Antigen-binding Site Research Articles

Unveiling MHC-DAB Polymorphism Within the Western Balkan Salmonid Hotspot: Preliminary Outcomes from Native Trouts of Ohrid Lake and the Drin-Skadar Drainage (Albania)

Due to their involvement in pathogen-mediated immune responses, the hypervariable genes of the Major Histocompatibility Complex (MHC) have become a paradigm for investigating the evolution and maintenance of genetic (adaptive) diversity, contextually providing insight into the viability of wild populations, which is meaningful for conservation. Here, we provide the first preliminary characterization of MHC polymorphism and evolution in trouts from Albania, a known hotspot of Salmonid diversity harboring ecologically and phylogenetically distinct native (threatened) taxa. Overall, 36 trout—including Lake Ohrid-endemic Salmo ohridanus and S. letnica, and both riverine and lacustrine native brown trout (the S. trutta complex) from the Drin-Skadar drainage—were genotyped at the MHC-DAB locus through next-generation amplicon sequencing. We identified 34 alleles (including 30 novel alleles), unveiling remarkable population/taxon MHC-DAB distinctiveness. Despite apparent functional (supertype) similarity, S. letnica and the S. trutta complex showed MHC-typical high sequence/allele diversity and evidence of global/codon-specific positive selection, particularly at antigen-binding sites. Conversely, deep-water-adapted S. ohridanus revealed unexpectedly reduced allelic/supertype diversity and relaxed selection. Evolution by reticulation and signals of trans-species polymorphism emerged from sequence genealogies. Further investigations and increased sampling will provide a deeper understanding of the evolutionary mechanisms yielding the observed pattern of MHC diversity across Albanian trout taxa and populations.

Cross-reactivity of antigenic binding sites of antiphosphatidylserine/prothrombin antibodies in patients with pregnancy loss and epidermal growth factor

BackgroundEpidermal growth factor (EGF) protein family is essential for implantation and maintenance of normal pregnancy. Results of our previous study on the high incidence of autoantibodies to EGF in patients with pregnancy loss indicated a strong association between EGF autoantibodies and antiphosphatidylserine/prothrombin antibodies (aPS/PT), which are observed in the plasma of patients with thrombosis and adverse pregnancy outcomes. ObjectivesTo investigate the association between EGF autoantibodies and aPS/PT in patients with pregnancy loss. Patients and methodsPlasma specimens were analyzed from patients who experienced pregnancy loss. Direct binding studies using recombinant proteins of the fragments were conducted to determine the antigenic binding sites of aPS/PT, before examining the cross-reactivity of EGF and aPS/PT binding sites. ResultsOf the 219 patients with pregnancy loss, 26 (11.9 %) were positive for aPS/PT. Moreover, incidence of antihuman EGF autoantibodies (anti-hEGF) was significantly higher in aPS/PT-positive patients than in aPS/PT-negative patients (18/26, 69.2 % and 58/193, 30.1 %, respectively; p = 0.0003). Of the aPS/PT-positive patients, 42.3 % recognized fragment 1 + 2 (F1 + 2), and 61.5 % recognized α-thrombin. Presence of anti-hEGF was correlated with recognition of α-thrombin but not of F1 + 2. Moreover, polyclonal antibodies against EGF recognized α-thrombin, and those against α- thrombin recognized hEGF. ConclusionsIn patients with pregnancy loss, aPS/PT recognize F1 + 2 and α-thrombin. Furthermore, α-thrombin and hEGF are immunologically cross-reactive.Therefore, autoantibody-associated disruption of the EGF system may be a cause ofpregnancy loss.

