Computational and statistical study on the molecular interaction between antigen and antibody

Understanding the Specific Implications of Amino Acids in the Antibody Development

As the demand for immunotherapy to treat and manage cancers, infectious diseases and other disorders grows, a comprehensive understanding of amino acids and their intricate role in antibody engineering has become a prime requirement. Naturally produced antibodies may not have the most suitable amino acids at the complementarity determining regions (CDR) and framework regions, for therapeutic purposes. Therefore, to enhance the binding affinity and therapeutic properties of an antibody, the specific impact of certain amino acids on the antibody's architecture must be thoroughly studied. In antibody engineering, it is crucial to identify the key amino acid residues that significantly contribute to improving antibody properties. Therapeutic antibodies with higher binding affinity and improved functionality can be achieved through modifications or substitutions with highly suitable amino acid residues. Here, we have indicated the frequency of amino acids and their association with the binding free energy in CDRs. The review also analyzes the experimental outcome of two studies that reveal the frequency of amino acids in CDRs and provides their significant correlation between the outcomes. Additionally, it discusses the various bond interactions within the antibody structure and antigen binding. A detailed understanding of these amino acid properties should assist in the analysis of antibody sequences and structures needed for designing and enhancing the overall performance of therapeutic antibodies.

Prediction of Paratope-Epitope Pairs Using Convolutional Neural Networks

Antibodies play a central role in the adaptive immune response of vertebrates through the specific recognition of exogenous or endogenous antigens. The rational design of antibodies has a wide range of biotechnological and medical applications, such as in disease diagnosis and treatment. However, there are currently no reliable methods for predicting the antibodies that recognize a specific antigen region (or epitope) and, conversely, epitopes that recognize the binding region of a given antibody (or paratope). To fill this gap, we developed ImaPEp, a machine learning-based tool for predicting the binding probability of paratope-epitope pairs, where the epitope and paratope patches were simplified into interacting two-dimensional patches, which were colored according to the values of selected features, and pixelated. The specific recognition of an epitope image by a paratope image was achieved by using a convolutional neural network-based model, which was trained on a set of two-dimensional paratope-epitope images derived from experimental structures of antibody-antigen complexes. Our method achieves good performances in terms of cross-validation with a balanced accuracy of 0.8. Finally, we showcase examples of application of ImaPep, including extensive screening of large libraries to identify paratope candidates that bind to a selected epitope, and rescoring and refining antibody-antigen docking poses.

Advancement in COVID-19 detection using nanomaterial-based biosensors

Coronavirus disease 2019 (COVID-19) pandemic has exemplified how viral growth and transmission are a significant threat to global biosecurity. The early detection and treatment of viral infections is the top priority to prevent fresh waves and control the pandemic. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified through several conventional molecular methodologies that are time-consuming and require high-skill labor, apparatus, and biochemical reagents but have a low detection accuracy. These bottlenecks hamper conventional methods from resolving the COVID-19 emergency. However, interdisciplinary advances in nanomaterials and biotechnology, such as nanomaterials-based biosensors, have opened new avenues for rapid and ultrasensitive detection of pathogens in the field of healthcare. Many updated nanomaterials-based biosensors, namely electrochemical, field-effect transistor, plasmonic, and colorimetric biosensors, employ nucleic acid and antigen-antibody interactions for SARS-CoV-2 detection in a highly efficient, reliable, sensitive, and rapid manner. This systematic review summarizes the mechanisms and characteristics of nanomaterials-based biosensors for SARS-CoV-2 detection. Moreover, continuing challenges and emerging trends in biosensor development are also discussed.

