Anatomy of the antibody molecule

From bioinformatics to clinical application: A new strategy in CRP detection with peptide aptamer

C-Reactive protein (CRP) is a key biomarker for evaluating inflammation levels and estimating cardiovascular risk. However, current CRP detection methods rely on monoclonal antibodies (mAb), which possess shortcomings such as a lengthy preparation cycle, high cost, and poor repeatability. To address these challenges, we explored the potential of peptide aptamers as an alternative to mAb for CRP detection. Using some bioinformatics approaches, we designed and optimized peptide aptamers, selecting the dominant peptide aptamer C9m (KWRWRFRLSR) through experimental validation for its specific recognition of CRP. We then established a sandwich ELISA detection system combining C9m with CRP mAb. This system demonstrated a detection limit of 22.275 ng/mL CRP and exhibited excellent specificity, with no cross-reactivity observed with human serum albumin or γ-globulin. The method also showed high reproducibility, with intra- and inter-assay coefficients of variation (CV) less than 15 %, meeting laboratory testing standards. Furthermore, comparison with clinically used immunoturbidimetry revealed high consistency (r = 0.9891).

Modulating ion channels with nanobodies

Ion channels play instrumental roles in regulating membrane potential and cross-membrane signal transduction, thus making them attractive targets for understanding various physiological processes and associated diseases. Gaining a deeper understanding of their structural and functional properties has significant implications for developing therapeutic interventions. In recent years, nanobodies, single-domain antibody fragments derived from camelids, have emerged as powerful tools in ion channel and synthetic biology research. Their small size, high specificity, and ability to recognize difficult-to-reach epitopes offer advantages over conventional antibodies and biologics. Furthermore, their resemblance to the variable region of human IgG family III reduces immunogenicity concerns. Nanobodies have introduced new opportunities for exploring ion channel structure-function relationships and offer a promising alternative to conventional drugs, which often face challenges such as off-target effects and toxicity. This review highlights recent progress in applying nanobodies to interrogate and modulate ion channel activity, with an emphasis on their potential to overcome current technical and therapeutic limitations.

Computational electrostatic engineering of nanobodies for enhanced SARS-CoV-2 receptor binding domain recognition

This study presents a novel computational approach for engineering nanobodies (Nbs) for improved interaction with receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Using Protein Structure Reliability reports, RBD (7VYR_R) was selected and refined for subsequent Nb-RBD interactions. By leveraging electrostatic complementarity (EC) analysis, we engineered and characterized five Electrostatically Complementary Nbs (ECSb1-ECSb5) based on the CeVICA library's SR6c3 Nb. Through targeted modifications in the complementarity-determining regions (CDR) and framework regions (FR), we optimized electrostatic interactions to improve binding affinity and specificity. The engineered Nbs (ECSb3, ECSb4, and ECSb5) demonstrated high binding specificity for AS3, CA1, and CA2 epitopes. Interestingly, ECSb1 and ECSb2 selectively engaged with AS3 and CA1 instead of AS1 and AS2, respectively, due to a preference for residues that conferred superior binding complementarities. Furthermore, ECSbs significantly outperformed SR6c3 Nb in MM/GBSA results, notably, ECSb4 and ECSb3 exhibited superior binding free energies of -182.58 kcal.mol-1 and -119.07 kcal.mol-1, respectively, compared to SR6c3 (-105.50 kcal.mol-1). ECSbs exhibited significantly higher thermostability (100.4-148.3 kcal·mol⁻1) compared to SR6c3 (62.6 kcal·mol⁻1). Similarly, enhanced electrostatic complementarity was also observed for ECSb4-RBD and ECSb3-RBD (0.305 and 0.390, respectively) relative to SR6c3-RBD (0.233). Surface analyses confirmed optimized electrostatic patches and reduced aggregation propensity in the engineered Nb. This integrated EC and structural engineering approach successfully developed engineered Nbs with enhanced binding specificity, increased thermostability, and reduced aggregation, laying the groundwork for novel therapeutic applications targeting the SARS-CoV-2 spike protein.

