Aminoglycoside binding to human and bacterial A-Site rRNA decoding region constructs

The 16S bacterial ribosomal A-site decoding rRNA region is thought to be the pharmacological target for the aminoglycoside antibiotics. The clinical utility of aminoglycosides could possibly depend on the preferential binding of these drugs to the prokaryotic A-site versus the corresponding A-site from eukaryotes. However, quantitative aminoglycoside binding experiments reported here on prokaryotic and eukaryotic A-site RNA constructs show that there is little in the way of differential binding affinities of aminoglycosides for the two targets. The largest difference in affinity is 4-fold in the case of neomycin, with the prokaryotic A-site construct exhibiting the higher binding affinity. Mutational studies revealed that decoding region constructs retaining elements of non-Watson-Crick (WC) base pairing, specifically bound aminoglycosides with affinities in the muM range. These studies are consistent with the idea that aminoglycoside antibiotics can specifically bind to RNA molecules as long as the latter have non-A form structural elements allowing access of aminoglycosides to the narrow major groove.     

Engineering the rRNA decoding site of eukaryotic cytosolic ribosomes in bacteria

Structural and genetic studies on prokaryotic ribosomes have provided important insights into fundamental aspects of protein synthesis and translational control and its interaction with ribosomal drugs. Comparable mechanistic studies in eukaryotes are mainly hampered by the absence of both high-resolution crystal structures and efficient genetic models. To study the interaction of aminoglycoside antibiotics with selected eukaryotic ribosomes, we replaced the bacterial drug binding site in 16S rRNA with its eukaryotic counterpart, resulting in bacterial hybrid ribosomes with a fully functional eukaryotic rRNA decoding site. Cell-free translation assays demonstrated that hybrid ribosomes carrying the rRNA decoding site of higher eukaryotes show pronounced resistance to aminoglycoside antibiotics, equivalent to that of rabbit reticulocyte ribosomes, while the decoding sites of parasitic protozoa show distinctive drug susceptibility. Our findings suggest that phylogenetically variable components of the ribosome, other than the rRNA-binding site, do not affect aminoglycoside susceptibility of the protein-synthesis machinery. The activities of the hybrid ribosomes indicate that helix 44 of the rRNA decoding site behaves as an autonomous domain, which can be exchanged between ribosomes of different phylogenetic domains for study of function.     

Evidence That Antibiotics Bind to Human Mitochondrial Ribosomal RNA Has Implications for Aminoglycoside Toxicity

Aminoglycosides are a well known antibiotic family used to treat bacterial infections in humans and animals, but which can be toxic. By binding to the decoding site of helix44 of the small subunit RNA of the bacterial ribosome, the aminoglycoside antibiotics inhibit protein synthesis, cause misreading, or obstruct peptidyl-tRNA translocation. Although aminoglycosides bind helix69 of the bacterial large subunit RNA as well, little is known about their interaction with the homologous human helix69. To probe the role this binding event plays in toxicity, changes to thermal stability, base stacking, and conformation upon aminoglycoside binding to the human cytoplasmic helix69 were compared with those of the human mitochondrial and Escherichia coli helix69. Surprisingly, binding of gentamicin and kanamycin A to the chemically synthesized terminal hairpins of the human cytoplasmic, human mitochondrial, and E. coli helix69 revealed similar dissociation constants (1.3–1.7 and 4.0–5.4 μm, respectively). In addition, aminoglycoside binding enhanced conformational stability of the human mitochondrial helix69 by increasing base stacking. Proton one-dimensional and two-dimensional NMR suggested significant and specific conformational changes of human mitochondrial and E. coli helix69 upon aminoglycoside binding, as compared with human cytoplasmic helix69. The conformational changes and similar aminoglycoside binding affinities observed for human mitochondrial helix69 and E. coli helix69, as well as the increase in structural stability shown for the former, suggest that this binding event is important to understanding aminoglycoside toxicity.     

Decoding region bubble size and aminoglycoside antibiotic binding

Aminoglycoside antibiotics promiscuously bind to structurally diverse RNA molecules containing internal bubbles and bulges with affinities in the microM range. An interesting exception is found in the human 12S mitochondrial decoding region where aminoglycoside binding, unlike in the case of its bacterial and human cytoplasmic counterparts, is absent. Mutations that reduce the size of the bubble in the 12S decoding region immediately restore aminoglycoside binding, giving the system chemical switch like behavior.     