Design and development of dual targeting CAR protein for the development of CAR T-cell therapy against KRAS mutated pancreatic ductal adenocarcinoma using computational approaches

Mutant KRAS promotes the proliferation, metastasis, and aggressiveness of various cancers including pancreatic ductal adenocarcinoma (PDAC), non-small cell lung cancer (NSCLC), and colorectal adenocarcinoma (CRC) respectively. Mutant KRAS therapeutics are limited, while Sotorasib and Adagrasib were the only FDA-approved drugs for the treatment of KRASG12C mutated NSCLC. Chimeric antigen receptor (CAR) T-cell therapy has been emerged as an effective strategy against hematological malignancies and being extended towards solid cancers including PDAC. mesothelin (MSLN) and Carcinoembryonic Antigen (CEA) were reported to be highly overexpressed in KRAS-mutated PDAC. Meanwhile, in clinical trials, several CAR T-cell therapy studies are mainly focused towards these two cancer antigens in PDAC, however, the dual targeting of these two neoantigens is not reported. In the present study, we have designed and developed a novel dual-targeting CAR protein by employing various bioinformatics approaches such as functional analysis (antigenicity, allergenicity, antigen binding sites & signalling cascades), qualitative analysis (physicochemical, prediction, refinement & validation of 2D and 3D structures), molecular docking, and in silico cloning. Our results revealed that the designed CAR protein specifically binds with both MSLN & CEA with significant binding affinities, and was predicted to be stable & non-allergenic. Additionally, the protein–protein interaction network reveals the T-cell mediated antitumor responses of each domain in the designed CAR. Conclusively, we have designed and developed a dual targeting (MSLN & CEA) CAR protein towards KRAS-mutated PDAC using computational approaches. Alongside, we further recommend to engineer this designed CAR in T-cells and evaluating their therapeutic efficiency in in vitro and in vivo studies in the near future.

MHC Class II Supertypes Affect Survival and Lifetime Reproductive Success in a Migratory Songbird.

The major histocompatibility complex (MHC) plays a critical role in the immune response against pathogens. Its high polymorphism is thought to be mainly the consequence of host-pathogen co-evolution, but elucidating the mechanism(s) driving MHC evolution remains challenging for natural populations. We investigated the diversity of MHC class II genes in a wild population of pied flycatchers Ficedula hypoleuca and tested its associations with two key components of individual fitness: lifetime reproductive success and survival. Among 180 breeding adults in our study population, we found 182 unique MHC class II exon 2 alleles. The alleles showed a strong signal of positive selection and grouped into nine functional supertypes based on physicochemical properties at the inferred antigen-binding sites. Three supertypes were found in > 98% of the sampled individuals, indicating that they are nearly fixed in the population. We found no rare supertypes in the population, as all supertypes were present in > 70% of individuals. Three supertypes were related to different components of individual fitness: two were associated with lower offspring production over time, while the third was positively associated with survival. Overall, the substantial allelic and functional diversity and the relationship between specific supertypes and fitness are in accordance with the notion that balancing selection maintains MHC class II diversity in the study population, possibly with fluctuating selection as the underlying mechanism. The absence of rare supertypes in the population suggests that the balancing selection is not driven by rare-allele advantage.

Generation and Selection of Phage Display Antibody Libraries in Fab Format.

Monoclonal antibodies (mAbs) have exceptional utility as research reagents and pharmaceuticals. As a complement to both traditional and contemporary single-B-cell cloning technologies, the mining of antibody libraries via display technologies-which mimic and simplify B cells by physically linking phenotype (protein) to genotype (protein-encoding DNA or RNA)-has become an important method for mAb discovery. Among these display technologies, phage display has been particularly successful for the generation of mAbs that bind to a wide variety of antigens with exceptional specificities and affinities. Rather than multivalent whole antibodies, phage display typically uses monovalent antibody fragments, such as "fragment antigen binding" (Fab), as the format of choice. The ∼50-kDa Fab format consists of four immunoglobulin (Ig) domains on two polypeptide chains (light chain and shortened heavy chain), and exhibits its antigen binding site in a natural configuration found in bivalent IgG and other multivalent Ig molecules. The Fab fragment has a high melting temperature and a low tendency to aggregate, and can be readily converted to natural and nonnatural Ig formats without affecting antigen binding properties, which has made it a favored format for phage display for more than three decades. Here, I briefly summarize some of the approaches used for the generation and selection of phage display antibody libraries in Fab format, from human and nonhuman antibody repertoires.

