CDR3 Research Articles

The characteristics of T-cell receptor repertoire in relation to systemic immune response of patients with ischemic stroke.

T lymphocytes play a vital role in the immune-inflammatory response following a stroke. However, the specific mechanisms behind the contrasting functions of T cells in the brain and peripheral tissues after a stroke remain unclear and require further investigation. T-cell receptors (TCRs) are essential in controlling how T lymphocytes develop and become active. This study aims to gain a deeper understanding of the biological function of T lymphocytes by analyzing the TCR repertoire in patients who have experienced an acute ischemic stroke (AIS). High-throughput TCR sequencing was conducted on peripheral blood samples from 25 AIS patients and 10 healthy controls. We compared the percentage of T cells and the characteristics of the TCR repertoire, specifically focusing on the recombination of V(D)J gene fragments and the diversity of the complementarity determining region 3 (CDR3) of the Vβ gene. Additionally, this study analyzed the potential biological significance of the skewed TCR repertoire in AIS patients. In patients with AIS, the proportion of circulating lymphocytes (LY%) decreased while the systemic immune-inflammatory index (SII) increased compared to healthy controls. The average number of TCR read pairs decreased, corresponding with the presence of lymphopenia. However, the recombination of V(D)J gene fragments, the number of CDR3 clonotypes, and the diversity of CDR3 was elevated in the peripheral blood of AIS patients. Furthermore, the increased number of CDR3 amino acid or nucleotide clonotypes was negatively correlated with neurologic deficits but positively correlated with AIS patients' systemic immune condition and functional outcomes. Our findings suggest that both immunosuppression and enhanced antigen-specific T-cell response may exist in the periphery of the AIS patients. Further investigation into the mechanisms underlying these opposing changes may lead to the discovery of novel targets to reverse immunosuppression or mitigate the detrimental effects of T cells in the lesioned brain of AIS patients.

On the humanization of VHHs: Prospective case studies, experimental and computational characterization of structural determinants for functionality.

The humanization of camelid-derived variable domain heavy chain antibodies (VHHs) poses challenges including immunogenicity, stability, and potential reduction of affinity. Critical to this process are complementarity-determining regions (CDRs), Vernier and Hallmark residues, shaping the three-dimensional fold and influencing VHH structure and function. Additionally, the presence of non-canonical disulfide bonds further contributes to conformational stability and antigen binding. In this study, we systematically humanized two camelid-derived VHHs targeting the natural cytotoxicity receptor NKp30. Key structural positions in Vernier and Hallmark regions were exchanged with residues from the most similar human germline sequences. The resulting variants were characterized for binding affinities, yield, and purity. Structural binding modes were elucidated through crystal structure determination and AlphaFold2 predictions, providing insights into differences in binding affinity. Comparative structural and molecular dynamics characterizations of selected variants were performed to rationalize their functional properties and elucidate the role of specific sequence motifs in antigen binding. Furthermore, systematic analyses of next-generation sequencing (NGS) and Protein Data Bank (PDB) data was conducted, shedding light on the functional significance of Hallmark motifs and non-canonical disulfide bonds in VHHs in general. Overall, this study provides valuable insights into the structural determinants governing the functional properties of VHHs, offering a roadmap for their rational design, humanization, and optimization for therapeutic applications.