Ligand binding analysis and screening by chemical denaturation shift

The identification of small molecule ligands is an important first step in drug development, especially drugs that target proteins with no intrinsic activity. Toward this goal, it is important to have access to technologies that are able to measure binding affinities for a large number of potential ligands in a fast and accurate way. Because ligand binding stabilizes the protein structure in a manner dependent on concentration and binding affinity, the magnitude of the protein stabilization effect elicited by binding can be used to identify and characterize ligands. For example, the shift in protein denaturation temperature (T_m shift) has become a popular approach to identify potential ligands. However, T_m shifts cannot be readily transformed into binding affinities, and the ligand rank order obtained at denaturation temperatures (?60 °C) does not necessarily coincide with the rank order at physiological temperature. An alternative approach is the use of chemical denaturation, which can be implemented at any temperature. Chemical denaturation shifts allow accurate determination of binding affinities with a surprisingly wide dynamic range (high micromolar to sub nanomolar) and in situations where binding changes the cooperativity of the unfolding transition. In this article, we develop the basic analytical equations and provide several experimental examples.     

Energy landscape of the ribosomal decoding center

The ribosome decodes the genetic information that resides in nucleic acids. A key component of the decoding mechanism is a conformational switch in the decoding center of the small ribosomal subunit discovered in high-resolution X-ray crystallography studies. It is known that small subunit nucleotides A1492 and A1493 flip out of helix 44 upon transfer RNA (tRNA) binding; however, the operation principles of this switch remain unknown. Replica molecular dynamics simulations reveal a low free energy barrier between flipped-out and flipped-in states, consistent with a switch that can be controlled by shifting the equilibrium between states. The barrier determined by the simulations is sufficiently small for the binding of ligands, such as tRNAs or aminoglycoside antibiotics, to shift the equilibrium.     

An adaptable pentaloop defines a robust neomycin-B RNA aptamer with conditional ligand-bound structures

Aptamers can be highly specific for their targets, which implies precise molecular recognition between aptamer and target. However, as small polymers, their structures are more subject to environmental conditions than the more constrained longer RNAs such as those that constitute the ribosome. To understand the balance between structural and environmental factors in establishing ligand specificity of aptamers, we examined the RNA aptamer (NEO1A) previously reported as specific for neomycin-B. We show that NEO1A can recognize other aminoglycosides with similar affinities as for neomycin-B and its aminoglycoside specificity is strongly influenced by ionic strength and buffer composition. NMR and 2-aminopurine (2AP) fluorescence studies of the aptamer identified a flexible pentaloop and a stable binding pocket. Consistent with a well-structured binding pocket, docking analysis results correlated with experimental measures of the binding energy for most ligands. Steady state fluorescence studies of 2AP-substituted aptamers confirmed that A16 moves to a more solvent accessible position upon ligand binding while A14 moves to a less solvent accessible position, which is most likely a base stack. Analysis of binding affinities of NEO1A sequence variants showed that the base in position 16 interacts differently with each ligand and the interaction is a function of the buffer constituents. Our results show that the pentaloop provides NEO1A with the ability to adapt to external influences on its structure, with the critical base at position 16 adjusting to incorporate each ligand into a stable pocket by hydrophobic interactions and/or hydrogen bonds depending on the ligand and the ionic environment.     

Quantitative affinity electrophoresis of RNA–small molecule interactions by cross-linking the ligand to acrylamide

We show that the affinity electrophoresis analysis of RNA–small molecule interactions can be made quantifiable by cross-linking the ligand to the gel matrix. Using an RNA–aminoglycoside model system to verify our method, we attached an acryloyl chloride molecule to the aminoglycosides paromomycin and neomycin B to synthesize an acrylamide–aminoglycoside monomer. This molecule was then used as a component in gel polymerization for affinity electrophoresis, covalently attaching an aminoglycoside molecule to the gel matrix. To test RNA binding to the cross-linked aminoglycosides, we used the aminoglycoside binding RNA molecule derived from thymidylate synthase messenger RNA (mRNA) that contains a C–C mismatch. Binding is indicated by the difference in RNA mobility between gels with cross-linked ligand, with ligand embedded during polymerization, and with no ligand present. Critically, the predicted straight line relationship between the reciprocal of the relative migration of the RNA and the ligand concentration is obtained when using cross-linked aminoglycosides, whereas a straight line is not obtained using embedded aminoglycosides. Average apparent dissociation constants are determined from the slope of the line from these plots. This method allows an easy quantitative comparison between different nucleic acid molecules for a small molecule ligand.     

