Antibody-protein Interactions Research Articles

Design And Evaluating The Efficacy Of Novel Antibodies Enhancing Binding On CTLA-4 And PD-1 Immune Checkpoints

Immune checkpoint proteins, including CTLA-4 and PD-1, have emerged as promising targets for cancer immunotherapy due to their vital role in immune regulation. In this comprehensive study, we conducted a thorough analysis of antibody-protein interactions by employing structural analysis, mutational studies, and antibody-antigen docking simulations. Our findings revealed that antibodies 1 and 2 exhibited strong binding affinities towards CTLA-4 and PD-1 proteins, respectively. Further analysis through alanine scanning identified specific residues, namely Tyr91 on antibody 1, along with Asn31 and Asp96 on antibody 2, as potential mutation sites. Introducing these mutations resulted in the generation of two novel antibodies, 1a, 2a and 2b, which displayed enhanced binding affinity towards their respective target proteins. With their improved binding capabilities, these novel antibodies hold tremendous promise for enhancing the effectiveness of antibody-based therapies designed to target immune checkpoints in cancer treatment. The ultimate objective is to significantly improve the health outcomes of patients by leveraging the potential of these novel antibodies.

Antibody Binding Captures High Energy State of an Antigen: The Case of Nsp1 SARS-CoV-2 as Revealed by Hydrogen-Deuterium Exchange Mass Spectrometry.

We describe an investigation using structural mass spectrometry (MS) of the impact of two antibodies, 15497 and 15498, binding the highly flexible SARS-CoV-2 Nsp1 protein. We determined the epitopes and paratopes involved in the antibody-protein interactions by using hydrogen-deuterium exchange MS (HDX-MS). Notably, the Fab (Fragment antigen binding) for antibody 15498 captured a high energy form of the antigen exhibiting significant conformational changes that added flexibility over most of the Nsp1 protein. The Fab for antibody 15497, however, showed usual antigen binding behavior, revealing local changes presumably including the binding site. These findings illustrate an unusual antibody effect on an antigen and are consistent with the dynamic nature of the Nsp1 protein. Our studies suggest that this interaction capitalizes on the high flexibility of Nsp1 to undergo conformational change and be trapped in a higher energy state by binding with a specific antibody.

Developing similarity matrices for antibody-protein binding interactions.

The inventions of AlphaFold and RoseTTAFold are revolutionizing computational protein science due to their abilities to reliably predict protein structures. Their unprecedented successes are due to the parallel consideration of several types of information, one of which is protein sequence similarity information. Sequence homology has been studied for many decades and depends on similarity matrices to define how similar or different protein sequences are to one another. A natural extension of predicting protein structures is predicting the interactions between proteins, but similarity matrices for protein-protein interactions do not exist. This study conducted a mutational analysis of 384 non-redundant antibody-protein antigen complexes to calculate antibody-protein interaction similarity matrices. Every important residue in each antibody and each antigen was mutated to each of the other 19 commonly occurring amino acids and the percentage changes in interaction energies were calculated using three force fields: CHARMM, Amber, and Rosetta. The data were used to construct six interaction similarity matrices, one for antibodies and another for antigens using each force field. The matrices exhibited both commonalities, such as mutations of aromatic and charged residues being the most detrimental, and differences, such as Rosetta predicting mutations of serines to be better tolerated than either Amber or CHARMM. A comparison to nine previously published similarity matrices for protein sequences revealed that the new interaction matrices are more similar to one another than they are to any of the previous matrices. The created similarity matrices can be used in force field specific applications to help guide decisions regarding mutations in protein-protein binding interfaces.

Physicochemical determinants of antibody-protein interactions.

