Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens

Velikova, Nadya and Fulle, Simone and Manso, Ana and Mechkarska, Milena and Finn, Paul W. and Conlon, J. Michael and Oggioni, Marco Rinaldo and Wells, Jerry and Marina, Alberto (2016) Putative histidine kinase inhibitors with antibacterial effect against multi-drug resistant clinical isolates identified by in vitro and in silico screens. Scientific Reports, 6. ISSN 2045-2322

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Abstract

Novel antibacterials are urgently needed to address the growing problem of bacterial resistance to conventional antibiotics. Two-component systems (TCS) are widely used by bacteria to regulate gene expression in response to various environmental stimuli and physiological stress and have been previously proposed as promising antibacterial targets. TCS consist of a sensor histidine kinase (HK) and an effector response regulator. The HK component contains a highly conserved ATP-binding site that is considered to be a promising target for broad-spectrum antibacterial drugs. Here, we describe the identification of putative HK autophosphorylation inhibitors following two independent experimental approaches: in vitro fragment-based screen via differential scanning fluorimetry and in silico structure-based screening, each followed up by the exploration of analogue compounds as identified by ligand-based similarity searches. Nine of the tested compounds showed antibacterial effect against multi-drug resistant clinical isolates of bacterial pathogens and include three novel scaffolds, which have not been explored so far in other antibacterial compounds. Overall, putative HK autophosphorylation inhibitors were found that together provide a promising starting point for further optimization as antibacterials.

Item Type: Article
Uncontrolled Keywords: Drug development; virtual screening; antibiotics resistance; Two-component systems
Subjects: Q Science > QR Microbiology
R Medicine > RM Therapeutics. Pharmacology
Divisions: School of Science > Applied Computing
School of Science > Metabolic Research
Depositing User: Paul Finn
Date Deposited: 23 May 2016 15:38
Last Modified: 02 Aug 2017 10:11
URI: http://bear.buckingham.ac.uk/id/eprint/135

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