Direct recognition of an intact foreign protein by an αβ T cell receptor

αβ T cell receptors (αβTCRs) co-recognise antigens when bound to Major Histocompatibility Complex (MHC) or MHC class I-like molecules. Additionally, some αβTCRs can bind non-MHC molecules, but how much intact antigen reactivities are achieved remains unknown. Here, we identify an αβ T cell clone that directly recognises the intact foreign protein, R-phycoerythrin (PE), a multimeric (αβ)6γ protein complex. This direct αβTCR–PE interaction occurs in an MHC-independent manner, yet triggers T cell activation and bound PE with an affinity comparable to αβTCR–peptide–MHC interactions. The crystal structure reveals how six αβTCR molecules simultaneously engage the PE hexamer, mediated by the complementarity-determining regions (CDRs) of the αβTCR. Here, the αβTCR mainly binds to two α-helices of the globin fold in the PE α-subunit, which is analogous to the antigen-binding platform of the MHC molecule. Using retrogenic mice expressing this TCR, we show that it supports intrathymic T cell development, maturation, and exit into the periphery as mature CD4/CD8 double negative (DN) T cells with TCR-mediated functional capacity. Accordingly, we show how an αβTCR can recognise an intact foreign protein in an antibody-like manner.

Detection of anti-EBV TCR CDR3s associated with better outcomes for EBV-positive, Ugandan cases of Burkitt lymphoma.

Burkitt lymphoma (BL) has a tight association with Epstein-Barr virus (EBV), especially in sub-Saharan Africa. While the relationship between BL and EBV is well documented, the relationship between the anti-EBV adaptive immune response, particularly in sub-Saharan African cases, and disease course, has not been substantially investigated. An analysis of T-cell receptor (TCR) complementarity determining region-3 (CDR3) sequences, reported here, from EBV-positive, Ugandan BL tumor samples revealed a correlation between the presence of anti-EBV CDR3s and improved overall survival probabilities. Furthermore, chemical complementarity assessments demonstrated higher complementarity for TCR CDR3s and EBV epitopes in the cases where there had been a detection of the anti-EBV CDR3 AA sequence matches in the BL tumor samples. Overall, the results reported here raise the question of whether EBV targeted immunotherapy would lead to better BL outcomes?

Development, physico-chemical characterization, and in vivo stability of a novel aglycosylated monoclonal antibody targeting FAM19A5

AbstractIntroducing aglycosylation into therapeutic monoclonal antibodies (mAbs) can prevent side effects associated with fragment crystallizable (Fc)-mediated effector functions. This modification induces structural changes in the heavy chain constant domain 2-constant domain 3 within Fc regions, which decreases antibody stability at acidic pH and high temperature. In this study, NS101, a novel aglycosylated mAb targeting family with sequence similarity 19, A5 (FAM19A5) for neurological diseases was evaluated with respect to its developability and in vivo stability as therapeutics. When recombinant CHO cells producing NS101 were cultivated using a fed-batch mode in a 500 L bioreactor, cell growth and mAb production profiles were consistent across three consecutive runs. NS101, thus produced, features an additional intra-disulfide bond in the heavy chain complementarity-determining region 3, contributing strong and sophisticated binding to the cryptic epitope. The melting temperature (Tm) of NS101 was lower than that of commercial glycosylated therapeutic mAbs, but NS101 showed better stability at 4 °C for 36 months. The binding affinity of NS101 to FAM19A5 and neonatal Fc receptor were comparable to those of glycosylated NS101. In addition, in three human cohort groups receiving 6, 12, and 24 mg/kg of NS101, the mean half-life was 22 days, and NS101 exhibited in vivo stability, considering that the half-lives of commercialized therapeutic mAbs and endogenous IgGs are 2–4 weeks and 21 days, respectively. Taken together, the results obtained here demonstrate that NS101, a novel aglycosylated mAb, has potential as a therapeutic agent for neurological diseases.

Stratification of Wilms tumor patients using physicochemical properties of the adaptive immune receptor polypeptides, IGL and TRG

