Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Effect of electrolytes and of distilled water on antigen-antibody complexes.

ABSTRACT: Specific immune precipitates dissolve in concentrated solutions of alkali-metal halides, and of alkaline-earth-metal halides and thiocyanates. The quantity of protein dissolved depends on the nature of the antigen-antibody system, on the proportion of the antigen in the precipitate, and on the avidity of the antibody. The extent of solubilization is a function of the temperature, of the volume of solution used and of the concentration of the ions in the solution, and also depends on the nature of these ions. The dissolving power of bivalent cations is greater than that of monovalent ones, and is as follows: Mg(2+)[unk]Ba(2+)[unk]Ca(2+)[unk]Sr(2+). Antigen-antibody complexes and free antibodies, but no free antigen, are detected in supernatants of specific precipitates dissolved in solutions of electrolytes of low ionic strength. Antigen-antibody complexes, free antibodies and also free antigen are detected in supernatants of specific precipitates dissolved in solutions of electrolytes of high ionic strength. Comparable results are obtained when the electrolyte solutions are studied for their effect on the bonds formed between an antibody and its corresponding immunosorbent. Moreover, in the latter case, 50% of the fixed antibodies could be recovered by elution with distilled water.

SUBMITTER: Ternynck T

PROVIDER: S-EPMC1178053 | biostudies-other | 1971 Nov

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Similar Datasets

Direct-MS analysis of antibody-antigen complexes.

Project description:In recent decades, antibodies (Abs) have attracted the attention of academia and the biopharmaceutical industry due to their therapeutic properties and versatility in binding a vast spectrum of antigens. Different engineering strategies have been developed for optimizing Ab specificity, efficacy, affinity, stability and production, enabling systematic screening and analysis procedures for selecting lead candidates. This quality assessment is critical but usually demands time-consuming and labor-intensive purification procedures. Here, we harnessed the direct-mass spectrometry (direct-MS) approach, in which the analysis is carried out directly from the crude growth media, for the rapid, structural characterization of designed Abs. We demonstrate that properties such as stability, specificity and interactions with antigens can be defined, without the need for prior purification.

| S-EPMC8595693 | biostudies-literature

Antibody Specific B-Cell Epitope Predictions: Leveraging Information From Antibody-Antigen Protein Complexes.

Project description:B-cells can neutralize pathogenic molecules by targeting them with extreme specificity using receptors secreted or expressed on their surface (antibodies). This is achieved via molecular interactions between the paratope (i.e., the antibody residues involved in the binding) and the interacting region (epitope) of its target molecule (antigen). Discerning the rules that define this specificity would have profound implications for our understanding of humoral immunogenicity and its applications. The aim of this work is to produce improved, antibody-specific epitope predictions by exploiting features derived from the antigens and their cognate antibodies structures, and combining them using statistical and machine learning algorithms. We have identified several geometric and physicochemical features that are correlated in interacting paratopes and epitopes, used them to develop a Monte Carlo algorithm to generate putative epitopes-paratope pairs, and train a machine-learning model to score them. We show that, by including the structural and physicochemical properties of the paratope, we improve the prediction of the target of a given B-cell receptor. Moreover, we demonstrate a gain in predictive power both in terms of identifying the cognate antigen target for a given antibody and the antibody target for a given antigen, exceeding the results of other available tools.

| S-EPMC6399414 | biostudies-literature

Promoting crystallization of antibody-antigen complexes via microseed matrix screening.

