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

Epitope and Paratope Mapping of a SUMO-Remnant Antibody Using Cross-Linking Mass Spectrometry and Molecular Docking

The small ubiquitin-like modifier (SUMO) is an important post-translational modification that regulates the function of various proteins essential for DNA damage repair, genome integrity, and cell homeostasis. To identify protein SUMOylation effectively, an enrichment step is necessary, often requiring exogenous gene expression in cells and immunoaffinity purification of SUMO-remnant peptides following tryptic digestion. Previously, an antibody was developed to enrich tryptic peptides containing the remnant NQTGG on the receptor lysine, although the specifics of the structural interaction motif remained unclear. This study integrates de novo sequencing, intact mass spectrometry, cross-linking mass spectrometry, and molecular docking to elucidate the structural interaction motifs of a SUMO-remnant antibody. Additional cross-linking experiments were performed using SUMOylated peptides and high-field asymmetric waveform ion mobility spectrometry (FAIMS) to enhance the sensitivity and confirm interactions at the paratope interface. This study establishes a robust framework for characterizing antibody-antigen interactions, offering valuable insights into the structural basis of SUMO-remnant peptide recognition.

Amino acids characterization based on frequency and interaction analysis in human antigen-antibody complexes from Thera-SAbDab

BackgroundAntibodies are composed of light and heavy chains, both of which have constant and variable regions. The diversity, specific binding ability and therapeutic potential of antibodies are determined by hypervariable loops called complementarity-determining regions (CDRs), with the other regions being the framework regions.ObjectiveTo investigate the key amino acid patterns in various antibody regions in the human therapeutic antigen-antibody (Ag-Ab) complexes collected from the Thera-SAbDab database.MethodThe study focuses on identifying the amino acid frequency, diversity index in CDRs, paratope-epitope amino acid interactions, amino acid bond formation frequency, and bond types among selected therapeutic Ag-Ab complexes.ResultsThe results revealed that Ser is highly distributed in the overall light chain CDRs while Gly is highly distributed in the heavy chain CDRs. CDR profiling analysis indicated that the average amino acid diversity in heavy chain CDRs is 60% to 70%, while in the light chain, it is 50% to 60%. Aromatic residues such as Tyr, Trp and Phe are the top contributors to these paratope-epitope interactions in the light and heavy chains. Moreover, we examined the frequency of amino acids in light and heavy chains of Ag-Ab complexes. Importantly, the outcome of this study leverages the in depth analysis on single residues, dipeptides, and tripeptides for the therapeutic Ag-Ab complexes.ConclusionWe conclude that the amino acid frequency and interaction analysis centered on therapeutic Ag-Ab complexes will benefit antibody engineering parameters such as antibody design, optimization, affinity maturation, and overall antibody development.

Amino Acids Frequency and Interaction Trends: Comprehensive Analysis of Experimentally Validated Viral Antigen-Antibody Complexes

Antibodies have specific binding capabilities and therapeutic potential for treating various diseases, including viral infections. The amino acid composition of the hypervariable complementarity determining regions (CDR) loops and the framework regions (FR) are the determining factors for the affinity and therapeutic efficacy of the antibodies. In this study selected and curated, 77 viral antigen-human antibody complexes from Protein data bank from the Thera-SAbdab database were analyzed. The results revealed diversity indices within specific CDR regions, amino acid frequencies, paratope-epitope interactions, bond formations, and bond types among the analyzed viral Ag-Ab complexes. The finding revealed that Ser, Gly, Tyr, Thr, and Phe are prominently present in the antibody CDRs. Analysis of CDR profiles indicated an average amino acid diversity of 60-80% in heavy chain CDRs and 45-60% in light chain CDRs. Aromatic residues, particularly Tyr, Phe, and Trp showed significant involvement in the paratope-epitope interactions in the heavy chain, while Tyr, Ser, and Thr were key contributors in the light chain. Furthermore, the study examined the occurrence of amino acids in both light and heavy chains of viral Ag- human Ab complexes, analyzing the presence of amino acids as single residues, dipeptides and tripeptides. The analysis is crucial for enhancing the antibody engineering processes including, design, optimization, affinity enhancement, and overall antibody development.

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.