Wilms tumor (WT) is the most common pediatric renal malignancy. Current guidelines that stratify WT risk and determine treatment courses are inadequate, as over 60% of WT survivors develop treatment-related complications. Recently, numerous advances in establishing patient sub-groups with different clinical features have been realized by evaluating the adaptive immune receptor (IR) complementarity determining region-3 (CDR3) amino acid (AA) sequences, a reasonable series of successes, given the prominent role of the CDR3 in antigen binding, including tumor antigen binding. However, the possibility that adaptive IR chemical variability correlates with distinct survival outcomes for WT has not yet been explored. The goal of this study was to isolate the T-cell receptor and B-cell receptor recombination, sequencing reads from WT RNAseq files, representing the actual tumor tissue, translate the sequences to AAs, identify the adaptive IR CDR3 domains, and determine whether the physicochemical properties of those CDR3 AA sequences correlated with survival probability distinctions. WT RNA-seq files were mined to obtain the CDR3 AAs for various adaptive IRs. The physicochemical properties of these CDR3s were examined for trends in how those properties correlated with survival probabilities for WT patients, using a Kaplan-Meier analyses, verified via several approaches. The above processes indicated the association of the (a) IGL CDR3s' instability index and the (b) TRG CDR3s' fraction disorder promoting features with better outcomes. Additionally, the IGL CDR3 data were assessed using the Predictor of Natural Disordered Regions web tool, which strengthened the evidence for the association with the IGL CDR3 instability index with a better outcome. The approaches described here indicate that greater adaptive IR CDR3 instability and flexibility may serve as prognostic indicators; and may indicate the flexibility of CDR3 domains provides for greater opportunity to bind tumor antigens. Further exploration and development of these approaches and findings may lead to new guidelines for more precise treatment regimens, or even watchful waiting periods, that could thereby decrease the lifetime occurrence of adverse events.

CDR identification, epitope mapping and binding affinity determination of novel monoclonal antibodies generated against human apolipoprotein B-100

In-house generated mAbs to apolipoprotein B-100 (apoB-100) clones hLDL-E8, hLDL-2D8 and hLDL-F5 were extensively studied to determine their complementarity-determining regions (CDRs), binding epitopes and affinity. RT-PCR revealed that all mAbs consisted of kappa light chains and gamma heavy chains. DNA sequencing and bioinformatic analysis showed that the variable gene and protein sequences of their CDRs shared over 50 % identity with the existing databases. The 3D structures of the mAb variable fragments (Fv) with a QSQE score above 0.7 were constructed using the SWISS-MODEL platform. The structural accuracy was confirmed by Ramachandran plots, with 99 % of amino acid residues falling within acceptable regions. Thrombolytic cleavage of apoB-100 and Western blot analysis demonstrated that hLDL-E8 and hLDL-F5 specifically bind to the T3 fragment (aa 1297–3249), whereas hLDL-2D8 binds to the T4 fragment (aa 1–1297). These findings were supported with epitope-binding assays using inhibition ELISA, which indicated that hLDL-E8 binds at different epitopes from hLDL-2D8 and has some overlap with hLDL-F5. Lastly, the binding affinity of the mAbs was examined by indirect ELISA. The average affinity constants (Kaff) for mAbs hLDL-2D8, hLDL-E8 and hLDL-F5 are 1.51 ± 0.69 × 109 Mol−1, 7.25 ± 3.56 × 108 Mol−1 and 4.39 ± 2.63 × 106 Mol−1, respectively. Additionally, the behavior of the antibodies in the dose-response curve revealed that hLDL-F5 may recognize two epitopes of apoB-100 or have very low binding affinity. In contrast, hLDL-2D8 and hLDL-E8 each recognize a single epitope. These findings provide information that will be useful when selecting mAbs for both laboratory and clinical research purposes.

Computational Analysis of T-Cell Receptor Repertoire Workflow: From T-Cell Isolation to Bioinformatics Analysis.

The T-cell receptor (TCR) is the key molecule involved in the adaptive immune response. It is generated by the V(D)J recombination, responsible of the enormous diversity of the TCR repertoire, a crucial feature determining the individual capability to response to antigens and to build immunological memory. A pivotal role in the recognition of antigen is played by the hypervariable complementarity-determining region 3 (CDR3) of the V-beta chain of TCR. Investigating the CDR3 supports the understanding of the adaptive immune system dynamics in physiological processes, such as immune aging, and in disease, especially autoimmune disorders in which T cells are main actors. High-throughput sequencing (HTS) paved the way for a great progress in the investigation of TCR repertoire, enhancing the read depth in the process of library generation of sequencing and the number of samples that can be analyzed simultaneously. Therefore, the leverage of big datasets stressed the need to develop computational approach, by bioinformatics, to unravel the characteristics of the TCR repertoire.