Antibody CDR amino acids underlying the functionality of antibody repertoires in recognizing diverse protein antigens

Antibodies recognize protein antigens with exquisite specificity in a complex aqueous environment, where interfacial waters are an integral part of the antibody–protein complex interfaces. In this work, we elucidate, with computational analyses, the principles governing the antibodies’ specificity and affinity towards their cognate protein antigens in the presence of explicit interfacial waters. Experimentally, in four model antibody–protein complexes, we compared the contributions of the interaction types in antibody–protein antigen complex interfaces with the antibody variants selected from phage-displayed synthetic antibody libraries. Evidently, the specific interactions involving a subset of aromatic CDR (complementarity determining region) residues largely form the predominant determinant underlying the specificity of the antibody–protein complexes in nature. The interfacial direct/water-mediated hydrogen bonds accompanying the CDR aromatic interactions are optimized locally but contribute little in determining the epitope location. The results provide insights into the phenomenon that natural antibodies with limited sequence and structural variations in an antibody repertoire can recognize seemingly unlimited protein antigens. Our work suggests guidelines in designing functional artificial antibody repertoires with practical applications in developing novel antibody-based therapeutics and diagnostics for treating and preventing human diseases.

Secondary Structure and Conformational Stability of the Antigen Residues Making Contact with Antibodies

Antibodies are crucial biomolecules that bring high therapeutic efficacy in medicine and accurate molecular detection in diagnosis. Many studies have been devoted to analyzing the antigen-antibody interaction from the importance of understanding the antibody recognition mechanism. However, most of the previous studies examined the characteristic of the antibody for interaction. It is also informative to clarify the significant antigen residues contributing to the binding. To characterize the molecular interaction of antigens, we computationally analyzed 350 antigen-antibody complex structures by molecular mechanics (MM) calculations and molecular dynamics (MD) simulations. Based on the MM calculations, the antigen residues contributing to the binding were extracted from all the 350 complexes. The extracted residues are located at the antigen-antibody interface and are responsible for making contact with the antibody. The appearances of the charged polar residues, Asp, Glu, Arg, and Lys, were noticeably large. In contrast, the populations of the hydrophobic residues, Leu, Val, and Ala, were relatively low. The appearance frequencies of the other amino acid residues were almost close to the abundance of general proteins of eukaryotes. The binding score indicated that the hydrophilic interaction was dominant at the antigen-antibody contact instead of the hydrophobic one. The positively charged residues, Arg and Lys, remarkably contributed to the binding compared to the negatively charged ones, Asp and Glu. Considerable contributions were also observed for the noncharged polar residues, Asn and Gln. The analysis of the secondary structures of the extracted antigen residues suggested that there was no marked difference in recognition by antibodies among helix, sheet, turn, and coil. A long helix of the antigen sometimes made contact with antibody complementarity-determining regions, and a large sheet also frequently covered the antibody heavy and light chains. The turn structure was the most popularly observed at the contact with antibody among 350 complexes. Three typical complexes were picked up for each of the four secondary structures. MD simulations were performed to examine the stability of the interfacial structures of the antigens for these 12 complex models. The alterations of secondary structures were monitored through the simulations. The structural fluctuations of the contact residues were low compared with the other domains of antigen molecules. No drastic conversion was observed for every model during the 100 ns simulation. The motions of the interfacial antigen residues were small compared to the other residues on the protein surface. Therefore, diverse molecular conformations are possible for antibody recognition as long as the target areas are polar, nonflexible, and protruding on the protein surface.

Novel allosteric ligands of the angiotensin receptor AT1R as autoantibody blockers

While orthosteric ligands of the angiotensin II (AngII) type 1 receptor (AT1R) are available for clinical and research applications, allosteric ligands are not known for this important G protein-coupled receptor (GPCR). Allosteric ligands are useful tools to modulate receptor pharmacology and subtype selectivity. Here, we report AT1R allosteric ligands for a potential application to block autoimmune antibodies. The epitope of autoantibodies for AT1R is outside the orthosteric pocket in the extracellular loop 2. A molecular dynamics simulation study of AT1R structure reveals the presence of a druggable allosteric pocket encompassing the autoantibody epitope. Small molecule binders were then identified for this pocket using structure-based high-throughput virtual screening. The top 18 hits obtained inhibited the binding of antibody to AT1R and modulated agonist-induced calcium response of AT1R. Two compounds out of 18 studied in detail exerted a negative allosteric modulator effect on the functions of the natural agonist AngII. They blocked antibody-enhanced calcium response and reactive oxygen species production in vascular smooth muscle cells as well as AngII-induced constriction of blood vessels, demonstrating their efficacy in vivo. Our study thus demonstrates the feasibility of discovering inhibitors of the disease-causing autoantibodies for GPCRs. Specifically, for AT1R, we anticipate development of more potent allosteric drug candidates for intervention in autoimmune maladies such as preeclampsia, bilateral adrenal hyperplasia, and the rejection of organ transplants.