Advancements in Nanobody Epitope Prediction: A Comparative Study of AlphaFold2Multimer vs AlphaFold3

Nanobodies have emerged as a versatile class of biologics with promising therapeutic applications, driving the need for robust tools to predict their epitopes, a critical step for in silico affinity maturation and epitope-targeted design. While molecular docking has long been employed for epitope identification, it requires substantial expertise. With the advent of AI driven tools, epitope identification has become more accessible to a broader community increasing the risk of models' misinterpretation. In this study, we critically evaluate the nanobody epitope prediction performance of two leading models: AlphaFold3 and AlphaFold2-Multimer (v.2.3.2), highlighting their strengths and limitations. Our analysis revealed that the overall success rate remains below 50% for both tools, with AlphaFold3 achieving a modest overall improvement. Interestingly, a significant improvement in AlphaFold3's performance was observed within a specific nanobody class. To address this discrepancy, we explored factors influencing epitope identification, demonstrating that accuracy heavily depends on CDR3 characteristics, such as its 3D spatial conformation and length, which drive binding interactions with the antigen. Additionally, we assessed the robustness of AlphaFold3's confidence metrics, highlighting their potential for broader applications. Finally, we evaluated different strategies aimed at improving the prediction success rate. This study can be extended to assess the accuracy of emerging deep learning models adopting an approach similar to that of AlphaFold3.

Structural Survey of Antigen Recognition by Synthetic Human Antibodies

Synthetic antibody libraries have been used extensively to isolate and optimize antibodies. To generate these libraries, the immunological diversity and the antibody framework(s) that supports it outside of the binding regions are carefully designed/chosen to ensure favorable functional and biophysical properties. In particular, minimalist, single-framework synthetic libraries pioneered by our group have yielded a vast trove of antibodies to a broad array of antigens. Here, we review their systematic and iterative development to provide insights into the design principles that make them a powerful tool for drug discovery. In addition, the ongoing accumulation of crystal structures of antigen-binding fragment (Fab)-antigen complexes generated with synthetic antibodies enables a deepening understanding of the structural determinants of antigen recognition and usage of immunoglobulin sequence diversity, which can assist in developing new strategies for antibody and library optimization. Toward this, we also survey here the structural landscape of a comprehensive and unbiased set of 50 distinct complexes derived from these libraries and compare it to a similar set of natural antibodies with the goal of better understanding how each achieves molecular recognition and whether opportunities exist for iterative improvement of synthetic libraries. From this survey, we conclude that despite the minimalist strategies used for design of these synthetic antibody libraries, the overall structural interaction landscapes are highly similar to natural repertoires. We also found, however, some key differences that can help guide the iterative design of new synthetic libraries via the introduction of positionally tailored diversity.

Antibody numbering schemes: advances, comparisons and tools for antibody engineering

The evolution of antibody engineering has significantly enhanced the development of antibody-based therapeutics, enabling the creation of novel antibody formats tailored for specific applications. Since the introduction of the Kabat numbering scheme in 1977, various schemes have been developed and modified, forming the foundation for multiple antibody engineering projects. The tools associated with these schemes further facilitate the engineering process. However, discrepancies among current numbering schemes can lead to confusion. This study examines various numbering schemes and related tools, providing new insights into antibody variable domains. Improved understanding of antibody numbering and related tools holds significant potential for more precise and efficient antibody design, thereby advancing antibody-based therapeutics and diagnostics.

Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors

Monoclonal antibodies (mAbs) have found extensive applications and development in treating various diseases. From the pharmaceutical industry's perspective, the journey from the design and development of mAbs to clinical testing and large-scale production is a highly time-consuming and resource-intensive process. During the research and development phase, assessing and optimizing the developability of mAbs is of paramount importance to ensure their success as candidates for therapeutic drugs. The critical factors influencing mAb development are their biophysical properties, such as aggregation propensity, solubility, and viscosity. This study utilized a data set comprising 12 biophysical properties of 137 antibodies from a previous study (Proc Natl Acad Sci USA. 114(5):944-949, 2017). We employed full-length antibody molecular dynamics simulations and machine learning techniques to predict experimental data for these 12 biophysical properties. Additionally, we utilized a newly developed deep learning model called DeepSP, which directly predicts the dynamical and structural properties of spatial aggregation propensity and spatial charge map in different antibody regions from sequences. Our research findings indicate that the machine learning models we developed outperform previous methods in predicting most biophysical properties. Furthermore, the DeepSP model yields similar predictive results compared to molecular dynamic simulations while significantly reducing computational time. The code and parameters are freely available at https://github.com/Lailabcode/AbDev. Also, the webapp, AbDev, for 12 biophysical properties prediction has been developed and provided at https://devpred.onrender.com/AbDev.

Considerations on the stability of IgG antibody in clinical specimens

The 1890s marked a significant milestone with the introduction of antibody-based agglutination and precipitation assays, revolutionizing the detection of bacterial pathogens in both animals and humans. This era also witnessed pivotal contributions to our understanding of humoral immunity, as researchers elucidated the structure and functions of antibody molecules, laying the groundwork for diagnostic applications. Among antibody isotypes, IgG is of paramount importance in diagnostic investigations given its definitive indication of infection or vaccination, coupled with its widespread presence and detectability across various specimen types, such as serum, colostrum, milk, oral fluids, urine, feces, and tissue exudate. Despite their resilience, immunoglobulins are susceptible to structural alterations induced by physicochemical and enzymatic processes, which can compromise the reliability of their detection. Here we review comprehensively the historical milestones, underlying mechanisms, and influencing factors (e.g., temperature, pH, storage) that shape the structural integrity and stability of IgG antibodies in aqueous solutions and various clinical specimens.

Nanoparticle targeting strategies for traumatic brain injury

Nanoparticle (NP)-based drug delivery systems hold immense potential for targeted therapy and diagnosis of neurological disorders, overcoming the limitations of conventional treatment modalities. This review explores the design considerations and functionalization strategies of NPs for precise targeting of the brain and central nervous system. This review discusses the challenges associated with drug delivery to the brain, including the blood-brain barrier and the complex heterogeneity of traumatic brain injury. We also examine the physicochemical properties of NPs, emphasizing the role of size, shape, and surface characteristics in their interactions with biological barriers and cellular uptake mechanisms. The review concludes by exploring the options of targeting ligands designed to augment NP affinity and retention to specific brain regions or cell types. Various targeting ligands are discussed for their ability to mimic receptor-ligand interaction, and brain-specific extracellular matrix components. Strategies to mimic viral mechanisms to increase uptake are discussed. Finally, the emergence of antibody, antibody fragments, and antibody mimicking peptides are discussed as promising targeting strategies. By integrating insights from these scientific fields, this review provides an understanding of NP-based targeting strategies for personalized medicine approaches to neurological disorders. The design considerations discussed here pave the way for the development of NP platforms with enhanced therapeutic efficacy and minimized off-target effects, ultimately advancing the field of neural engineering.

50 Years of Antibody Numbering Schemes: A Statistical and Structural Evaluation Reveals Key Differences and Limitations

BACKGROUND

The complementarity-determining region (CDR) of antibodies represents the most diverse region both in terms of sequence and structural characteristics, playing the most critical role in antibody recognition and binding for immune responses. Over the past decades, several numbering schemes have been introduced to define CDRs based on sequence. However, the existence of diverse numbering schemes has led to potential confusion, and a comprehensive evaluation of these schemes is lacking.

METHODS

We employ statistical analyses to quantify the diversity of CDRs compared to the framework regions.