Insights into lipid-modified recognition of Apolipoprotein E3 to extra-cellular domain of TREM2 associated with Alzheimer’s disease

E3 genotype of apolipoprotein E (ApoE) and triggering receptor expressed on myeloid cells 2 (TREM2) are critical genetic risk factors for late-onset Alzheimer’s diseases (AD) that influences the formation of plaques and neurofibrillary tangles associated with AD pathogenesis. In addition, variation in genetic association of ApoE and TREM2 in presence of lipids have been advocated to potentially regulate different aspects of AD pathology by facilitating the clearance of amyloid beta (Aβ) from brain. However, the proteinopathy and functional mechanism underlying their molecular interaction in presence of lipid remains poorly understood. Herein, to shed inherent insights into the mode of ApoE3-TREM2 interaction in both lipid and aqueous medium, we have used a combination of different state-of-the-art computational tools including knowledge-based protein–protein docking and molecular dynamics (MD) simulations. Remarkably, we find the direct involvement of regulatory complementarity-determining region-2 (CDR2) loop of TREM2 in interaction with the major hinge region and helix H4 of ApoE3. We further anticipate that ApoE3 attains distinct conformational states and forms an open and extended cavity-like structure in ApoE3-TREM2 complex in presence of lipids. Our data also exhibits reduced hydrophobicity in the ApoE3 binding interface of TREM2, which sets a baseline for reduced binding affinity towards ApoE3. Therefore, we hypothesize that this decline in hydrophobic index might have resulted due to structural variations in the H4 helix and major hinge region leading to altered TREM2 conformation in presence of lipids. Altogether, our findings demonstrate the effect of phospholipids on the structural dynamics and conformation of ApoE3, which contributes to our understanding of how APOE and TREM2 influences the development of AD. However, further experimental studies are necessary to validate and explore our findings which will open up new avenues towards development of novel therapeutic strategies for AD.

Insights into cytomegalovirus-associated T cell receptors in recipients following allogeneic hematopoietic stem cell transplantation

BackgroundCytomegalovirus (CMV) reactivation is a serious problem in recipients of allogeneic hematopoietic stem cell transplantation. Long-term latency depends on specific T cell immune reconstitution, which identifies various pathogens by T cell receptors (TCRs). However, the mechanisms underlying the selection of CMV-specific TCRs in recipients after transplantation remain unclear.MethodsUsing high-throughput sequencing and bioinformatics analysis, the T cell immune repertoire of seven CMV reactivated recipients (CRRs) were analyzed and compared to those of seven CMV non-activated recipients (CNRs) at an early stage after transplant.ResultsThe counts of unique complementarity-determining region 3 (CDR3) were significantly higher in CNRs than in CRRs. The CDR3 clones in the CNRs exhibit higher homogeneity compared to the CRRs. With regard to T cell receptor β-chain variable region (TRBV) and joint region (TRBJ) genotypes, significant differences were observed in the frequencies of TRBV6, BV23, and BV7–8 between the two groups. In addition to TRBV29–1/BJ1–2, TRBV2/BJ2–2, and TRBV12–4/BJ1–5, 11 V-J combinations had significantly different expression levels between CRRs and CNRs.ConclusionsThe differences in TCR diversity, TRBV segments, and TRBV-BJ combinations observed between CNRs and CRRs might be associated with post-transplant CMV reactivation and could serve as a foundation for further research.

AI-driven antibody design with generative diffusion models: current insights and future directions.