Nonspecific Binding-Fundamental Concepts and Consequences for Biosensing Applications

Nature achieves differentiation of specific and nonspecific binding in molecular interactions through precise control of biomolecules in space and time. Artificial systems such as biosensors that rely on distinguishing specific molecular binding events in a sea of nonspecific interactions have struggled to overcome this issue. Despite the numerous technological advancements in biosensor technologies, nonspecific binding has remained a critical bottleneck due to the lack of a fundamental understanding of the phenomenon. To date, the identity, cause, and influence of nonspecific binding remain topics of debate within the scientific community. In this review, we discuss the evolution of the concept of nonspecific binding over the past five decades based upon the thermodynamic, intermolecular, and structural perspectives to provide classification frameworks for biomolecular interactions. Further, we introduce various theoretical models that predict the expected behavior of biosensors in physiologically relevant environments to calculate the theoretical detection limit and to optimize sensor performance. We conclude by discussing existing practical approaches to tackle the nonspecific binding challenge in vitro for biosensing platforms and how we can both address and harness nonspecific interactions for in vivo systems.

Binding characteristics of staphylococcal protein A and streptococcal protein G for fragment crystallizable portion of human immunoglobulin G

In the wide array of physiological processes, protein-protein interactions and their binding are the most basal activities for achieving adequate biological metabolism. Among the studies on binding proteins, the examination of interactions between immunoglobulin G (IgG) and natural immunoglobulin-binding ligands, such as staphylococcal protein A (spA) and streptococcal protein G (spG), is essential in the development of pharmaceutical science, biotechnology, and affinity chromatography. The widespread utilization of IgG-spA/spG binding characteristics has allowed researchers to investigate these molecular interactions. However, the detailed binding strength of each ligand and the corresponding binding mechanisms have yet to be fully investigated. In this study, the authors analyzed the binding strengths of IgG-spA and IgG-spG complexes and identified the mechanisms enabling these bindings using molecular dynamics simulation, steered molecular dynamics, and advanced Poisson-Boltzmann Solver simulations. Based on the presented data, the binding strength of the spA ligand was found to significantly exceed that of the spG ligand. To find out which non-covalent interactions or amino acid sites have a dominant role in the tight binding of these ligands, further detailed analyses of electrostatic interactions, hydrophobic bonding, and binding free energies have been performed. In investigating their binding affinity, a relatively independent and different unbinding mechanism was found in each ligand. These distinctly different mechanisms were observed to be highly correlated to the protein secondary and tertiary structures of spA and spG ligands, as explicated from the perspective of hydrogen bonding.

Analysis of Binding Modes of Antigen-Antibody Complexes by Molecular Mechanics Calculation

Antibodies are one of the most important protein molecules in biopharmaceutics. Due to the recent advance in technology for producing monoclonal antibodies, many structural data are available on the antigen-antibody complexes. To characterize the molecular interaction in antigen-antibody recognition, we computationally analyzed 500 complex structures by molecular mechanics calculations. The presence of Ser and Tyr is markedly large in the complementarity-determining regions (CDRs). Although Ser is abundant in CDRs, its contribution to the binding score is not large. Instead, Tyr, Asp, Glu, and Arg significantly contribute to the molecular interaction from the viewpoint of the binding score. The decomposition of the binding score suggests that the hydrophilic interaction is predominant in all CDRs compared with the hydrophobic one. The contribution of the heavy chain is larger than that of the light chain. In particular, H2 and H3 largely contribute to the binding interaction. Tyr is a main contributing residue both in H2 and H3. The positively charged residue Arg also significantly contributes to the binding score in H3, while the contribution of Lys is small. The appearance of Ser is remarkable in H2, and Asp is abundant in H3. The non-charged polar residues, Thr, Asn, and Gln, appear much in H2, compared to appearing in H3. The negatively charged residues Asp and Glu significantly contribute to the binding score in H3. The contributions of Phe and Trp are not large in spite that the aromatic residues are capable of making the π-π or CH-π interaction. Gly is commonly abundant both in H2 and H3. The average distance of the shortest direct hydrogen bond between the antigen and antibody is longer than that of the hydrogen bonds observed in the complexes between compounds and their target proteins. Therefore, the antigen-antibody interface is not so tight as the compound-target protein interface. The calculation of shape complementarity is consistent with the result of the hydrogen bonds in that the fitness of the antigen-antibody contact is not so high as that of the compound-target protein contact. There exist many water molecules at the antigen-antibody interface. These findings suggest that Tyr, Asp, Glu, and Arg are rich in H3 and work as major contributors for the interaction with the antigen. Ser, Thr, Asn, and Gln are rich in H2 and support the interaction with enhancing molecular fitness. Gly is helpful in increasing flexibility and geometrical diversity. Because the antigen-antibody binding is fundamentally hydrophilic-driven, the non-polar residues are unfavorable for mediating the contact even for the aromatic residues such as Phe and Trp.

