How antibiotics kill bacteria: from targets to networks

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Abstract

Antibiotic drug-target interactions, and their respective direct effects, are generally well characterized. By contrast, the bacterial responses to antibiotic drug treatments that contribute to cell death are not as well understood and have proven to be complex as they involve many genetic and biochemical pathways. In this Review, we discuss the multilayered effects of drug-target interactions, including the essential cellular processes that are inhibited by bactericidal antibiotics and the associated cellular response mechanisms that contribute to killing. We also discuss new insights into these mechanisms that have been revealed through the study of biological networks, and describe how these insights, together with related developments in synthetic biology, could be exploited to create new antibacterial therapies.

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A common mechanism of cellular death induced by bactericidal antibiotics.

Michael A Kohanski, Daniel Dwyer, Boris Hayete … (2007)

Antibiotic mode-of-action classification is based upon drug-target interaction and whether the resultant inhibition of cellular function is lethal to bacteria. Here we show that the three major classes of bactericidal antibiotics, regardless of drug-target interaction, stimulate the production of highly deleterious hydroxyl radicals in Gram-negative and Gram-positive bacteria, which ultimately contribute to cell death. We also show, in contrast, that bacteriostatic drugs do not produce hydroxyl radicals. We demonstrate that the mechanism of hydroxyl radical formation induced by bactericidal antibiotics is the end product of an oxidative damage cellular death pathway involving the tricarboxylic acid cycle, a transient depletion of NADH, destabilization of iron-sulfur clusters, and stimulation of the Fenton reaction. Our results suggest that all three major classes of bactericidal drugs can be potentiated by targeting bacterial systems that remediate hydroxyl radical damage, including proteins involved in triggering the DNA damage response, e.g., RecA.

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The structural basis of ribosome activity in peptide bond synthesis.

P. NISSEN, J. Hansen, N Ban … (2000)

Using the atomic structures of the large ribosomal subunit from Haloarcula marismortui and its complexes with two substrate analogs, we establish that the ribosome is a ribozyme and address the catalytic properties of its all-RNA active site. Both substrate analogs are contacted exclusively by conserved ribosomal RNA (rRNA) residues from domain V of 23S rRNA; there are no protein side-chain atoms closer than about 18 angstroms to the peptide bond being synthesized. The mechanism of peptide bond synthesis appears to resemble the reverse of the acylation step in serine proteases, with the base of A2486 (A2451 in Escherichia coli) playing the same general base role as histidine-57 in chymotrypsin. The unusual pK(a) (where K(a) is the acid dissociation constant) required for A2486 to perform this function may derive in part from its hydrogen bonding to G2482 (G2447 in E. coli), which also interacts with a buried phosphate that could stabilize unusual tautomers of these two bases. The polypeptide exit tunnel is largely formed by RNA but has significant contributions from proteins L4, L22, and L39e, and its exit is encircled by proteins L19, L22, L23, L24, L29, and L31e.

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Inferring genetic networks and identifying compound mode of action via expression profiling.

Timothy S Gardner, Diego di Bernardo, David Lorenz … (2003)

The complexity of cellular gene, protein, and metabolite networks can hinder attempts to elucidate their structure and function. To address this problem, we used systematic transcriptional perturbations to construct a first-order model of regulatory interactions in a nine-gene subnetwork of the SOS pathway in Escherichia coli. The model correctly identified the major regulatory genes and the transcriptional targets of mitomycin C activity in the subnetwork. This approach, which is experimentally and computationally scalable, provides a framework for elucidating the functional properties of genetic networks and identifying molecular targets of pharmacological compounds.