Getting Closer to the Real Bacterial Cell Wall Target: Biomolecular Interactions of Water‐Soluble Lipid II with Glycopeptide Antibiotics

Vollmerhaus, Pauline J.; Breukink, Eefjan; Heck, Albert J. R.

doi:10.1002/chem.200390179

Cited by 25 publications

(16 citation statements)

References 49 publications

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“…The rate of bacterial killing by nisin over the studied concentration range was satisfactorily described when modeled to be proportional to the nisin concentration, and a more complex function was not necessary to describe the profiles. This second-order killing function for nisin was in agreement with its ability to form pores in bacterial membranes (16,38). The killing rate constant was 85.5-fold lower for the Nis i and 821-fold lower for the Nis r populations compared to the Nis s populations (Table 1).…”

Section: Resultssupporting

confidence: 71%

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Landersdorfer

et al. 2013

Antimicrob Agents Chemother

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Quantitative modeling of combination therapy can describe the effects of each antibiotic against multiple bacterial populations. Our aim was to develop an efficient experimental and modeling strategy that evaluates different synergy mechanisms using a rapidly killing peptide antibiotic (nisin) combined with amikacin or linezolid as probe drugs. Serial viable counts over 48 h were obtained in time-kill experiments with all three antibiotics in monotherapy against a methicillin-resistant Staphylococcus aureus USA300 strain (inoculum, 10 8 CFU/ml). A sequential design (initial dosing of 8 or 32 mg/liter nisin, switched to amikacin or linezolid at 1.5 h) assessed the rate of killing by amikacin and linezolid against nisin-intermediate and nisin-resistant populations. Simultaneous combinations were additionally studied and all viable count profiles comodeled in S-ADAPT and NONMEM. A mechanism-based model with six populations (three for nisin times two for amikacin) yielded unbiased and precise (r ‫؍‬ 0.99, slope ‫؍‬ 1.00; S-ADAPT) individual fits. The second-order killing rate constants for nisin against the three populations were 5.67, 0.0664, and 0.00691 liter/(mg · h). For amikacin, the maximum killing rate constants were 10.1 h ؊1 against its susceptible and 0.771 h ؊1 against its less-susceptible populations, with 14.7 mg/liter amikacin causing half-maximal killing. After incorporating the effects of nisin and amikacin against each population, no additional synergy function was needed. Linezolid inhibited successful bacterial replication but did not efficiently kill populations less susceptible to nisin. Nisin plus amikacin achieved subpopulation synergy. The proposed sequential and simultaneous dosing design offers an efficient approach to quantitatively characterize antibiotic synergy over time and prospectively evaluate antibiotic combination dosing strategies.

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Section: Resultssupporting

confidence: 71%

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Landersdorfer

et al. 2013

Antimicrob Agents Chemother

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“…The solution-phase structures of complexes formed between the vancomycin-group antibiotics and several small bacterial cell-wall mimicking peptides have been elucidated using NMR spectroscopy [3, 18 -20] and X-Ray [6, 21,22]. Electrospray ionization mass spectrometry (ESI-MS) has been applied to study vancomycinpeptide complexes in gas phase [23][24][25][26][27][28][29][30][31][32]. These gas-phase ESI-MS studies have determined the stoichiometry of vancomycin complexes and relative binding affinities for D/L-peptide stereoisomers.…”