Label-free optical antibody testing kit based on a self-assembled whispering-gallery-mode microsphere

The appearance of antibodies in blood is a critical signal to suggest the infection. A rapid and accurate detection method for the antibody is significant to the disease diagnosis, especially for the epidemic. To this end, a highly sensitive whispering-gallery-mode (WGM) optical testing kit is designed and fabricated for detecting the specific immunoglobulin antibodies. The key component of the kit is a silica self-assembled microsphere decorated with the nucleocapsid proteins (N-proteins) of the SARS-CoV-2 virus. After the N-protein antibody immunoglobulin G (N-IgG) and immunoglobulin M (N-IgM) solutions being injected into the kit, the WGM red-shifts due to the antigen-antibody reaction. The wavelength displacement rates are proportional to the concentrations of these two antibodies from 1 to 100 μg/mL. A good specificity of the kit is demonstrated by the nonspecific human immunoglobulin G (H-IgG) and immunoglobulin M (H-IgM).

Solving the α-helix correspondence problem at medium-resolution Cryo-EM maps through modeling and 3D matching

Cryo-electron microscopy (cryo-EM) has recently emerged as a prominent biophysical method for macromolecular structure determination. Many research efforts have been devoted to produce cryo-EM images, density maps, at near-atomic resolution. Despite many advances in technology, the resolution of the generated density maps may not be sufficiently adequate and informative to directly construct the atomic structure of proteins. At medium-resolution (∼4-10 Å), secondary structure elements (α-helices and β-sheets) are discernible, whereas finding the correspondence of secondary structure elements detected in the density map with those on the sequence remains a challenging problem. In this paper, an automatic framework is proposed to solve α-helix correspondence problem in three-dimensional space. Through modeling of the sequence with the aid of a novel strategy, the α-helix correspondence problem is initially transformed into a complete weighted bipartite graph matching problem. An innovative correlation-based scoring function based on a well-known and robust statistical method is proposed for weighting the graph. Moreover, two local optimization algorithms, which are Greedy and Improved Greedy algorithms, have been presented to find α-helix correspondence. A widely used data set including 16 reconstructed and 4 experimental cryo-EM maps were chosen to verify the accuracy and reliability of the proposed automatic method. The experimental results demonstrate that the automatic method is highly efficient (86.25% accuracy), robust (11.3% error rate), fast (∼1.4 s), and works independently from cryo-EM skeleton.

Understanding microcystin-LR antibody binding interactions using in silico docking and in vitro mutagenesis