Antibodies are specialized proteins generated by immune system for high specificity and affinity binding to target antigens. Because of their essential roles in immune system, antibodies have been successfully developed and engineered as biopharmaceuticals for treatment of various diseases. Analysis of antibody-protein interactions is always required to get detailed information on effectivity of such antibody-based therapeutics. Although physicochemical rules cannot be generalized for every antibody-protein interaction, there are some features which should be taken into account during antibody development and engineering efforts. In this chapter, physicochemical analysis of antibody paratope-protein epitope interactions will be discussed to highlight important characteristics. First, paratope and non-paratope regions of antibodies will be described and important roles of these regions on binding and biophysical features of antibodies will be discussed. Then, general features of epitope regions of protein antigens will be introduced along with several computational/experimental tools to identify them. Lastly, a rising star of antibody biopharmaceuticals, nanobodies, will be described to show importance of next-generation antibody fragment based biopharmaceuticals in drug development.

Design and evaluation of a multiplexed angular-scanning surface plasmon resonance system employing line-laser optics and CCD detection in combination with multi-ligand sensor chips

An angle-scanning Kretschmann configuration SPR instrument allowing multiplexed analysis is presented. Laser light was guided through optics that converted the collimated light into a line-shaped beam, which was directed to a prism, illuminating the gold sensor surface over a 1 × 10 mm area. The reflected light was led to a CCD detector providing simultaneous readout of individual analysis spots along the laser line at a selected angle (fixed-angle detection) or in scanning-angle mode (width of 35°). Full SPR curve could be measured every 3.6 s for each illuminated spot on the sensor surface. Two in-house manufactured flow cell designs were used for evaluating multiplexed angular-scanning SPR. The first comprised six parallel channels with the laser line perpendicular to the flow direction in order to allow interrogation of the sensor surface in the six channels. Refractive index changes by varying solution composition, and adsorption of different concentrations of albumin to the sensor surface could be correctly monitored simultaneously in each of the channels. In the second flow-cell design the laser line was coinciding with the flow path, allowing recording of SPR curves along a 10-mm length of the sensor surface. Adsorption of layers of positively and negatively charged polyelectrolytes could be consistently measured for sixteen selected positions along the channel. As a proof of principle, several target proteins were immobilized on different positions along the sensor and the binding of various antibodies with these proteins was monitored simultaneously, showing excellent selectivity and reproducibility for probing antibody-protein interactions in a multiplexed fashion.

In Silico Prediction of Linear B-Cell Epitopes on Proteins.

Antibody-protein interactions play a critical role in the humoral immune response. B-cells secrete antibodies, which bind antigens (e.g., cell surface proteins of pathogens). The specific parts of antigens that are recognized by antibodies are called B-cell epitopes. These epitopes can be linear, corresponding to a contiguous amino acid sequence fragment of an antigen, or conformational, in which residues critical for recognition may not be contiguous in the primary sequence, but are in close proximity within the folded protein 3D structure.Identification of B-cell epitopes in target antigens is one of the key steps in epitope-driven subunit vaccine design, immunodiagnostic tests, and antibody production. In silico bioinformatics techniques offer a promising and cost-effective approach for identifying potential B-cell epitopes in a target vaccine candidate. In this chapter, we show how to utilize online B-cell epitope prediction tools to identify linear B-cell epitopes from the primary amino acid sequence of proteins.

Origins of specificity and affinity in antibody-protein interactions.

Natural antibodies are frequently elicited to recognize diverse protein surfaces, where the sequence features of the epitopes are frequently indistinguishable from those of nonepitope protein surfaces. It is not clearly understood how the paratopes are able to recognize sequence-wise featureless epitopes and how a natural antibody repertoire with limited variants can recognize seemingly unlimited protein antigens foreign to the host immune system. In this work, computational methods were used to predict the functional paratopes with the 3D antibody variable domain structure as input. The predicted functional paratopes were reasonably validated by the hot spot residues known from experimental alanine scanning measurements. The functional paratope (hot spot) predictions on a set of 111 antibody-antigen complex structures indicate that aromatic, mostly tyrosyl, side chains constitute the major part of the predicted functional paratopes, with short-chain hydrophilic residues forming the minor portion of the predicted functional paratopes. These aromatic side chains interact mostly with the epitope main chain atoms and side-chain carbons. The functional paratopes are surrounded by favorable polar atomistic contacts in the structural paratope-epitope interfaces; more that 80% these polar contacts are electrostatically favorable and about 40% of these polar contacts form direct hydrogen bonds across the interfaces. These results indicate that a limited repertoire of antibodies bearing paratopes with diverse structural contours enriched with aromatic side chains among short-chain hydrophilic residues can recognize all sorts of protein surfaces, because the determinants for antibody recognition are common physicochemical features ubiquitously distributed over all protein surfaces.