RESULTS

Comparative analyses across different numbering schemes demonstrate notable variations in CDR definitions. The Kabat and AbM numbering schemes tend to incorporate more conserved residues into their CDR definitions, whereas CDRs defined by the Chothia and IMGT numbering schemes display greater diversity, sometimes missing certain loop residues. Notably, we identify a critical residue, L29, within the kappa light chain CDR1, which appears to act as a pivotal structural point within the loop. In contrast, most numbering schemes designate the topological equivalent point in the lambda light chain as L30, suggesting the need for further refinement in the current numbering schemes.

CONCLUSIONS

These findings shed light on regional sequence and structural conservation within antibody sequence databases while also highlighting discrepancies stemming from different numbering schemes. These insights yield valuable guidelines for the precise delineation of antibody CDRs and the strategic design of antibody repertoires, with practical implications in developing innovative antibody-based therapeutics and diagnostics.

Determining key residues of engineered scFv antibody variants with improved MMP-9 binding using deep sequencing and machine learning

Given the crucial role of specific matrix metalloproteinases (MMPs) in the extracellular matrix, an imbalance in the regulation of activation of matrix metalloproteinase-9 (MMP-9) zymogen and inhibition of the enzyme can result in various diseases, such as cancer, neurodegenerative, and gynecological diseases. Thus, developing novel therapeutics that target MMP-9 with single-chain antibody fragments (scFvs) is a promising approach. We used fluorescent-activated cell sorting (FACS) to screen a synthetic scFv antibody library displayed on yeast for enhanced binding to MMP-9. The screened scFv mutants demonstrated improved binding to MMP-9 compared to the natural inhibitor of MMPs, tissue inhibitor of metalloproteinases (TIMPs). To identify the molecular determinants of these engineered scFv variants that affect binding to MMP-9, we used next-generation DNA sequencing and computational protein structure analysis. Additionally, a deep-learning language model was trained on the screened scFv library of variants to predict the binding affinities of scFv variants based on their CDR-H3 sequences.

Optimizing Western blotting immunodetection: Streamlining antibody cocktails for reduced protocol time and enhanced multiplexing applications

Adaptive, rather than innate, immunity relies mainly on antigen-antibody recognition. This recognition is driven by the binding of specific antibody paratopes to distinct epitopes found on antigens. This interaction is pivotal for immune responses that have been re-purposed for diagnostic and therapeutic purposes. This article focuses on Western blotting, an in vitro technique performed for protein immunodetection. Traditionally, this technique requires separate incubations of both primary and secondary antibodies, for which these antibodies recognize different antigen epitopes (conventional method). We propose a modified protocol combining both antibodies, involving a single incubation step that reduces time and conserves reagents (non-conventional/improved method). This improved protocol will enhance efficiency without compromising detection accuracy. It will support multiplexing, enabling the simultaneous detection of multiple proteins. Despite the positive results found by applying available antibodies, further optimization is required for a more thorough evaluation, to ensure that all antibodies consistently yield successful results in every detection attempt for broader use. Our findings indicate that the tested antibody cocktails remained stable over time, which suggests potential for commercialization of this modified Western blot protocol with a wide scope towards multiplex diagnostic application.

In vivo mRNA expression of a multi-mechanistic mAb combination protects against Staphylococcus aureus infection

Single monoclonal antibodies (mAbs) can be expressed in vivo through gene delivery of their mRNA formulated with lipid nanoparticles (LNPs). However, delivery of a mAb combination could be challenging due to the risk of heavy and light variable chain mispairing. We evaluated the pharmacokinetics of a three mAb combination against Staphylococcus aureus first in single chain variable fragment scFv-Fc and then in immunoglobulin G 1 (IgG1) format in mice. Intravenous delivery of each mRNA/LNP or the trio (1 mg/kg each) induced functional antibody expression after 24 h (10-100 μg/mL) with 64%-78% cognate-chain paired IgG expression after 3 days, and an absence of non-cognate chain pairing for scFv-Fc. We did not observe reduced neutralizing activity for each mAb compared with the level of expression of chain-paired mAbs. Delivery of the trio mRNA protected mice in an S. aureus-induced dermonecrosis model. Intravenous administration of the three mRNA in non-human primates achieved peak serum IgG levels ranging between 2.9 and 13.7 μg/mL with a half-life of 11.8-15.4 days. These results suggest nucleic acid delivery of mAb combinations holds promise and may be a viable option to streamline the development of therapeutic antibodies.