Integrating molecular dynamics simulation with small- and wide-angle X-ray scattering to unravel the flexibility, antigen-blocking, and protease-restoring functions in a hindrance-based pro-antibody.

Spatial hindrance-based pro-antibodies (pro-Abs) are engineered antibodies to reduce monoclonal antibodies' (mAbs) on-target toxicity using universal designed blocking segments that mask mAb antigen-binding sites through spatial hindrance. By linking through protease substrates and linkers, these blocking segments can be removed site-specifically. Although many types of blocking segments have been developed, such as coiled-coil and hinge-based Ab locks, the molecular structure of the pro-Ab, particularly the region showing how the blocking fragment blocks the mAb, has not been elucidated by X-ray crystallography or cryo-EM. To achieve maximal effect, a pro-Ab must have high antigen-blocking and protease-restoring efficiencies, but the unclear structure limits its further optimization. Here, we utilized molecular dynamics (MD) simulations to study the dynamic structures of a hinge-based Ab lock pro-Ab, pro-Nivolumab, and validated the simulated structures with small- and wide-angle X-ray scattering (SWAXS). The MD results were closely consistent with SWAXS data (χ2 best-fit = 1.845, χ2 allMD = 3.080). The further analysis shows a pronounced flexibility of the Ab lock (root-mean-square deviation = 10.90 Å), yet it still masks the important antigen-binding residues by 57.3%-88.4%, explaining its 250-folded antigen-blocking efficiency. The introduced protease accessible surface area method affirmed better protease efficiency for light chain (33.03 Å2) over heavy chain (5.06 Å2), which aligns with the experiments. Overall, we developed MD-SWAXS validation method to study the dynamics of flexible blocking segments and introduced methodologies to estimate their antigen-blocking and protease-restoring efficiencies, which would potentially be advancing the clinical applications of any spatial hindrance-based pro-Ab.

Moderate Genetic Diversity of MHC Genes in an Isolated Small Population of Black-and-White Snub-Nosed Monkeys (Rhinopithecus bieti).

Genetic diversity is an essential indicator that echoes the natural selection and environmental adaptation of a species. Isolated small populations are vulnerable to genetic drift, inbreeding, and limited gene flow; thus, assessing their genetic diversity is critical in conservation. In this study, we studied the genetic diversity of black-and-white snub-nosed monkeys (Rhinopithecus bieti) using neutral microsatellites and five adaptive major histocompatibility complex (MHC) genes. Two DQA1 alleles, two DQB1 alleles, two DRB1 alleles, two DRB5 alleles, and three DPB1 alleles were isolated from a population. The results indicate that neutral microsatellites demonstrate a high degree of heterozygosity and polymorphism, while adaptive MHC genes display a high degree of heterozygosity and moderate polymorphism. The results also show that balancing selection has prominently influenced the MHC diversity of the species during evolution: (1) significant positive selection is identified at several amino acid sites (primarily at and near antigen-binding sites) of the DRB1, DRB5, and DQB1 genes; (2) phylogenetic analyses display the patterns of trans-species evolution for all MHC loci. This study provides valuable genetic diversity insights into black-and-white snub-nosed monkeys, which dwell at the highest altitude and have experienced the harshest environmental selection of all primates globally since the Pleistocene. Such results provide valuable scientific evidence and a reference for making or amending conservation strategies for this endangered primate species.

B cell epitope mapping: The journey to better vaccines and therapeutic antibodies

B-cell epitope mapping is an approach that can identify and characterise specific antigen binding sites of B-cell receptors and secreted antibodies. The ability to determine the antigenic clusters of amino acids bound by B-cell clones provides unprecedented detail that will aid in developing novel and effective vaccine targets and therapeutic antibodies for various diseases. Here, we discuss conventional approaches and emerging techniques that are used to map B-cell epitopes.