Effect of solvent and protein dynamics in ligand recognition and inhibition of aminoglycoside adenyltransferase 2″‐Ia

The aminoglycoside modifying enzyme (AME) ANT(2″)‐Ia is a significant target for next generation antibiotic development. Structural studies of a related aminoglycoside‐modifying enzyme, ANT(3″)(9), revealed this enzyme contains dynamic, disordered, and well‐defined segments that modulate thermodynamically before and after antibiotic binding. Characterizing these structural dynamics is critical for in situ screening, design, and development of contemporary antibiotics that can be implemented in a clinical setting to treat potentially lethal, antibiotic resistant, human infections. Here, the first NMR structural ensembles of ANT(2″)‐Ia are presented, and suggest that ATP‐aminoglycoside binding repositions the nucleotidyltransferase (NT) and C‐terminal domains for catalysis to efficiently occur. Residues involved in ligand recognition were assessed by site‐directed mutagenesis. In vitro activity assays indicate a critical role for I129 toward aminoglycoside modification in addition to known catalytic D44, D46, and D48 residues. These observations support previous claims that ANT aminoglycoside sub‐class promiscuity is not solely due to binding cleft size, or inherent partial disorder, but can be controlled by ligand modulation on distinct dynamic and thermodynamic properties of ANTs under cellular conditions. Hydrophobic interactions in the substrate binding cleft, as well as solution dynamics in the C‐terminal tail of ANT(2″)‐Ia, advocate toward design of kanamycin‐derived cationic lipid aminoglycoside analogs, some of which have already shown antimicrobial activity in vivo against kanamycin and gentamicin‐resistant P. aeruginosa. This data will drive additional in silico, next generation antibiotic development for future human use to combat increasingly prevalent antimicrobial resistance.     

Ligand binding and activation in a prokaryotic cyclic nucleotide-modulated channel

We designed a technique that directly determines binding of cyclic nucleotides to the prokaryotic cyclic nucleotide modulated ion channel MloK1. The ability to purify large quantities of MloK1 facilitated equilibrium binding assays, which avoided the inherent problem of relatively low affinity binding which hindered the use of eukaryotic channels. We found that MloK1 specifically binds cAMP and cGMP with affinity values in the range of those observed for activity assays for eukaryotic channels. Notably, the concentration of ligand that elicited 50% of maximum response in (86)Rb flux assays (K1/2), also referred to as ligand sensitivity, was smaller than the corresponding value obtained from binding assays (Kd) potentially indicating significant channel activity in partially liganded states. To gain further insight into the mechanism of binding and activation of these channels, we mutated several amino acids in the ligand-binding pocket of MloK1, known from electrophysiological studies of homologous eukaryotic channels to affect ligand selectivity and binding efficacy. The S308V MloK1 mutant (a mutation which decreases cGMP selectivity in eukaryotic channels) decreased both the observed cGMP binding affinity and the sensitivity to cGMP relative to the wild-type (WT) channel, leaving those for cAMP unchanged. Conversely, the A352D MloK1 mutant (a mutation which increases cGMP selectivity in eukaryotic channels) increased both the affinity and the sensitivity for cGMP relative to the WT channel, again leaving those for cAMP unchanged. Mutations at R307 in MloK1, the most conserved residue in the binding pocket of cyclic nucleotide-binding proteins, were not tolerated as these mutants do not form functional channels. Furthermore, for each mutation, changes in binding affinities were mirrored by equivalent changes in ligand sensitivity. These data, together with the evidence that partially liganded channels open significantly, suggested strong coupling between cyclic nucleotide binding and MloK1 channel opening.     