Elucidating key determinants of engineered scFv antibody in MMP-9 binding using high throughput screening and machine learning

An imbalance in matrix metalloproteinase-9 (MMP-9) regulation can lead to numerous diseases, including neurological disorders, cancer, and pre-term labor. Engineering single-chain antibody fragments (scFvs) Targeting MMP-9 to develop novel therapeutics for such diseases is desirable. We screened a synthetic scFv antibody library displayed on the yeast surface for binding improvement to MMP-9 using FACS (fluorescent-activated cell sorting). The scFv antibody clones isolated after FACS showed improvement in binding to MMP-9 compared to the endogenous inhibitor. To understand molecular determinants of binding between engineered scFv antibody variants and MMP-9, next-generation DNA sequencing, and computational protein structure analysis were used. Additionally, a deep-learning language model was trained on the synthetic library to predict the binding of scFv variants using their CDR-H3 sequences.

Folding Kinetics and Volume Variation of the β-Hairpin Peptide Chignolin upon Ultrafast pH-Jumps

In-depth characterization of fundamental folding steps of small model peptides is crucial for a better understanding of the folding mechanisms of more complex biomacromolecules. We have previously reported on the folding/unfolding kinetics of a model α-helix. Here, we study folding transitions in chignolin (GYDPETGTWG), a short β-hairpin peptide previously used as a model to study conformational changes in β-sheet proteins. Although previously suggested, until now, the role of the Tyr2-Trp9 interaction in the folding mechanism of chignolin was not clear. In the present work, pH-dependent conformational changes of chignolin were characterized by circular dichroism (CD), nuclear magnetic resonance (NMR), ultrafast pH-jump coupled with time-resolved photoacoustic calorimetry (TR-PAC), and molecular dynamics (MD) simulations. Taken together, our results present a comprehensive view of chignolin's folding kinetics upon local pH changes and the role of the Tyr2-Trp9 interaction in the folding process. CD data show that chignolin's β-hairpin formation displays a pH-dependent skew bell-shaped curve, with a maximum close to pH 6, and a large decrease in β-sheet content at alkaline pH. The β-hairpin structure is mainly stabilized by aromatic interactions between Tyr2 and Trp9 and CH-π interactions between Tyr2 and Pro4. Unfolding of chignolin at high pH demonstrates that protonation of Tyr2 is essential for the stability of the β-hairpin. Refolding studies were triggered by laser-induced pH-jumps and detected by TR-PAC. The refolding of chignolin from high pH, mainly due to the protonation of Tyr2, is characterized by a volume expansion (10.4 mL mol-1), independent of peptide concentration, in the microsecond time range (lifetime of 1.15 μs). At high pH, the presence of the deprotonated hydroxyl (tyrosinate) hinders the formation of the aromatic interaction between Tyr2 and Trp9 resulting in a more disorganized and dynamic tridimensional structure of the peptide. This was also confirmed by comparing MD simulations of chignolin under conditions mimicking neutral and high pH.

Next generation single-domain antibodies against respiratory zoonotic RNA viruses

The global impact of zoonotic viral outbreaks underscores the pressing need for innovative antiviral strategies, particularly against respiratory zoonotic RNA viruses. These viruses possess a high potential to trigger future epidemics and pandemics due to their high mutation rate, broad host range and efficient spread through airborne transmission. Recent pandemics caused by coronaviruses and influenza A viruses underscore the importance of developing targeted antiviral strategies. Single-domain antibodies (sdAbs), originating from camelids, also known as nanobodies or VHHs (Variable Heavy domain of Heavy chain antibodies), have emerged as promising tools to combat current and impending zoonotic viral threats. Their unique structure, coupled with attributes like robustness, compact size, and cost-effectiveness, positions them as strong alternatives to traditional monoclonal antibodies. This review describes the pivotal role of sdAbs in combating respiratory zoonotic viruses, with a primary focus on enhancing sdAb antiviral potency through optimization techniques and diverse administration strategies. We discuss both the promises and challenges within this dynamically growing field.