Section: Vancomycin-peptide Noncovalent Complexesmentioning

confidence: 99%

Fluorescence lifetime probe of biomolecular conformations

Shi¹,

Parks²

2010

J. Am. Soc. Mass Spectrom.

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Methods have been developed to measure the fluorescence lifetime versus temperature of trapped biomolecular ions derivatized with a fluorescent dye. Previous measurements for different sequences of polyproline peptides demonstrated that quenching rates are related to conformations and their spatial fluctuations. This paper presents the results of extending these methods to study the conformational dynamics of larger biomolecules. Vancomycin-peptide noncovalent complexes in the 1ϩ charge state were studied as a function of temperature for different W-KAA peptide chiralities (L-LDD, D-LDD, L-DLL). Fluorescence-quenching rates, k q , were found to be stereoselective for these different chiralities with relative magnitudesThe variation in fluorescent quenching resulting from switching the chirality of the single Trp residue was readily detectable. Molecular dynamics analysis of complexes formed by W-KAA (L-LDD) and W-KAA(L-DLL) indicates that increased flexibility in the (L-DLL) complex is correlated with reduced quenching rates. Fluorescence measurements were also performed for the Trp-cage protein comparing quenching rates in the 1ϩ, 2ϩ, and 3ϩ charge states for which k q. Measurements of a sequence including a single-point mutation infer the presence of a salt-bridge structure in the 1ϩ charge state and its absence in both the 2ϩ and 3ϩ states. Molecular dynamics structures of Trp-cage indicate that a salt bridge in the 1ϩ charge state produces more compact conformations leading to larger quenching rates based on the quenching mechanism. In both these experimental studies the fluorescence-quenching rates were consistent with changes in structure induced by either intermolecular or intramolecular interactions. (J Am Soc Mass Spectrom 2010, 21, 707-718) © 2010 American Society for Mass Spectrometry P revious measurements [1] of the lifetime of a fluorescent dye covalently bound to polypeptide ions exhibited a quenching rate that depends both on the separation of the dye to a Trp side chain and on the strength of electrostatic fields in the vicinity of the dye. Quenching rates were found to depend on specific peptide sequences giving rise to different conformations and spatial fluctuations characterized by each conformation. Consequently, lifetime measurements provide an opportunity to extract information sensitive to local molecular arrangements and, perhaps more importantly, changes in that arrangement determined by intramolecular and intermolecular interactions. This paper applies lifetime measurements to study two larger biomolecules: the vancomycin-peptide noncovalent complex and the Trp-cage protein. The structures of these biomolecules have been identified in NMR solution measurements; and each has been studied previously in gas-phase measurements. Results of gas-phase studies of the vancomycin-peptide complex infer that specific changes in the peptide ligand chirality lead to different hydrogen binding networks and thus to different conformations. Gas-phase measurements and calculations of Trp-cage protein i...

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“…Vancomycin primarily interacts with the peptidic region of lipid II and the interaction between vancomycin and a range of lipid II peptidoglycan analogs has been studied using a variety of techniques. Lipid II is insoluble in water and thus most investigations of the recognition of lipid II by vancomycin have involved either chemically modified or truncated fragments of lipid II [10]. NMR and X-ray crystallographic studies [11][12][13][14][15][16][17] showed that the ligand bound to the concave (front face) of vancomycin, the C-terminal carboxylic acid group of D-Ala-D-Ala interacting with the backbone amide groups of resides NLEU1, HDPY2 and ASN3.…”

Section: Introductionmentioning

confidence: 99%

Vancomycin: ligand recognition, dimerization and super‐complex formation

et al. 2013

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The antibiotic vancomycin targets lipid II, blocking cell wall synthesis in Gram-positive bacteria. Despite extensive study, questions remain regarding how it recognizes its primary ligand and what is the most biologically relevant form of vancomycin. In this study, molecular dynamics simulation techniques have been used to examine the process of ligand binding and dimerization of vancomycin. Starting from one or more vancomycin monomers in solution, together with different peptide ligands derived from lipid II, the simulations predict the structures of the ligated monomeric and dimeric complexes to within 0.1 nm rmsd of the structures determined experimentally. The simulations reproduce the conformation transitions observed by NMR and suggest that proposed differences between the crystal structure and the solution structure are an artifact of the way the NMR data has been interpreted in terms of a structural model. The spontaneous formation of both back-to-back and face-to-face dimers was observed in the simulations. This has allowed a detailed analysis of the origin of the cooperatively between ligand binding and dimerization and suggests that the formation of face-to-face dimers could be functionally significant. The work also highlights the possible role of structural water in stabilizing the vancomycin ligand complex and its role in the manifestation of vancomycin resistance.

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Getting Closer to the Real Bacterial Cell Wall Target: Biomolecular Interactions of Water‐Soluble Lipid II with Glycopeptide Antibiotics

Cited by 25 publications

References 49 publications

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Quantifying Subpopulation Synergy for Antibiotic Combinations via Mechanism-Based Modeling and a Sequential Dosing Design

Fluorescence lifetime probe of biomolecular conformations

Vancomycin: ligand recognition, dimerization and super‐complex formation

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