ATP binding enables broad antibiotic selectivity of aminoglycoside phosphotransferase(3')-IIIa: an elastic network analysis

The bacterial enzyme aminoglycoside phosphotransferase(3′)-IIIa (APH) confers resistance against a wide range of aminoglycoside antibiotics. In this study, we use the Gaussian network model to investigate how the binding of nucleotides and antibiotics influences the dynamics and thereby the ligand binding properties of APH. Interestingly, in NMR experiments, the dynamics differ significantly in various APH complexes, although crystallographic studies indicate that no larger conformational changes occur upon ligand binding. Isothermal titration calorimetry also shows different thermodynamic contributions to ligand binding. Formation of aminoglycoside-APH complexes is enthalpically driven, while the enthalpic change upon aminoglycoside binding to the nucleotide-APH complex is much smaller. The differential effects of nucleotide binding and antibiotic binding to APH can be explained theoretically by single-residue fluctuations and correlated motions of the enzyme. The surprising destabilization of β-sheet residues upon nucleotide binding, as seen in hydrogen/deuterium exchange experiments, shows that the number of closest neighbors does not fully explain residue flexibility. Additionally, we must consider correlated motions of dynamic protein domains, which show that not only connectivity but also the overall protein architecture is important for protein dynamics.     

Conformational switch in the decoding region of 16S rRNA during aminoacyl-tRNA selection on the ribosome

Binding of aminoglycoside antibiotics to 16S ribosomal RNA induces a particular structure of the decoding center and increases the misincorporation of near-cognate amino acids. By kinetic analysis we show that this is due to stabilization of the near-cognate codon recognition complex and the acceleration of two rearrangements that limit the rate of amino acid incorporation. The same rearrangement steps are accelerated in the cognate coding situation. We suggest that cognate codon recognition, or near-cognate codon recognition augmented by aminoglycoside binding, promote the transition of 16S rRNA from a 'binding' to a 'productive' conformation that determines the fidelity of decoding.     

Streptomyces rimosus Aminoglycoside 3"-Phosphotransferase VIII: Comparisons with Aminoglycoside 3"-Phosphotransferases of Aminoglycoside-Producing Strains and with Eukaryotic Protein Kinases

The nucleotide sequence was established for the aphVIII aminoglycoside phosphotransferase gene of an oxytetracycline-producing Streptomyces rimosus strain. The gene is 804 bp in size and possibly codes for APHVIII of 267 residues. Heterologous expression of aphVIII was studied in Escherichia coli and Chlamydomonas reinhardtii. The deduced APHVIII sequence was compared with known sequences of aminoglycoside phosphotransferases of aminoglycoside-producing actinomycete strains and of eukaryotic protein kinases. A local homology of 38 residues was found between APHVIII and actinomycete serine–threonine protein kinases in the conserved region possibly involved in ATP binding. APHVIII differed from aminoglycoside 3"-phosphotransferases of aminoglycoside-producing actinomycete strains and of clinical isolates, and can be classed to a separate group.     

Compressed images for affinity prediction-2 (CIFAP-2): an improved machine learning methodology on protein–ligand interactions based on a study on caspase 3 inhibitors

Abstract

The aim of this study is to propose an improved computational methodology, which is called Compressed Images for Affinity Prediction-2 (CIFAP-2) to predict binding affinities of structurally related protein–ligand complexes. CIFAP-2 method is established based on a protein–ligand model from which computational affinity information is obtained by utilizing 2D electrostatic potential images determined for the binding site of protein–ligand complexes. The quality of the prediction of the CIFAP-2 algorithm was tested using partial least squares regression (PLSR) as well as support vector regression (SVR) and adaptive neuro-fuzzy ?nference system (ANFIS), which are highly promising prediction methods in drug design. CIFAP-2 was applied on a protein–ligand complex system involving Caspase 3 (CASP3) and its 35 inhibitors possessing a common isatin sulfonamide pharmacophore. As a result, PLSR affinity prediction for the CASP3–ligand complexes gave rise to the most consistent information with reported empirical binding affinities (pIC₅₀) of the CASP3 inhibitors.     