Teaching biologics design using molecular modeling and simulations

Teaching chemistry and biology students about biologics design remains challenging despite its increasing importance in pharmaceutical development. Monoclonal antibodies, commonly called mAbs, are the most popular biologics. They have been developed into drugs to treat various diseases in the past decades. Multiple challenges exist for designing proper formulations to stabilize mAbs, such as preventing aggregation and mitigating viscosity. Molecular modeling and simulations can improve pharmaceutical products by examining the interactions between mAbs and other compounds, such as excipients. To introduce students to biopharmaceuticals, eight students at the Stevens Institute of Technology participated in a semester-long course to learn the challenges of pharmaceutical development and different computational skills to study biologics design. The students started with a limited background in this field. Throughout one semester, they were introduced to various literature and software tools for modeling antibodies and studying their interactions with excipients. This paper aims to develop a course structure to be replicated at other universities and institutions to teach biopharmaceutical development to students.

Development, High-Throughput Profiling, and Biopanning of a Large Phage Display Single-Domain Antibody Library

Immunoglobulin G-based monoclonal antibodies (mAbs) have been effective in treating various diseases, but their large molecular size can limit their penetration of tissue and efficacy in multifactorial diseases, necessitating the exploration of alternative forms. In this study, we constructed a phage display library comprising single-domain antibodies (sdAbs; or "VHHs"), known for their small size and remarkable stability, using a total of 1.6 × 109 lymphocytes collected from 20 different alpacas, resulting in approximately 7.16 × 1010 colonies. To assess the quality of the constructed library, next-generation sequencing-based high-throughput profiling was performed, analyzing approximately 5.65 × 106 full-length VHH sequences, revealing 92% uniqueness and confirming the library's diverse composition. Systematic characterization of the library revealed multiple sdAbs with high affinity for three therapeutically relevant antigens. In conclusion, our alpaca sdAb phage display library provides a versatile resource for diagnostics and therapeutics. Furthermore, the library's vast natural VHH antibody repertoire offers insights for generating humanized synthetic sdAb libraries, further advancing sdAb-based therapeutics.

Combinatorially restricted computational design of protein-protein interfaces to produce IgG heterodimers

Redesigning protein-protein interfaces is an important tool for developing therapeutic strategies. Interfaces can be redesigned by in silico screening, which allows for efficient sampling of a large protein space before experimental validation. However, computational costs limit the number of combinations that can be reasonably sampled. Here, we present combinatorial tyrosine (Y)/serine (S) selection (combYSelect), a computational approach combining in silico determination of the change in binding free energy (ΔΔG) of an interface with a highly restricted library composed of just two amino acids, tyrosine and serine. We used combYSelect to design two immunoglobulin G (IgG) heterodimers-combYSelect1 (L368S/D399Y-K409S/T411Y) and combYSelect2 (D399Y/K447S-K409S/T411Y)-that exhibit near-optimal heterodimerization, without affecting IgG stability or function. We solved the crystal structures of these heterodimers and found that dynamic π-stacking interactions and polar contacts drive preferential heterodimeric interactions. Finally, we demonstrated the utility of our combYSelect heterodimers by engineering both a bispecific antibody and a cytokine trap for two unique therapeutic applications.