Therapeutic antibodies are at the forefront of biotherapeutics, valued for their high target specificity and binding affinity. Despite their potential, optimizing antibodies for superior efficacy presents significant challenges in both monetary and time costs. Recent strides in computational and artificial intelligence (AI), especially generative diffusion models, have begun to address these challenges, offering novel approaches for antibody design. This review delves into specific diffusion-based generative methodologies tailored for antibody design tasks, de novo antibody design, and optimization of complementarity-determining region (CDR) loops, along with their evaluation metrics. We aim to provide an exhaustive overview of this burgeoning field, making it an essential resource for leveraging diffusion-based generative models in antibody design endeavors.

Rapid affinity optimization of an anti-TREM2 clinical lead antibody by cross-lineage immune repertoire mining

We describe a process for rapid antibody affinity optimization by repertoire mining to identify clones across B cell clonal lineages based on convergent immune responses where antigen-specific clones with the same heavy (VH) and light chain germline segment pairs, or parallel lineages, bind a single epitope on the antigen. We use this convergence framework to mine unique and distinct VH lineages from rat anti-triggering receptor on myeloid cells 2 (TREM2) antibody repertoire datasets with high diversity in the third complementarity-determining loop region (CDR H3) to further affinity-optimize a high-affinity agonistic anti-TREM2 antibody while retaining critical functional properties. Structural analyses confirm a nearly identical binding mode of anti-TREM2 variants with subtle but significant structural differences in the binding interface. Parallel lineage repertoire mining is uniquely tailored to rationally explore the large CDR H3 sequence space in antibody repertoires and can be easily and generally applied to antibodies discovered in vivo.

Structure-guided mutations in CDRs for enhancing the affinity of neutralizing SARS-CoV-2 nanobody

The optimization of antibodies to attain the desired levels of affinity and specificity holds great promise for the development of next generation therapeutics. This study delves into the refinement and engineering of complementarity-determining regions (CDRs) through in silico affinity maturation followed by binding validation using isothermal titration calorimetry (ITC) and pseudovirus-based neutralization assays. Specifically, it focuses on engineering CDRs targeting the epitopes of receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. A structure-guided virtual library of 112 single mutations in CDRs was generated and screened against RBD to select the potential affinity-enhancing mutations. Protein-protein docking analysis identified 32 single mutants of which nine mutants were selected for molecular dynamics (MD) simulations. Subsequently, biophysical ITC studies provided insights into binding affinity, and consistent with in silico findings, six mutations that demonstrated better binding affinity than native nanobody were further tested in vitro for neutralization activity against SARS-CoV-2 pseudovirus. Leu106Thr mutant was found to be most effective in virus-neutralization with IC50 values of ∼0.03 μM, as compared to the native nanobody (IC50 ∼0.77 μM). Thus, in this study, the developed computational pipeline guided by structure-aided interface profiles and thermodynamic analysis holds promise for the streamlined development of antibody-based therapeutic interventions against emerging variants of SARS-CoV-2 and other infectious pathogens.

An Integrated Strategy to Identify Tyrosine Sulfation from the Therapeutic Proteins.

Posttranslational modifications (PTMs) are potential critical quality attributes in biotherapeutic development, as they can affect drug efficacy and safety. Tyrosine sulfation plays a critical role in protein-protein interactions and has been found on many surface receptors as well as antibody complementarity-determining regions (CDR). However, the presence and function of tyrosine sulfation in therapeutic proteins have not been broadly investigated due to difficulties in detecting the modification. Here, we establish an integrated strategy to identify tyrosine sulfation in biotherapeutic proteins. In silico prediction was used to estimate possible modification sites, followed by the elucidation with intact LCMS and native SCX-MS. The combination of these three steps takes less than 1 h, which provides quick and confident preliminary detection of potential CQAs. Taking NB1 as an example, three +80 Da mass shifts were observed from intact mass analysis and three acidic peaks were monitored by SCX, allowing confirmation of modification as either phosphorylation or sulfation. Peptide mapping, Fe3+-IMAC enrichment, and dephosphorylation were further conducted to provide improved signal intensity and differentiation of modification such as sulfation or phosphorylation. With this integrated strategy, we were able to identify for the first time both tyrosine sulfation and serine phosphorylation in one therapeutic protein.