The CH1 domain influences the expression and antigen sensing of the HIV-specific CH31 IgM-BCR and IgG-BCR

How different classes of the B cell antigen receptor (BCR) sense viral antigens used in vaccination protocols is poorly understood. Here, we study antigen binding and sensing of human Ramos B cells expressing a BCR of either the IgM or IgG1 class with specificity for the CD4-binding-site of the envelope (Env) protein of the HIV-1. Both BCRs carry an identical antigen binding site derived from the broad neutralizing antibody (bnAb) CH31. We find a five times higher expression of the IgG1-BCR in comparison to the IgM-BCR on the surface of transfected Ramos B cells. The two BCR classes also differ from each other in their interaction with cognate HIV Env antigens in that the IgG1-BCR and IgM-BCR bind preferentially to polyvalent and monovalent antigens, respectively. By generating an IgM/IgG1 chimeric BCR, we found that the class-specific BCR expression and antigen-sensing behavior can be transferred with the CH1γ domain from the IgG1-BCR to the IgM-BCR. Thus, the class of CH1 domain has an impact on BCR assembly and expression as well as on antigen sensing.

Dynamics and Activation of Membrane-Bound B Cell Receptor Assembly.

B-cell receptor complexes (BCR) are expressed on the surface of a B-cell and are the critical regulators of adaptive immune response. Even though the relevance of antibodies has been known for almost a hundred years, the antigen-dependent activation of antibody-producing B-cells has remained elusive. Several models have been proposed for BCR activation, including cross-linking, conformation-induced oligomerization, and dissociation activation models. Recently, the first cryo-EM structure of the human B-cell antigen receptor of the IgM isotype was published. Given the new asymmetric BCR complex, we have carried out extensive molecular dynamics simulations to probe the conformational changes upon antigen binding and the influence of the membrane. We identified two critical dynamical events that could be associated with antigen-dependent activation of BCR. First, antigen binding caused increased flexibility in regions distal to the antigen binding site. Second, this increased flexibility led to the rearrangement of helices in transmembrane helices, including the relative interaction of Igα/Igβ, which has been responsible for intracellular signaling. Further, these transmembrane rearrangements led to changes in localized lipid composition. Even though the simulations considered only a single BCR complex, our work indirectly supports the dissociation activation model.

Enhanced stabilisation and reduced fibril forming potential of an amyloidogenic light chain using a variable heavy domain to mimic the homodimer complex.

Light chain amyloidosis (AL), is classified as a plasma cell dyscrasia, whereby a mutant plasma cell multiplies uncontrollably and secretes enormous amounts of immunoglobulin-free light chain (FLC) fragments. These FLCs undergo a process of misfolding and aggregation into amyloid fibrils, that can cause irreversible system-wide damage. Current treatments that focus on depleting the underlying plasma cell clone are often poorly tolerated, particularly in patients with severe cardiac involvement, meaning patient prognosis is poor. An alternative treatment approach currently being explored is the inhibition of FLC aggregation by stabilisation of the native conformer. Here, we aimed to identify and characterise antibody fragments that target FLC domains and promote their stabilisation. Using phage-display screening methods, we identified a variable heavy (VH) domain, termed VH1, targeted towards the FLC. Using differential scanning fluorimetry and surface plasmon resonance, VH1 was characterised to bind and kinetically stabilise an amyloidogenic FLC, whereby a > 5.5 °C increase in thermal stability was noted. This improved stability corresponded to the inhibition of fibril formation, where 10 : 1 LC : VH1 concentration reduced aggregation to baseline levels. X-ray crystallographic structures of the LC : VH1 complex at atomic resolution revealed binding in a 1 : 1 ratio, mimicking the dimeric antigen binding sites of the native immunoglobulin molecule and the native LC homodimer.