Simultaneous Recording of Remote Domain Dynamics in Membrane Proteins Using the Double-Labeled DXB/DXT Technique

Protein dynamics play important roles in biological functions, which accompany allosteric structure changes. Diffracted X-ray blinking (DXB) uses monochromatic X-rays and nanocrystal probes. The intramolecular motion of target proteins is analyzed from the intensity changes in detector signals at the diffraction rings. In contrast, diffracted X-ray tracking (DXT) elucidates molecular dynamics by analyzing the trajectories of Laue spots. In this study, we have developed a dual-labeling technique for DXB and DXT, allowing the simultaneous observation of motions at different domains in proteins. We identified zinc oxide (ZnO) crystals as promising candidates for the second labeling probes due to their excellent diffraction patterns, high chemical stability, and favorable binding properties with proteins. The diffraction spots from the ZnO crystals are sufficiently separated from those of gold, enabling independent motion analysis at different domains. Dual-labeling DXB was employed for the motion analysis of the 5-HT2A receptor in living cells. Simultaneous motion recording of the N-terminus and the second extracellular loop demonstrated ligand-induced motion suppression at both domains. The dual-labeling DXT technique demonstrated a capsaicin-induced peak shift in the two-dimensional motion maps at the N-terminus of the TRPV1 protein, but the peak shift was not obvious in the C-terminus. The capsaicin-induced motion modulation was recovered by the addition of the competitive inhibitor AMG9810.

CE-MS/MS and CE-timsTOF to separate and characterize intramolecular disulfide bridges of monoclonal antibody subunits and their application for the assessment of subunit reduction protocols

Characterization at the subunit level enables detailed mass spectrometric characterization of posttranslational modifications (PTMs) of monoclonal antibodies (mAbs). The implemented reduction often leaves the intramolecular disulfide bridges intact. Here, we present a capillary electrophoretic (CE) method based on a neutral-coated capillary for the separation of immunoglobulin G-degrading enzyme of Streptococcus pyogenes (IdeS) digested and reduced mAb subunits followed by mass spectrometry (MS), MS/MS identification, and trapped ion mobility mass spectrometry (timsTOF). Our CE approach enables the separation of (i) different subunit moieties, (ii) various reduction states, and (iii) positional isomers of these partly reduced subunit moieties. The location of the remaining disulfide bridges can be determined by middle-down electron transfer higher energy collisional dissociation (EThcD) experiments. All these CE-separated variants show differences in ion mobility in the timsTOF measurements. Applying the presented CE-MS/MS method, reduction parameters such as the use of chaotropic salts were studied. For the investigated antibodies, urea improved the subunit reduction significantly, whereas guanidine hydrochloride (GuHCl) leads to multiple signals of the same subunit in the CE separation. The presented CE-MS method is a powerful tool for the disulfide-variant characterization of mAbs on the subunit level. It enables understanding disulfide bridge reduction processes in antibodies and potentially other proteins.

Comparison of Non B-Ig and B-Ig

Immunoglobulin (Ig) has been widely acknowledged to be produced solely by B-lineage cells. However, growing evidence has demonstrated the expression of Ig in an array of cancer cells, as well as normal cells including epithelial cells, epidermal cells, mesangial cells, monocytes, and neutrophils. Ig has even been found to be expressed in non-B cells at immune-privileged sites such as neurons and spermatogenic cells. Despite these non-B cell-derived Igs (non-B-Igs) sharing the same symmetric structures with conventional Igs (B-Igs), further studies have revealed unique characteristics of non-B-Ig, such as restricted variable region and aberrant glycosylation. Moreover, non-B-Ig exhibits properties of promoting malignant behaviours of cancer cells, therefore it could be utilised in the clinic as a potential therapeutic biomarker or target. The elucidation of the generation and regulation of non-B-Ig will certainly broaden our understanding of immunology.

Conformation-selective rather than avidity-based binding to tumor associated antigen derived peptide-MHC enables targeting of WT1-pMHC low expressing cancer cells by anti-WT1-pMHC/CD3 T cell engagers