Microcystins (MCs) are a group of highly potent cyanotoxins that are becoming more widely distributed due to increased global temperatures and climate change. Microcystin-leucine-arginine (MC-LR) is the most potent and most common variant, with a guideline limit of 1 μg/l in drinking water. We previously developed a novel avian single-chain fragment variable (scFv), designated 2G1, for use in an optical-planar waveguide detection system for microcystin determination. This current work investigates interactions between 2G1 and MC-LR at the molecular level through modelling with an avian antibody template and molecular docking by AutoDock Vina to identify key amino acid (AA) residues involved. These potential AA interactions were investigated in vitro by targeted mutagenesis, specifically, by alanine scanning mutations. Glutamic acid (E) was found to play a critical role in the 2G1-MC-LR binding interaction, with the heavy chain glutamic acid (E) 102 (H-E102) forming direct bonds with the arginine (R) residue of MC-LR. In addition, alanine mutation of light chain residue aspartic acid 57 (L-D57) led to an improvement in antigen-binding observed using enzyme-linked immunosorbent assay (ELISA), and was confirmed by surface plasmon resonance (SPR). This work will contribute to improving the binding of recombinant anti-MC-LR to its antigen and aid in the development of a higher sensitivity harmful algal toxin diagnostic.

Antibody-mediated biorecognition of myelin oligodendrocyte glycoprotein: computational evidence of demyelination-related epitopes

Antigen-antibody interaction is crucial in autoimmune disease pathogenesis, as multiple sclerosis and neuromyelitis optica. Given that, autoantibodies are essential biomolecules, of which the myelin oligodendrocyte glycoprotein (MOG) can figure as a target. Here we combined Molecular Dynamics (MD), Steered Molecular Dynamics (SMD), and Atomic Force Microscope (AFM) to detail MOG recognition by its specific antibody. The complex model consisted of the MOG external domain interacting with an experimental anti-MOG antibody from the Protein Data Bank (1PKQ). Computational data demonstrated thirteen MOG residues with a robust contribution to the antigen-antibody interaction. Comprising five of the thirteen anchor residues (ASP₁₀₂, HIS₁₀₃, SER₁₀₄, TYR₁₀₅, and GLN₁₀₆), the well-known MOG_92–106 peptide in complex with the anti-MOG was analysed by AFM and SMD. These analyses evidenced similar force values of 780 pN and 765 pN for computational and experimental MOG_92–106 and anti-MOG detachment, respectively. MOG_92–106 was responsible for 75% of the total force measured between MOG external domain and anti-MOG, holding the interaction with the antibody. The antigen-antibody binding was confirmed by Surface Plasmon Resonance (SPR) measurements. Combined approaches presented here can conveniently be adjusted to detail novel molecules in diseases research. This can optimize pre-clinical steps, guiding experiments, reducing costs, and animal model usage.

Rapid quantitative protein detection by light transmission spectroscopy

Rapid, sensitive, and quantitative protein detection is critical for many applications in medicine, environmental monitoring, and the food industry. Advancements in detection of proteins include the use of antigen-antibody binding; however, many current methods are time-consuming and have limiting factors such as low sensitivity and the inability to provide absolute values. We present a new high-throughput method for protein detection using light transmission spectroscopy (LTS), which can quantify and size nanoparticles in fluid suspension. LTS can quantify proteins directly and target specific proteins through antigen-antibody binding. This work shows that LTS can distinguish between and quantify bovine serum albumin, its antibody, and the BSA + Ab complex and determine BSA protein concentrations down to 5 μg/mL. We use both Mie and discrete dipole approximation models to provide geometric insight into the binding process.

Mechanism of Hormone Peptide Activation of a GPCR: Angiotensin II Activated State of AT1R Initiated by van der Waals Attraction

We present a succession of structural changes involved in hormone peptide activation of a prototypical GPCR. Microsecond molecular dynamics simulation generated conformational ensembles reveal propagation of structural changes through key "microswitches" within human AT₁R bound to native hormone. The endocrine octa-peptide angiotensin II (AngII) activates AT₁R signaling in our bodies which maintains physiological blood pressure, electrolyte balance, and cardiovascular homeostasis. Excessive AT₁R activation is associated with pathogenesis of hypertension and cardiovascular diseases which are treated by sartan drugs. The mechanism of AT₁R inhibition by sartans has been elucidated by 2.8 Å X-ray structures, mutagenesis, and computational analyses. Yet, the mechanism of AT₁R activation by AngII is unclear. The current study delineates an activation scheme initiated by AngII binding. A van der Waals "grasp" interaction between Phe8^AngII with Ile288^7.39 in AT₁R induced mechanical strain pulling Tyr292^7.43 and breakage of critical interhelical H-bonds, first between Tyr292^7.43 and Val108^3.32 and second between Asn111^3.35 and Asn295^7.46. Subsequently changes are observed in conserved microswitches DRY^TM3, Yx7K(R)^TM5, CWxP^TM6, and NPxxY^TM7 in AT₁R. Activating the microswitches in the intracellular region of AT₁R may trigger formation of the G-protein binding pocket as well as exposure of helix-8 to cytoplasm. Thus, the active-like conformation of AT₁R is initiated by the van der Waals interaction of Phe8^AngII with Ile288^7.39, followed by systematic reorganization of critical interhelical H-bonds and activation of microswitches.