A Highly Sensitive Dual-Drive Microfluidic Device for Multiplexed Detection of Respiratory Virus Antigens

Conventional microfluidic systems that rely on capillary force have a fixed structure and limited sensitivity, which cannot meet the demands of clinical applications. Herein, we propose a dual-drive microfluidic device for sensitive and flexible detection of multiple pathogenic microorganisms antigens/antibodies. The device comprises a portable microfluidic analyzer and a dual-drive microfluidic chip. Along with capillary force, a second active driving force is provided by a removable self-driving valve in the waste chamber. The interval between these two driving forces can be adjusted to control the reaction time in the microchannel, optimizing the formation of antigen-antibody complexes and enhancing sensitivity. Moreover, the material used in the self-driving valve can be changed to adjust the active force strength needed for different tests. The device offers quantitative analysis for respiratory syncytial virus antigen and SARS-CoV-2 antigen using a 35 μL sample, delivering results within 5 min. The detection limits of the system were 1.121 ng/mL and 0.447 ng/mL for respiratory syncytial virus recombinant fusion protein and SARS-CoV-2 recombinant nucleoprotein, respectively. Although the dual-drive microfluidic device has been used for immunoassay for respiratory syncytial virus and SARS-CoV-2 in this study, it can be easily adapted to other immunoassay applications by changing the critical reagents.

Development of Inhibitory Compounds for Metallo-beta-lactamase through Computational Design and Crystallographic Analysis

Metallo-β-lactamases (MBL) deactivate β-lactam antibiotics through a catalytic reaction caused by two zinc ions at the active center. Since MBLs deteriorate a wide range of antibiotics, they are dangerous factors for bacterial multidrug resistance. In this work, organic synthesis, computational design, and crystal structure analysis were performed to obtain potent MBL inhibitors based on a previously identified hit compound. The hit compound comprised 3,4-dihydro-2(1H)-quinolinone linked with a phenyl-ether-methyl group via a thiazole ring. In the first step, the thiazole ring was replaced with a tertiary amine to avoid the planar structure. In the second step, we virtually modified the compound by keeping the quinolinone backbone. Every modified compound was bound to a kind of MBL, imipenemase-1 (IMP-1), and the binding pose was optimized by a molecular mechanics calculation. The binding scores were evaluated for the respective optimized binding poses. Given the predicted binding poses and calculated binding scores, candidate compounds were determined for organic syntheses. The inhibitory activities of the synthesized compounds were measured by an in vitro assay for two kinds of MBLs, IMP-1 and New Delhi metallo-β-lactamase (NDM-1). A quinolinone connected with an amine bound with methyl-phenyl-ether-propyl and cyclohexyl-ethyl showed a 50% inhibitory concentration of 4.8 μM. An X-ray crystal analysis clarified the binding structure of a synthesized compound to IMP-1. The δ-lactam ring of quinolinone was hydrolyzed, and the generated carboxyl group was coordinated with zinc ions. The findings on the chemical structure and binding pose are expected to be a base for developing MBL inhibitors.

Sticklac-Derived Natural Compounds Inhibiting RNase H Activity of HIV-1 Reverse Transcriptase

The emergence of drug-resistant viruses is a serious concern in current chemotherapy for human immunodeficiency virus type-1 (HIV-1) infectious diseases. Hence, antiviral drugs aiming at targets that are different from those of approved drugs are still required, and the RNase H activity of HIV-1 reverse transcriptase is a suitable target. In this study, a search of a series of natural compounds was performed to identify the RNase H inhibitors. Three compounds were found to block the RNase H enzymatic activity. A laccaic acid skeleton was observed in all three natural compounds. A hydroxy phenyl group is connected to an anthraquinone backbone in the skeleton. An acetamido-ethyl, amino-carboxy-ethyl, and amino-ethyl are bound to the phenyl in laccaic acids A, C, and E, respectively. Laccaic acid C showed a 50% inhibitory concentration at 8.1 μM. Laccaic acid C also showed inhibitory activity in a cell-based viral proliferation assay. Binding structures of these three laccaic acids were determined by X-ray crystallographic analysis using a recombinant protein composed of the HIV-1 RNase H domain. Two divalent metal ions were located at the catalytic center in which one carbonyl and two hydroxy groups on the anthraquinone backbone chelated two metal ions. Molecular dynamics simulations were performed to examine the stabilities of the binding structures. Laccaic acid C showed the strongest binding to the catalytic site. These findings will be helpful for the design of potent inhibitors with modification of laccaic acids to enhance the binding affinity.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

Analysis of Interaction Between Odorant Receptors and Flexible Spike of SARS CoV-2- Key to Loss of Smell

BACKGROUND

The development of a vaccine for SARS-CoV-2 is primarily focused on the structure of the spike (S) protein. The heavy glycosylation of S with flexible hinges at the stalk shields from antibody attachment.

OBJECTIVE

This study deciphers the flexible nature of hinges responsible for binding the odorant receptor on neurons responsible for the loss of smell in COVID-19 patients.

METHODS

The 3D structure via EPIK in Maestro, protein docking with ligands via Maestro protein analysis tool, and molecular dynamic simulation at 30 ns run using DESMOND was prepared.

