The direct evaluation of dissociation constants (K(D)) from the variation of saturation transfer difference (STD) NMR spectroscopy values with the receptor-ligand ratio is not feasible due to the complex dependence of STD intensities on the spectral properties of the observed signals. Indirect evaluation, by competition experiments, allows the determination of K(D), as long as a ligand of known affinity is available for the protein under study. Herein, we present a novel protocol based on STD NMR spectroscopy for the direct measurements of receptor-ligand dissociation constants (K(D)) from single-ligand titration experiments. The influence of several experimental factors on STD values has been studied in detail, confirming the marked impact on standard determinations of protein-ligand affinities by STD NMR spectroscopy. These factors, namely, STD saturation time, ligand residence time in the complex, and the intensity of the signal, affect the accumulation of saturation in the free ligand by processes closely related to fast protein-ligand rebinding and longitudinal relaxation of the ligand signals. The proposed method avoids the dependence of the magnitudes of ligand STD signals at a given saturation time on spurious factors by constructing the binding isotherms using the initial growth rates of the STD amplification factors, in a similar way to the use of NOE growing rates to estimate cross relaxation rates for distance evaluations. Herein, it is demonstrated that the effects of these factors are cancelled out by analyzing the protein-ligand association curve using STD values at the limit of zero saturation time, when virtually no ligand rebinding or relaxation takes place. The approach is validated for two well-studied protein-ligand systems: the binding of the saccharides GlcNAc and GlcNAcbeta1,4GlcNAc (chitobiose) to the wheat germ agglutinin (WGA) lectin, and the interaction of the amino acid L-tryptophan to bovine serum albumin (BSA). In all cases, the experimental K(D) measured under different experimental conditions converged to the thermodynamic values. The proposed protocol allows accurate determinations of protein-ligand dissociation constants, extending the applicability of the STD NMR spectroscopy for affinity measurements, which is of particular relevance for those proteins for which a ligand of known affinity is not available.
Saturation transfer difference NMR (STD NMR) spectroscopy is one of the most powerful NMR techniques for detection and characterization of transient (fast) receptor-ligand interactions in solution. By observing the signals of a small molecule (ligand) with spectroscopic properties suitable for high-resolution studies, irrespective of receptor size, STD NMR enables quantitative structural and affinity information to be obtained about the molecular recognition process under study. Approximately one decade after its introduction, the technique has reached maturity, and is highly robust and useful. The objective of this article is to review the current status of this powerful technique, with particular emphasis on quantitative applications, within the framework of the (bio-)chemistry of molecular recognition.
This paper presents new structural statistical matrices which are gray level size zone matrix (SZM) texture descriptor variants. The SZM is based on the cooccurrences of size/intensity of each flat zone (connected pixels with the same gray level). The first improvement increases the information processed by merging multiple gray-level quantizations and reduces the required parameter numbers. New improved descriptors were especially designed for supervised cell texture classification. They are illustrated thanks to two different databases built from quantitative cell biology. The second alternative characterizes the DNA organization during the mitosis, according to zone intensities radial distribution. The third variant is a matrix structure generalization for the fibrous texture analysis, by changing the intensity/size pair into the length/orientation pair of each region.
Sialic acid (Neu5Ac) is commonly found in terminal location of colonic mucins glycans where it is a much-coveted nutrient for gut bacteria including Ruminococcus gnavus. R. gnavus is part of Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:
Dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN) and Langerin are C-type lectins of dendritic cells (DCs) that share a specificity for mannose and are involved in pathogen recognition. HIV is known to use DC-SIGN on DCs to facilitate transinfection of T-cells. Langerin, on the contrary, contributes to virus elimination; therefore, the inhibition of this latter receptor is undesired. Glycomimetic molecules targeting DC-SIGN have been reported as promising agents for the inhibition of viral infections and for the modulation of immune responses mediated by DC-SIGN. We show here for the first time that glycomimetics based on a mannose anchor can be tuned to selectively inhibit DC-SIGN over Langerin. Based on structural and binding studies of a mannobioside mimic previously described by us (2), a focused library of derivatives was designed. The optimized synthesis gave fast and efficient access to a group of bis(amides), decorated with an azide-terminated tether allowing further conjugation. SPR inhibition tests showed improvements over the parent pseudomannobioside by a factor of 3-4. A dimeric, macrocyclic structure (11) was also serendipitously obtained, which afforded a 30-fold gain over the starting compound (2). The same ligands were tested against Langerin and found to exhibit high selectivity towards DC-SIGN. Structural studies using saturation transfer difference NMR spectroscopy (STD-NMR) were performed to analyze the binding mode of one representative library member with DC-SIGN. Despite the overlap of some signals, it was established that the new ligand interacts with the protein in the same fashion as the parent pseudodisaccharide. The two aromatic amide moieties showed relatively high saturation in the STD spectrum, which suggests that the improved potency of the bis(amides) over the parent dimethyl ester can be attributed to lipophilic interactions between the aromatic groups of the ligand and the binding site of DC-SIGN.
The bacterial effector proteins SseK and NleB glycosylate host proteins on arginine residues, leading to reduced NF-κB-dependent responses to infection. Salmonella SseK1 and SseK2 are E. coli NleB1 orthologs that behave as NleB1-like GTs, although they differ in protein substrate specificity. Here we report that these enzymes are retaining glycosyltransferases composed of a helix-loop-helix (HLH) domain, a lid domain, and a catalytic domain. A conserved HEN motif (His-Glu-Asn) in the active site is important for enzyme catalysis and bacterial virulence. We observe differences between SseK1 and SseK2 in interactions with substrates and identify substrate residues that are critical for enzyme recognition. Long Molecular Dynamics simulations suggest that the HLH domain determines substrate specificity and the lid-domain regulates the opening of the active site. Overall, our data suggest a front-face SNi mechanism, explain differences in activities among these effectors, and have implications for future drug development against enteric pathogens.
We present an automatic non-supervised set of algorithms for a fast and accurate spot data extraction from DNA microarrays using morphological operators which are robust to both intensity variation and artefacts. The approach can be summarised as follows. Initially, a gridding algorithm yields the automatic segmentation of the microarray image into spot quadrants which are later individually analysed. Then the analysis of the spot quadrant images is achieved in five steps. First, a pre-quantification, the spot size distribution law is calculated. Second, the background noise extraction is performed using a morphological filtering by area. Third, an orthogonal grid provides the first approach to the spot locus. Fourth, the spot segmentation or spot boundaries definition is carried out using the watershed transformation. And fifth, the outline of detected spots allows the signal quantification or spot intensities extraction; in this respect, a noise model has been investigated. The performance of the algorithm has been compared with two packages: ScanAlyze and Genepix, showing its robustness and precision.
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