Machine-learning-based structural analysis of interactions between antibodies and antigens

Computational analysis of paratope-epitope interactions between antibodies and their corresponding antigens can facilitate our understanding of the molecular mechanism underlying humoral immunity and boost the design of new therapeutics for many diseases. The recent breakthrough in artificial intelligence has made it possible to predict protein-protein interactions and model their structures. Unfortunately, detecting antigen-binding sites associated with a specific antibody is still a challenging problem. To tackle this challenge, we implemented a deep learning model to characterize interaction patterns between antibodies and their corresponding antigens. With high accuracy, our model can distinguish between antibody-antigen complexes and other types of protein-protein complexes. More intriguingly, we can identify antigens from other common protein binding regions with an accuracy of higher than 70% even if we only have the epitope information. This indicates that antigens have distinct features on their surface that antibodies can recognize. Additionally, our model was unable to predict the partnerships between antibodies and their particular antigens. This result suggests that one antigen may be targeted by more than one antibody and that antibodies may bind to previously unidentified proteins. Taken together, our results support the precision of antibody-antigen interactions while also suggesting positive future progress in the prediction of specific pairing.

Mechanistic computational modeling of monospecific and bispecific antibodies targeting interleukin-6/8 receptors.

The spread of cancer from organ to organ (metastasis) is responsible for the vast majority of cancer deaths; however, most current anti-cancer drugs are designed to arrest or reverse tumor growth without directly addressing disease spread. It was recently discovered that tumor cell-secreted interleukin-6 (IL-6) and interleukin-8 (IL-8) synergize to enhance cancer metastasis in a cell-density dependent manner, and blockade of the IL-6 and IL-8 receptors (IL-6R and IL-8R) with a novel bispecific antibody, BS1, significantly reduced metastatic burden in multiple preclinical mouse models of cancer. Bispecific antibodies (BsAbs), which combine two different antigen-binding sites into one molecule, are a promising modality for drug development due to their enhanced avidity and dual targeting effects. However, while BsAbs have tremendous therapeutic potential, elucidating the mechanisms underlying their binding and inhibition will be critical for maximizing the efficacy of new BsAb treatments. Here, we describe a quantitative, computational model of the BS1 BsAb, exhibiting how modeling multivalent binding provides key insights into antibody affinity and avidity effects and can guide therapeutic design. We present detailed simulations of the monovalent and bivalent binding interactions between different antibody constructs and the IL-6 and IL-8 receptors to establish how antibody properties and system conditions impact the formation of binary (antibody-receptor) and ternary (receptor-antibody-receptor) complexes. Model results demonstrate how the balance of these complex types drives receptor inhibition, providing important and generalizable predictions for effective therapeutic design.

Specific features of a scaffolding antibody light chain.

The antigen-binding sites in conventional antibodies are formed by hypervariable complementarity-determining regions (CDRs) from both heavy chains (HCs) and light chains (LCs). A deviation from this paradigm is found in a subset of bovine antibodies that bind antigens via an ultra-long CDR. The HCs bearing ultra-long CDRs pair with a restricted set of highly conserved LCs that convey stability to the antibody. Despite the importance of these LCs, their specific features remained unknown. Here, we show that the conserved bovine LC found in antibodies with ultra-long CDRs exhibits a distinct combination of favorable physicochemical properties such as good secretion from mammalian cells, strong dimerization, high stability, and resistance to aggregation. These physicochemical traits of the LCs arise from a combination of the specific sequences in the germline CDRs and a lambda LC framework. In addition to understanding the molecular architecture of antibodies with ultra-long CDRs, our findings reveal fundamental insights into LC characteristics that can guide the design of antibodies with improved properties.

Beyond Natural Immune Repertoires: Synthetic Antibodies.