Predictability of antigen binding based on short motifs in the antibody CDRH3.

Adaptive immune receptors, such as antibodies and T-cell receptors, recognize foreign threats with exquisite specificity. A major challenge in adaptive immunology is discovering the rules governing immune receptor-antigen binding in order to predict the antigen binding status of previously unseen immune receptors. Many studies assume that the antigen binding status of an immune receptor may be determined by the presence of a short motif in the complementarity determining region 3 (CDR3), disregarding other amino acids. To test this assumption, we present a method to discover short motifs which show high precision in predicting antigen binding and generalize well to unseen simulated and experimental data. Our analysis of a mutagenesis-based antibody dataset reveals 11 336 position-specific, mostly gapped motifs of 3-5 amino acids that retain high precision on independently generated experimental data. Using a subset of only 178 motifs, a simple classifier was made that on the independently generated dataset outperformed a deep learning model proposed specifically for such datasets. In conclusion, our findings support the notion that for some antibodies, antigen binding may be largely determined by a short CDR3 motif. As more experimental data emerge, our methodology could serve as a foundation for in-depth investigations into antigen binding signals.

Development and experimental validation of computational methods for human antibody affinity enhancement.

High affinity is crucial for the efficacy and specificity of antibody. Due to involving high-throughput screens, biological experiments for antibody affinity maturation are time-consuming and have a low success rate. Precise computational-assisted antibody design promises to accelerate this process, but there is still a lack of effective computational methods capable of pinpointing beneficial mutations within the complementarity-determining region (CDR) of antibodies. Moreover, random mutations often lead to challenges in antibody expression and immunogenicity. In this study, to enhance the affinity of a human antibody against avian influenza virus, a CDR library was constructed and evolutionary information was acquired through sequence alignment to restrict the mutation positions and types. Concurrently, a statistical potential methodology was developed based on amino acid interactions between antibodies and antigens to calculate potential affinity-enhanced antibodies, which were further subjected to molecular dynamics simulations. Subsequently, experimental validation confirmed that a point mutation enhancing 2.5-fold affinity was obtained from 10 designs, resulting in the antibody affinity of 2nM. A predictive model for antibody-antigen interactions based on the binding interface was also developed, achieving an Area Under the Curve (AUC) of 0.83 and a precision of 0.89 on the test set. Lastly, a novel approach involving combinations of affinity-enhancing mutations and an iterative mutation optimization scheme similar to the Monte Carlo method were proposed. This study presents computational methods that rapidly and accurately enhance antibody affinity, addressing issues related to antibody expression and immunogenicity.

Structural insights into CXCR4 modulation and oligomerization.

Activation of the chemokine receptor CXCR4 by its chemokine ligand CXCL12 regulates diverse cellular processes. Previously reported crystal structures of CXCR4 revealed the architecture of an inactive, homodimeric receptor. However, many structural aspects of CXCR4 remain poorly understood. Here, we use cryo-electron microscopy to investigate various modes of human CXCR4 regulation. CXCL12 activates CXCR4 by inserting its N terminus deep into the CXCR4 orthosteric pocket. The binding of US Food and Drug Administration-approved antagonist AMD3100 is stabilized by electrostatic interactions with acidic residues in the seven-transmembrane-helix bundle. A potent antibody blocker, REGN7663, binds across the extracellular face of CXCR4 and inserts its complementarity-determining region H3 loop into the orthosteric pocket. Trimeric and tetrameric structures of CXCR4 reveal modes of G-protein-coupled receptor oligomerization. We show that CXCR4 adopts distinct subunit conformations in trimeric and tetrameric assemblies, highlighting how oligomerization could allosterically regulate chemokine receptor function.

Full-Length Immune Repertoire Reconstruction and Profiling at the Transcriptome Level Using Long-Read Sequencing.