Side chain requirements for affinity and specificity in D5, an HIV-1 antibody derived from the VH1-69 germline segment

BackgroundAnalysis of factors contributing to high affinity antibody-protein interactions provides insight into natural antibody evolution, and guides the design of antibodies with new or enhanced function. We previously studied the interaction between antibody D5 and its target, a designed protein based on HIV-1 gp41 known as 5-Helix, as a model system [Da Silva, G. F.; Harrison, J. S.; Lai, J. R., Biochemistry, 2010, 49, 5464–5472]. Antibody D5 represents an interesting case study because it is derived from the VH1-69 germline segment; this germline segment is characterized by a hydrophobic second heavy chain complementarity determining region (HCDR2) that constitutes the major functional paratope in D5 and several antibodies derived from the same progenitor.ResultsHere we explore side chain requirements for affinity and specificity in D5 using phage display. Two D5-based libraries were prepared that contained diversity in all three light chain complementarity determining regions (LCDRs 1–3), and in the third HCDR (HCDR3). The first library allowed residues to vary among a restricted set of six amino acids (Tyr/Ala/Asp/Ser/His/Pro; D5-Lib-I). The second library was designed based on a survey of existing VH1-69 antibody structures (D5-Lib-II). Both libraries were subjected to multiple rounds of selection against 5-Helix, and individual clones characterized. We found that selectants from D5-Lib-I generally had moderate affinity and specificity, while many clones from D5-Lib-II exhibited D5-like properties. Additional analysis of the D5-Lib-II functional population revealed position-specific biases for particular amino acids, many that differed from the identity of those side chains in D5.ConclusionsTogether these results suggest that there is some permissiveness for alternative side chains in the LCDRs and HCDR3 of D5, but that replacement with a minimal set of residues is not tolerated in this scaffold for 5-Helix recognition. This work provides novel information about this high-affinity interaction involving an antibody from the VH1-69 germline segment.

Antigen recognition by antibody C836 through adjustment of VL/VHpacking

C836 is a neutralizing monoclonal antibody to human interleukin IL-13 generated by mouse immunization. The crystal structure of the C836 Fab was determined at 2.5 Å resolution and compared with the IL-13-bound form determined previously. This comparison indicates an induced-fit mechanism of antigen recognition through rigid-body rotation of the V(L) and V(H) domains. The magnitude of this rearrangement is one of the largest observed for antibody-protein interactions.

Tools for enhancement of diagnostic immunoassay applications (65.42)

Abstract Optimization of immunoassay applications is often hampered by issues such as non-specific binding, matrix interferences, destabilization of antibody/antigen interactions, and limited sensitivity. SurModics offers tools to address these problems and provides the framework to develop sensitive, reproducible, and robust immunoassays. Stabilization of antibody-protein interactions is fundamental for achieving a robust and reproducible assay. Novel stabilizer formulations have been developed to provide protein stability in both the dried state as well as in solution. The data presented here show improved stability compared to both common in-house formulations as well as other competitor solutions. Problems with non-specific binding and matrix interferences can cause high background, loss of sensitivity and false positives in many diagnostic applications. These issues were mitigated by use of protein-free blocking solutions, or novel passivating surface chemistry for microarray applications. Data here suggest the TRIDIA™ surface chemistry provides significantly reduced non-specific binding in protein arrays. Shown here are data from a new, protein-free diluent designed to reduce matrix interferences and to be substituted with ease into your existing assay protocol. Whether it is in solution or on a surface, SurModics provides the tools necessary to develop and optimize immunoassays that are sensitive, reproducible, and robust.