Project description:The application of microseed matrix screening to the crystallization of antibody-antigen complexes is described for a set of antibodies that include mouse anti-IL-13 antibody C836, its humanized version H2L6 and an affinity-matured variant of H2L6, M1295. The Fab fragments of these antibodies were crystallized in complex with the antigen human IL-13. The initial crystallization screening for each of the three complexes included 192 conditions. Only one hit was observed for H2L6 and none were observed for the other two complexes. Matrix self-microseeding using these microcrystals yielded multiple hits under various conditions that were further optimized to grow diffraction-quality H2L6 crystals. The same H2L6 seeds were also successfully used to promote crystallization of the other two complexes. The M1295 crystals appeared to be isomorphous to those of H2L6, whereas the C836 crystals were in a different crystal form. These results are consistent with the concept that the conditions that are best for crystal growth may be different from those that favor nucleation. Microseed matrix screening using either a self-seeding or cross-seeding approach proved to be a fast, robust and reliable method not only for the refinement of crystallization conditions but also to promote crystal nucleation and increase the hit rate.

| S-EPMC2917276 | biostudies-literature

The Allosteric Effect in Antibody-Antigen Recognition.

Project description:We studied the molecular details of the recognition of antigens by the variable domain of their cognate antibodies in as well as those elicited by the constant domains, which do not directly interact with antigens. Such effects are difficult to study experimentally; however, molecular dynamics simulations and subsequent residue interaction network analysis provide insight into the allosteric communication between the antigen-binding CDR region and the constant domain. We performed MD simulations of the complex of Fab and prion-associated peptide in the apo and bound forms and follow the conformational changes in the antibody and cross-talk between its subunits and with antigens. These protocols could be generally applied for studies of other antigens-antibody recognition systems.

| S-EPMC10802915 | biostudies-literature

Structure of water-in-salt and water-in-bisalt electrolytes.

Project description:We report a systematic diffraction study of two "water-in-salt" electrolytes and a "water-in-bisalt" electrolyte combining high-energy X-ray diffraction (HEXRD) with polarized and unpolarized neutron diffraction (ND) on both H2O and D2O solutions. The measurements provide three independent combinations of correlations between the different pairs of atom types that reveal the short- and intermediate-range order in considerable detail. The ND interference functions show pronounced peaks around a scattering vector Q ∼ 0.5 Å-1 that change dramatically with composition, indicating significant rearrangements of the water network on a length scale around 12 Å. The experimental results are compared with two sets of Molecular Dynamics (MD) simulations, one including polarization effects and the other based on a non-polarizable force field. The two simulations reproduce the general shapes of the experimental structure factors and their changes with concentration, but differ in many detailed respects, suggesting ways in which their force fields might be modified to better represent the actual systems.

| S-EPMC9445817 | biostudies-literature

Bound water molecules and conformational stabilization help mediate an antigen-antibody association.

Project description:We report the three-dimensional structures, at 1.8-A resolution, of the Fv fragment of the anti-hen egg white lysozyme antibody D1.3 in its free and antigen-bound forms. These structures reveal a role for solvent molecules in stabilizing the complex and provide a molecular basis for understanding the thermodynamic forces which drive the association reaction. Four water molecules are buried and others form a hydrogen-bonded network around the interface, bridging antigen and antibody. Comparison of the structures of free and bound Fv fragment of D1.3 reveals that several of the ordered water molecules in the free antibody combining site are retained and that additional water molecules link antigen and antibody upon complex formation. This solvation of the complex should weaken the hydrophobic effect, and the resulting large number of solvent-mediated hydrogen bonds, in conjunction with direct protein-protein interactions, should generate a significant enthalpic component. Furthermore, a stabilization of the relative mobilities of the antibody heavy- and light-chain variable domains and of that of the third complementarity-determining loop of the heavy chain seen in the complex should generate a negative entropic contribution opposing the enthalpic and the hydrophobic (solvent entropy) effects. This structural analysis is consistent with measurements of enthalpy and entropy changes by titration calorimetry, which show that enthalpy drives the antigen-antibody reaction. Thus, the main forces stabilizing the complex arise from antigen-antibody hydrogen bonding, van der Waals interactions, enthalpy of hydration, and conformational stabilization rather than solvent entropy (hydrophobic) effects.

| S-EPMC521459 | biostudies-other

Computational docking of antibody-antigen complexes, opportunities and pitfalls illustrated by influenza hemagglutinin.