Synthetic antibody libraries, in which the antigen-binding sites are precisely designed, offer unparalleled precision in antibody engineering, exceeding the potential of natural immune repertoires and constituting a novel generation of research tools and therapeutics. Recent advances in artificial intelligence-driven technologies and their integration into synthetic antibody discovery campaigns hold the promise to further streamline and effectively develop antibodies. Here, we provide an overview of synthetic antibodies. Our associated protocol describes how to develop highly diverse and functional synthetic antibody phage display libraries.

Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer

Antibodies are crucial proteins produced by the immune system in response to foreign substances or antigens. The specificity of an antibody is determined by its complementarity-determining regions (CDRs), which are located in the variable domains of the antibody chains and form the antigen-binding site. Previous studies have utilized complex techniques to generate CDRs, but they suffer from inadequate geometric modeling. Moreover, the common iterative refinement strategies lead to an inefficient inference. In this paper, we propose a simple yet effective model that can co-design 1D sequences and 3D structures of CDRs in a one-shot manner. To achieve this, we decouple the antibody CDR design problem into two stages: (i) geometric modeling of protein complex structures and (ii) sequence-structure co-learning. We develop a novel macromolecular structure invariant embedding, typically for protein complexes, that captures both intra- and inter-component interactions among the backbone atoms, including Calpha, N, C, and O atoms, to achieve comprehensive geometric modeling. Then, we introduce a simple cross-gate MLP for sequence-structure co-learning, allowing sequence and structure representations to implicitly refine each other. This enables our model to design desired sequences and structures in a one-shot manner. Extensive experiments are conducted to evaluate our results at both the sequence and structure level, which demonstrate that our model achieves superior performance compared to the state-of-the-art antibody CDR design methods.

NanoBERTa-ASP: predicting nanobody paratope based on a pretrained RoBERTa model

BackgroundNanobodies, also known as VHH or single-domain antibodies, are unique antibody fragments derived solely from heavy chains. They offer advantages of small molecules and conventional antibodies, making them promising therapeutics. The paratope is the specific region on an antibody that binds to an antigen. Paratope prediction involves the identification and characterization of the antigen-binding site on an antibody. This process is crucial for understanding the specificity and affinity of antibody-antigen interactions. Various computational methods and experimental approaches have been developed to predict and analyze paratopes, contributing to advancements in antibody engineering, drug development, and immunotherapy. However, existing predictive models trained on traditional antibodies may not be suitable for nanobodies. Additionally, the limited availability of nanobody datasets poses challenges in constructing accurate models.MethodsTo address these challenges, we have developed a novel nanobody prediction model, named NanoBERTa-ASP (Antibody Specificity Prediction), which is specifically designed for predicting nanobody-antigen binding sites. The model adopts a training strategy more suitable for nanobodies, based on an advanced natural language processing (NLP) model called BERT (Bidirectional Encoder Representations from Transformers). To be more specific, the model utilizes a masked language modeling approach named RoBERTa (Robustly Optimized BERT Pretraining Approach) to learn the contextual information of the nanobody sequence and predict its binding site.ResultsNanoBERTa-ASP achieved exceptional performance in predicting nanobody binding sites, outperforming existing methods, indicating its proficiency in capturing sequence information specific to nanobodies and accurately identifying their binding sites. Furthermore, NanoBERTa-ASP provides insights into the interaction mechanisms between nanobodies and antigens, contributing to a better understanding of nanobodies and facilitating the design and development of nanobodies with therapeutic potential.ConclusionNanoBERTa-ASP represents a significant advancement in nanobody paratope prediction. Its superior performance highlights the potential of deep learning approaches in nanobody research. By leveraging the increasing volume of nanobody data, NanoBERTa-ASP can further refine its predictions, enhance its performance, and contribute to the development of novel nanobody-based therapeutics.Github repository: https://github.com/WangLabforComputationalBiology/NanoBERTa-ASP

Ultrasensitive Electrochemiluminescence Biosensor Based on Efficient Signal Amplification of Copper Nanoclusters Induced by CaMnO3 for CD44 Trace Detection.