RESULTS

The data of the study strongly suggest that strong and stable bond formation results from the reaction between R:14: Trp and Phe at the residue, targeting the flexible hinges of SARS-CoV-2. The difference in the conformational structure of the S protein and its binding with the odorant receptor in COVID-19 is the prime factor for the loss of smell and taste in patients, as supported by the concept of Antigen (epitope) Antibody interaction by the stable formation of a hydrogen bond among odorant receptor and the S protein. The flexibility of structural proteins determines the binding potential of antibodies or other defense proteins produced to participate in the antigen-antibody reaction.

CONCLUSION

Molecular and atomic details potentiate the design and screening of small molecules that can inhibit the fusion at entry level or odorant receptors and potentially be used in the prevention and treatment of infection, particularly when formulated as nasal drops, paving a new approach for pharmacologists in the treatment of COVID-19 infection.

In Silico Identification of Inhibitory Compounds for SARS-Cov-2 Papain-Like Protease

Virtual screening with high-performance computers is a powerful and cost-effective technique in drug discovery. A chemical database is searched to find candidate compounds firmly bound to a target protein, judging from the binding poses and/or binding scores. The severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infectious disease has spread worldwide for the last three years, causing severe slumps in economic and social activities. SARS-Cov-2 has two viral proteases: 3-chymotrypsin-like (3CL) and papain-like (PL) protease. While approved drugs have already been released for the 3CL protease, no approved agent is available for PL protease. In this work, we carried out in silico screening for the PL protease inhibitors, combining docking simulation and molecular mechanics calculation. Docking simulations were applied to 8,820 molecules in a chemical database of approved and investigational compounds. Based on the binding poses generated by the docking simulations, molecular mechanics calculations were performed to optimize the binding structures and to obtain the binding scores. Based on the binding scores, 57 compounds were selected for in vitro assay of the inhibitory activity. Five inhibitory compounds were identified from the in vitro measurement. The predicted binding structures of the identified five compounds were examined, and the significant interaction between the individual compound and the protease catalytic site was clarified. This work demonstrates that computational virtual screening by combining docking simulation with molecular mechanics calculation is effective for searching candidate compounds in drug discovery.

Computational and Crystallographic Analysis of Binding Structures of Inhibitory Compounds for HIV-1 RNase H Activity

Chemotherapy of human immunodeficiency virus type-1 (HIV-1) has significantly developed over the last three decades. The emergence of drug-resistant variants is, however, still a severe problem. The RNase H activity of HIV-1 reverse transcriptase is an attractive target for a new class of antiviral drugs because there is no approved inhibitor. The nitro-furan-carbonyl and nitro-thiophene-carbonyl groups are potent scaffolds for the HIV-1 RNase H inhibitor. In this work, the binding structures of six inhibitory compounds were obtained by X-ray crystal analysis in a complex with a recombinant protein of HIV-1 RNase H domain. Every inhibitory compound was found to be bound to the catalytic site with the furan- or thiophene-ring coordinated to two divalent metal ions at the binding pocket. All the atoms in nitro, furan, carbonyl, and two metals were aligned in the nitro-furan derivatives. The straight line connecting nitro and carboxyl groups was parallel to the plane made by two metal ions and a furan O atom. The binding modes of the nitro-thiophene derivatives were slightly different from those of the nitro-furan ones. The nitro and carbonyl groups deviated from the plane made by two metals and a thiophene S atom. Molecular dynamics simulations suggested that the furan O or thiophene S atom and carbonyl O atom were firmly coordinated to the metal ions. The simulations made the planar nitro-furan moiety well aligned to the line connecting the two metal ions. In contrast, the nitro-thiophene derivatives were displaced from the initial positions after the simulations. The computational findings will be a sound basis for developing potent inhibitors for HIV-1 RNase H activity.

Electrostatic Features for the Receptor Binding Domain of SARS-COV-2 Wildtype and Its Variants. Compass to the Severity of the Future Variants with the Charge-Rule

Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pK_as for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This "RBD charge rule" should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future.

Molecularly Imprinting–Aptamer Techniques and Their Applications in Molecular Recognition

Molecular imprinting–aptamer techniques exhibit the advantages of molecular imprinting and aptamer technology. Hybrids of molecularly imprinted polymer–aptamer (MIP–aptamer) prepared by this technique have higher stability, binding affinity and superior selectivity than conventional molecularly imprinted polymers or aptamers. In recent years, molecular imprinting–aptamer technologies have attracted considerable interest for the selective recognition of target molecules in complex sample matrices and have been used in molecular recognition such as antibiotics, proteins, viruses and pesticides. This review introduced the development of molecular imprinting–aptamer-combining technologies and summarized the mechanism of MIP–aptamer formation. Meanwhile, we discussed the challenges in preparing MIP–aptamer. Finally, we summarized the application of MIP–aptamer to the molecular recognition in disease diagnosis, environmental analysis, food safety and other fields.

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.