, we introduced a new algorithm based on Matthews correlation coefficient called MCCA for feature selection and found that this algorithm is better or comparable to frequency based approach. CONCLUSION: In this study, we have developed computational models to predict phase specific inhibitors against drug resistant strains of M.tb grown under carbon starvation. Based on simple molecular properties, we have derived some rules, which would be useful in robust identification of tuberculosis inhibitors. Based on these observations, we have developed a webserver for predicting inhibitors against drug tolerant M.tb H37Rv available at http://crdd.osdd.net/oscadd/mdri/.

Dataset Information

Substituted aminopyrimidine protein kinase B (PknB) inhibitors show activity against Mycobacterium tuberculosis.

Publications

Substituted aminopyrimidine protein kinase B (PknB) inhibitors show activity against Mycobacterium tuberculosis.

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