Metal nanoclusters (Me NCs) have become a research hotspot in the field of electrochemiluminescence (ECL) sensing analysis. This is primarily attributed to their excellent luminescent properties and biocompatibility along with their easy synthesis and labeling characteristics. At present, the application of Me NCs in ECL mainly focuses on precious metals, whose high cost, to some extent, limits their widespread application. In this work, Cu NCs with cathode ECL emissions in persulfate (S2O82-) were prepared as signal probes using glutathione as ligands, which exhibited stable luminescence signals and high ECL efficiency. At the same time, CaMnO3 was introduced as a co-reaction promoter to increase the ECL responses of Cu NCs, thereby further expanding their application potential in biochemical analysis. Specifically, the reversible conversion of Mn3+/Mn4+ greatly promoted the generation of sulfate radicals (SO4•-), providing a guarantee for improving the luminescence signals of Cu NCs. Furthermore, a short peptide (NARKFYKGC) was introduced to enable the fixation of antibodies to specific targets, preventing the occupancy of antigen-binding sites (Fab fragments). Therefore, the sensitivity of the biosensor could be significantly enhanced by releasing additional Fab fragments. Considering the approaches discussed above, the constructed biosensor could achieve sensitive detection of CD44 over a broad range (10 fg/mL-100 ng/mL), with an ultralow detection limit of 3.55 fg/mL (S/N = 3), which had valuable implications for the application of nonprecious Me NCs in biosensing analysis.

Establishment of COS-BK cells persistently infected with archetype BK polyomavirus.

BK polyomavirus (BKPyV) was the first human polyomavirus to be isolated from an immunosuppressed kidney transplant recipient in 1971. BKPyV reactivation causes BKPyV-associated nephropathy and hemorrhagic cystitis. However, the mechanisms underlying BKPyV replication remain unclear. In the present study, we performed the long-term cultivation of COS-7 cells transfected with archetype KOM-5 DNA, which were designated as COS-BK cells. BKPyV derived from COS-BK cells was characterized by analyzing the amount of the virus based on hemagglutination, viral replication, and the production of viral protein 1 (VP1). Immunostaining showed that VP1-positive cells accounted for a small percentage of COS-BK cells. The nucleotide sequences encompassing the origin of the DNA replication of BKPyV derived from COS-BK cells were generated from KOM-5 by the deletion of an 8-bp sequence, which did not involve T antigen binding sites. BKPyV replicated most efficiently in COS-BK cells in DMEM containing 2% fetal bovine serum. These results indicate that COS-BK cells are a suitable culture system for studying the persistent infection of archetype BKPyV.

Cross-reaction mediated by distinct key amino acid combinations in the complementary-determining region (CDR) of a monoclonal antibody.

In immunology, cross-reaction between antigens and antibodies are commonly observed. Prior research has shown that various monoclonal antibodies (mAbs) can recognize a broad spectrum of epitopes related to influenza viruses. However, existing theories on cross-reactions fall short in explaining the phenomena observed. This study explored the interaction characteristics of H1-74 mAb with three peptides: two natural peptides, LVLWGIHHP and LPFQNI, derived from the hemagglutinin (HA) antigen of the H1N1 influenza virus, and one synthetic peptide, WPFQNY. Our findings indicate that the complementarity-determining region (CDR) of H1-74 mAb comprised five antigen-binding sites, containing eight key amino acid residues from the light chain variable region and 16 from the heavy chain variable region. These critical residues formed distinct hydrophobic or hydrophilic clusters and functional groups within the binding sites, facilitating interaction with antigen epitopes through hydrogen bonding, salt bridge formation, and π-π stacking. The study revealed that the formation of the antibody molecule led to the creation of binding groups and small units in the CDR, allowing the antibody to attach to a variety of antigen epitopes through diverse combinations of these small units and functional groups. This unique ability of the antibody to bind with antigen epitopes provides a new molecular basis for explaining the phenomenon of antibody cross-reaction.