The effects of antigen size, binding site valency, and flexibility on fab-antigen binding near solid surfaces

Next generation antibody microarray devices have the potential to outperform current molecular detection methods and realize new applications in medicine, scientific research, and national defense. However, antibody microarrays, or arrays of antibody fragments ("fabs"), continue to evade mainstream use in part due to persistent reliability problems despite improvements to substrate design and protein immobilization strategies. Other factors could be disrupting microarray performance, including effects resulting from antigen characteristics. Target molecules embody a wide range of sizes, shapes, number of epitopes, epitope accessibility, and other physical and chemical properties. As a result, it may not be ideal for microarray designs to utilize the same substrate or immobilization strategy for all of the capture molecules. This study investigates how three antigen properties, such as size, binding site valency, and molecular flexibility, affect fab binding. The work uses an advanced, experimentally validated, coarse-grain model and umbrella sampling to calculate the free energy of ligand binding and how this energy landscape is different on the surface compared to in the bulk. The results confirm that large antigens interact differently with immobilized fabs compared to smaller antigens. Analysis of the results shows that despite these differences, tethering fabs in an upright orientation on hydrophilic surfaces is the best configuration for antibody microarrays.

Divergent Spatiotemporal Interaction of Angiotensin Receptor Blocking Drugs with Angiotensin Type 1 Receptor

Crystal structures of the human angiotensin II type 1 receptor (AT₁R) complex with the antihypertensive agent ZD7155 (PDB id: 4YAY ) and the blood pressure medication Benicar (PDB id: 4ZUD ) showed that binding poses of both antagonists are similar. This finding implies that clinically used angiotensin receptor blocking (ARB) drugs may interact in a similar fashion. However, clinically observed differences in pharmacological and therapeutic efficacies of ARBs lead to the question of whether the dynamic interactions of AT₁R with ARBs vary. To address this, we performed induced-fit docking (IFD) of eight clinically used ARBs to AT₁R followed by 200 ns molecular dynamic (MD) simulation. The experimental K_i values for ARBs correlated remarkably well with calculated free energy with R² = 0.95 and 0.70 for AT₁R-ARB models generated respectively by IFD and MD simulation. The eight ARB-AT₁R complexes share a common set of binding residues. In addition, MD simulation results validated by mutagenesis data discovered distinctive spatiotemporal interactions that display unique bonding between an individual ARB and AT₁R. These findings provide a reasonably broader picture reconciling the structure-based observations with clinical studies reporting efficacy variations for ARBs. The unique differences unraveled for ARBs in this study will be useful for structure-based design of the next generation of more potent and selective ARBs.

Variable Regions of Antibodies and T-Cell Receptors May Not Be Sufficient in Molecular Simulations Investigating Binding

Antibodies and T-cell receptors are important proteins of the immune system that share similar structures. Both contain variable and constant regions. Insight into the dynamics of their binding can be provided by computational simulations. For these simulations the constant regions are often removed to save runtime as binding occurs in the variable regions. Here we present the first study to investigate the effect of removing the constant regions from antibodies and T-cell receptors on such simulations. We performed simulations of an antibody/antigen and T-cell receptor/MHC system with and without constant regions using 10 replicas of 100 ns of each of the four setups. We found that simulations without constant regions show significantly different behavior compared to simulations with constant regions. If the constant regions are not included in the simulations alterations in the binding interface hydrogen bonds and even partial unbinding can occur. These results indicate that constant regions should be included in antibody and T-cell receptor simulations for reliable conclusions to be drawn.