Identification of RNA–ligand interactions by affinity electrophoresis

We have developed an affinity electrophoresis method to screen for RNA–ligand interactions. Native polyacrylamide gels were polymerized in the absence and presence of different RNA binding molecules. Binding is indicated by a difference in mobility between the gel with ligand present and the gel with no ligand present. The utility of this method was demonstrated using the known interaction between the Escherichia coli ribosomal A-site RNA and different aminoglycoside ligands. The RNA–aminoglycoside interaction observed is dose dependent, and the affinity mirrors what is observed in solution. In addition, we used this method to gauge the affinity to different aminoglycoside molecules of an RNA molecule derived from the thymidylate synthase mRNA construct that contains a CC mismatch.     

Cross-linking reconsidered: binding and cross-linking fields and the cellular response.

We analyze a model for the reversible cross-linking of cell surface receptors by a collection of bivalent ligands with different affinities for the receptor as would be found in a polyclonal anti-receptor serum. We assume that the amount of cross-linking determines, via a monotonic function, the rate at which cells become activated and divide. In addition to the density of receptors on the cell surface, two quantities, the binding field and the cross-linking field, are needed to characterize the cross-linking curve, i.e., the equilibrium concentration of cross-linked receptors plotted as a function of the total ligand site concentration. The binding field is the sum of all ligand site concentrations weighted by their respective binding affinities, and the cross-linking field is the sum of all ligand site concentrations weighted by the product of their respective binding and cross-linking affinity and the total receptor density. Assuming that the cross-linking affinity decreases if the binding affinity decreases, we find that the height of the cross-linking curve decreases, its width narrows, and its center shifts to higher ligand site concentrations as the affinities decrease. Moreover, when we consider cross-linking-induced proliferation, we find that there is a minimum cross-linking affinity that must be surpassed before a clone can expand. We also show that under many circumstances a polyclonal antiserum would be more likely than a monoclonal antibody to lead to cross-linking-induced proliferation.     

Label-free quantification of membrane-ligand interactions using backscattering interferometry

Although membrane proteins are ubiquitous within all living organisms and represent the majority of drug targets, a general method for direct, label-free measurement of ligand binding to native membranes has not been reported. Here we show that backscattering interferometry (BSI) can accurately quantify ligand-receptor binding affinities in a variety of membrane environments. By detecting minute changes in the refractive index of a solution, BSI allows binding interactions of proteins with their ligands to be measured at picomolar concentrations. Equilibrium binding constants in the micromolar to picomolar range were obtained for small- and large-molecule interactions in both synthetic and cell-derived membranes without the use of labels or supporting substrates. The simple and low-cost hardware, high sensitivity and label-free nature of BSI should make it readily applicable to the study of many membrane-associated proteins of biochemical and pharmacological interest.     

An application of CIFAP for predicting the binding affinity of Chk1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide

Investigation of protein‐ligand interactions obtained from experiments has a crucial part in the design of newly discovered and effective drugs. Analyzing the data extracted from known interactions could help scientists to predict the binding affinities of promising ligands before conducting experiments. The objective of this study is to advance the CIFAP (compressed images for affinity prediction) method, which is relevant to a protein‐ligand model, identifying 2D electrostatic potential images by separating the binding site of protein‐ligand complexes and using the images for predicting the computational affinity information represented by pIC₅₀ values. The CIFAP method has 2 phases, namely, data modeling and prediction. In data modeling phase, the separated 3D structure of the binding pocket with the ligand inside is fitted into an electrostatic potential grid box, which is then compressed through 3 orthogonal directions into three 2D images for each protein‐ligand complex. Sequential floating forward selection technique is performed for acquiring prediction patterns from the images. In the prediction phase, support vector regression (SVR) and partial least squares regression are used for testing the quality of the CIFAP method for predicting the binding affinity of 45 CHK1 inhibitors derived from 2‐aminothiazole‐4‐carboxamide. The results show that the CIFAP method using both support vector regression and partial least squares regression is very effective for predicting the binding affinities of CHK1‐ligand complexes with low‐error values and high correlation. As a future work, the results could be improved by working on the pose of the ligands inside the grid.     

The reactivity of cytochrome c with soft ligands

The spectral changes caused by binding soft ligands to the cytochrome c iron and their correlation to ligand affinities support the hypothesis that the iron—methionine sulfur bond of this heme protein is enhanced by delocalization of the metal l₂, electrons into the empty 3d orbitals of the ligand atom. These findings also explain the unique spectrum of cytochrome c in the far red.