Project description:Antibodies play an increasingly important role in both basic research and the pharmaceutical industry. Since their efficiency depends, in ultimate analysis, on their atomic interactions with an antigen, studying such interactions is important to understand how they function and, in the long run, to design new molecules with desired properties. Computational docking, the process of predicting the conformation of a complex from its separated components, is emerging as a fast and affordable technique for the structural characterization of antibody-antigen complexes. In this manuscript, we first describe the different computational strategies for the modeling of antibodies and docking of their complexes, and then predict the binding of two antibodies to the stalk region of influenza hemagglutinin, an important pharmaceutical target. The purpose is two-fold: on a general note, we want to illustrate the advantages and pitfalls of computational docking with a practical example, using different approaches and comparing the results to known experimental structures. On a more specific note, we want to assess if docking can be successful in characterizing the binding to the same influenza epitope of other antibodies with unknown structure, which has practical relevance for pharmaceutical and biological research. The paper clearly shows that some of the computational docking predictions can be very accurate, but the algorithm often fails to discriminate them from inaccurate solutions. It is of paramount importance, therefore, to use rapidly obtained experimental data to validate the computational results.

| S-EPMC3039950 | biostudies-literature

Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server.

Project description:MOTIVATION: Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode. RESULTS: In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen. AVAILABILITY: http://www.biocomputing.it/proABC. CONTACT: anna.tramontano@uniroma1.it or paolo.marcatili@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

| S-EPMC3753563 | biostudies-literature

Characterization of Monoclonal Antibody-Protein Antigen Complexes Using Small-Angle Scattering and Molecular Modeling.

Project description:The determination of monoclonal antibody interactions with protein antigens in solution can lead to important insights guiding physical characterization and molecular engineering of therapeutic targets. We used small-angle scattering (SAS) combined with size-exclusion multi-angle light scattering high-performance liquid chromatography to obtain monodisperse samples with defined stoichiometry to study an anti-streptavidin monoclonal antibody interacting with tetrameric streptavidin. Ensembles of structures with both monodentate and bidentate antibody-antigen complexes were generated using molecular docking protocols and molecular simulations. By comparing theoretical SAS profiles to the experimental data it was determined that the primary component(s) were compact monodentate and/or bidentate complexes. SAS profiles of extended monodentate complexes were not consistent with the experimental data. These results highlight the capability for determining the shape of monoclonal antibody-antigen complexes in solution using SAS data and physics-based molecular modeling.

| S-EPMC6197476 | biostudies-literature

Relative energies of binding for antibody-carbohydrate-antigen complexes computed from free-energy simulations.

Project description:Free-energy perturbation (FEP) simulations have been applied to a series of analogues of the natural trisaccharide epitope of Salmonella serotype B bound to a fragment of the monoclonal anti-Salmonella antibody Se155-4. This system was selected in order to assess the ability of free-energy perturbation (FEP) simulations to predict carbohydrate-protein interaction energies. The ultimate goal is to use FEP simulations to aid in the design of synthetic high affinity ligands for carbohydrate-binding proteins. The molecular dynamics (MD) simulations were performed in the explicit presence of water molecules, at room temperature. The AMBER force field, with the GLYCAM parameter set for oligosaccharides, was employed. In contrast to many modeling protocols, FEP simulations are capable of including the effects of entropy, arising from differential ligand flexibilities and solvation properties. The experimental binding affinities are all close in value, resulting in small relative free energies of binding. Many of the DeltaDeltaG values are on the order of 0-1 kcal mol(-1), making their accurate calculation particularly challenging. The simulations were shown to reasonably reproduce the known geometries of the ligands and the ligand-protein complexes. A model for the conformational behavior of the unbound antigen is proposed that is consistent with the reported NMR data. The best agreement with experiment was obtained when histidine 97H was treated as fully protonated, for which the relative binding energies were predicted to well within 1 kcal mol(-1). To our knowledge this is the first report of FEP simulations applied to an oligosaccharide-protein complex.

| S-EPMC1764640 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data