Recombinant Surface Proteomics as a Tool to Analyze Humoral Immune Responses in Bovines Infected by Mycoplasma mycoides Subsp. mycoides Small Colony Type

A systematic approach to characterize the surface proteome of Mycoplasma mycoides subspecies mycoides small colony type (M. mycoides SC), the causative agent of contagious bovine pleuropneumonia (CBPP) in cattle, is presented. Humoral immune responses in 242 CBPP-affected cattle and controls were monitored against one-third of the surface proteins of M. mycoides SC in a high throughput magnetic bead-based assay. Initially, 64 surface proteins were selected from the genome sequence of M. mycoides SC and expressed as recombinant proteins in Escherichia coli. Binding of antibodies to each individual protein could then be analyzed simultaneously in minute sample volumes with the Luminex suspension array technology. The assay was optimized on Namibian CBPP-positive sera and Swedish negative controls to allow detection and 20-fold mean signal separation between CBPP-positive and -negative sera. Signals were proven to be protein-specific by inhibition experiments, and results agreed with Western blot experiments. The potential of the assay to monitor IgG, IgM, and IgA responses over time was shown in a proof-of-concept study with 116 sera from eight animals in a CBPP vaccine study. In conclusion, a toolbox with recombinant proteins and a flexible suspension array assay that allows multiplex analysis of humoral immune responses to M. mycoides SC has been created.

Antibody-protein interactions: benchmark datasets and prediction tools evaluation

BackgroundThe ability to predict antibody binding sites (aka antigenic determinants or B-cell epitopes) for a given protein is a precursor to new vaccine design and diagnostics. Among the various methods of B-cell epitope identification X-ray crystallography is one of the most reliable methods. Using these experimental data computational methods exist for B-cell epitope prediction. As the number of structures of antibody-protein complexes grows, further interest in prediction methods using 3D structure is anticipated. This work aims to establish a benchmark for 3D structure-based epitope prediction methods.ResultsTwo B-cell epitope benchmark datasets inferred from the 3D structures of antibody-protein complexes were defined. The first is a dataset of 62 representative 3D structures of protein antigens with inferred structural epitopes. The second is a dataset of 82 structures of antibody-protein complexes containing different structural epitopes. Using these datasets, eight web-servers developed for antibody and protein binding sites prediction have been evaluated. In no method did performance exceed a 40% precision and 46% recall. The values of the area under the receiver operating characteristic curve for the evaluated methods were about 0.6 for ConSurf, DiscoTope, and PPI-PRED methods and above 0.65 but not exceeding 0.70 for protein-protein docking methods when the best of the top ten models for the bound docking were considered; the remaining methods performed close to random. The benchmark datasets are included as a supplement to this paper.ConclusionIt may be possible to improve epitope prediction methods through training on datasets which include only immune epitopes and through utilizing more features characterizing epitopes, for example, the evolutionary conservation score. Notwithstanding, overall poor performance may reflect the generality of antigenicity and hence the inability to decipher B-cell epitopes as an intrinsic feature of the protein. It is an open question as to whether ultimately discriminatory features can be found.

Effect of antibody binding on protein motions studied by hydrogen-exchange labeling and two-dimensional NMR.

We have used hydrogen-exchange labeling detected by 2D NMR to study antibody-protein interactions for two monoclonal antibodies raised against horse cytochrome c. The data show that these antibodies bind mainly to the large 37-59 omega-loop of the cytochrome c molecule. In addition, the results provide some suggestive evidence concerning units of local structural flexibility in cytochrome c.