Due to the diversity of the immune repertoire (IR), reconstructing full-length IR using traditional short-read sequencing has proven challenging. A full-length IR sequencing (FLIRseq) work flow was developed with linear rolling circle amplification and nanopore sequencing. Its accuracy and quantification ability were verified by plasmid mixtures and commercial B-cell receptor/T-cell receptor sequencing (BCR/TCR-seq) based on short reads. IRs in tissues and the peripheral blood from 8 patients with acute lymphoblastic leukemia, 3 patients with allergic diseases, 4 patients with psoriasis, and 5 patients with prostate cancer were analyzed using FLIRseq. FLIRseq reads had lower mismatch rates and gap rates, and higher identify rates than nanopore reads (all P < 2.2 × -16). The relative quantification of components by FLIRseq was consistent with the actual quantification (P > 0.05). FLIRseq had superiority over BCR/TCR-seq, providing the long complementarity-determining region 3, B-cell isotype, and the rarely used V gene sequence. FLIRseq observed an increase in clonotype diversity (P < 0.05) and a decrease in the percentage of abnormal BCRs/TCRs in patients with leukemia in remission. For patients with allergic diseases or psoriasis, FLIRseq provided direct insights into V(D)J recombination and specific immunoglobulin classes. Compared with that in prostate cancer tissues, the full-length V segment of the biased T-cell receptor β chain from lymphocytes in psoriatic tissues showed a more consistent AlphaFold2-predicted protein structure (P < 0.05). FLIRseq enables unbiased and comprehensive analyses of direct V(D)J recombination and immunoglobulin classes, thereby contributing to characterizing pathogenic mechanisms, monitoring minimal residual disease, and customizing adoptive cell therapy.

The 1H, 15N, and 13C resonance assignments of a single-domain antibody against immunoglobulin G.

Research on camelid-derived single-domain antibodies (sdAbs) has demonstrated their significant utility in diverse biotechnological applications, including therapy and diagnostic. This is largely due to their relative simplicity as monomeric proteins, ranging from 12 to 15kDa, in contrast to immunoglobulin G (IgG) antibodies, which are glycosylated heterotetramers of 150-160kDa. Single-domain antibodies exhibit high conformational stability and adopt the typical immunoglobulin domain fold, consisting of a two-layer sandwich of 7-9 antiparallel beta-strands. They contain three loops, known as complementary-determining regions (CDRs), which are assembled on the sdAb surface and are responsible for antigen recognition. The single-domain antibody examined in this study, sdAb-mrh-IgG, was engineered to recognize IgG from rats, mice, but it also weakly recognizes IgG from humans (Pleiner et al. 2018). A search of the Protein Data Bank revealed only one NMR structure of a single-domain antibody, which is unrelated to sdAb-mrh-IgG. The NMR chemical shift assignments of sdAb-mrh-IgG will be utilized to study its molecular dynamics and interactions with antigens in solution, which is fundamental for the rational design of novel single-domain antibodies.

FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization

The immune system depends on antibodies (Abs) to recognize and attach to a wide range of antigens, playing a pivotal role in immunity. The precise prediction of the variable fragment (Fv) region of antibodies is vital for the progress of therapeutic and commercial applications, particularly in the treatment of diseases such as cancer. Although deep learning models exist for accurate antibody structure prediction, challenges persist, particularly in modeling complementarity-determining regions (CDRs) and the overall antibody Fv structures. Introducing the FvFold model, a deep learning approach harnessing the capabilities of the ProtT5-XL-UniRef50 protein language model which is capable of predicting accurate antibody Fv structure. Through evaluations on various benchmarks, our model outperforms existing models, demonstrating superior accuracy by achieving lower Root Mean Square Deviation (RMSD) in almost all loops and Orientational Coordinate Distance (OCD) values in the RosettaAntibody benchmark, Therapeutic benchmark and IgFold benchmark compared to the previous top-performing model.