T cell engagers, a category of T cell-retargeting immunotherapy, are rapidly transforming clinical cancer care. However, the lack of tumor-specific targets poses a significant roadblock for broad adaptation of this therapeutic modality in many indications, often resulting in systemic on-target off-tumor toxicity. Though various tumor-derived intracellular mutations provide a massive pool of potential tumor-specific antigens, targeting them is extremely challenging, partly due to the low copy number of tumor associated antigen (TAA)-derived pMHC on tumor cell surface. Further, the interplay of binding geometry and format valency in relation to the capacity of a T cell engager to efficiently target low density cell-surface pMHC is not well understood. Using the Wilms' tumor 1 (WT1) oncoprotein as a proof-of-principle TAA, combined with an array of IgG-like T cell engager modalities that differ in their anti-TAA valency and binding geometry, we show that the ability to induce an immunological synapse formation, resulting in potent killing of WT1 positive cancer cell lines is primarily dependent on the distinct geometrical conformations between the Fab arms of anti-WT1-HLA-A*02:01 and anti-CD3. The augmented avidity conferred by the binding of two anti-WT1-HLA-A*02:01 Fab arms has only minimal influence on cell killing potency. These findings demonstrate the need for careful examination of key design parameters for the development of next-generation T cell engagers targeting low density TAA-pMHCs on tumor cells.

Viscosity Prediction of High-Concentration Antibody Solutions with Atomistic Simulations

The computational prediction of the viscosity of dense protein solutions is highly desirable, for example, in the early development phase of high-concentration biopharmaceutical formulations where the material needed for experimental determination is typically limited. Here, we use large-scale atomistic molecular dynamics (MD) simulations with explicit solvation to de novo predict the dynamic viscosities of solutions of a monoclonal IgG1 antibody (mAb) from the pressure fluctuations using a Green-Kubo approach. The viscosities at simulated mAb concentrations of 200 and 250 mg/mL are compared to the experimental values, which we measured with rotational rheometry. The computational viscosity of 24 mPa·s at the mAb concentration of 250 mg/mL matches the experimental value of 23 mPa·s obtained at a concentration of 213 mg/mL, indicating slightly different effective concentrations (or activities) in the MD simulations and in the experiments. This difference is assigned to a slight underestimation of the effective mAb-mAb interactions in the simulations, leading to a too loose dynamic mAb network that governs the viscosity. Taken together, this study demonstrates the feasibility of all-atom MD simulations for predicting the properties of dense mAb solutions and provides detailed microscopic insights into the underlying molecular interactions. At the same time, it also shows that there is room for further improvements and highlights challenges, such as the massive sampling required for computing collective properties of dense biomolecular solutions in the high-viscosity regime with reasonable statistical precision.

A cell hybridization-based method of generating recombinant rabbit monoclonal antibodies for detecting cytokines

Recombinant rabbit monoclonal antibodies (rabbit rAbs) have shown promise in various biomedical fields. However, it is challenging and costly to generate rabbit rAbs using traditional techniques. Here we describe a convenient and cost-effective method. Using this method, we generated rabbit rAbs against mouse soluble IL-6 receptor α with affinities in the range of 10-9 to 10-12 M. The presented method is suitable for industrial and academic scientists looking to customize rabbit rAbs for their research.

Noninvasive In Vivo Imaging of T-Cells during Cancer Immunotherapy Using Rare-Earth Nanoparticles

Only a minority of patients respond positively to cancer immunotherapy, and addressing this variability is an active area of immunotherapy research. Infiltration of tumors by immune cells is one of the most significant prognostic indicators of response and disease-free survival. However, the ability to noninvasively sample the tumor microenvironment for immune cells remains limited. Imaging in the near-infrared-II region using rare-earth nanocrystals is emerging as a powerful imaging tool for high-resolution deep-tissue imaging. In this paper, we demonstrate that these nanoparticles can be used for noninvasive in vivo imaging of tumor-infiltrating T-cells in a highly aggressive melanoma tumor model. We present nanoparticle synthesis and surface modification strategies for the generation of small, ultrabright, and biocompatible rare-earth nanocrystals necessary for deep tissue imaging of rare cell types. The ability to noninvasively monitor the immune contexture of a tumor during immunotherapy could lead to early identification of nonresponding patients in real time, leading to earlier interventions and better outcomes.

Development of a V5-tag-directed nanobody and its implementation as an intracellular biosensor of GPCR signaling

Protein-protein interactions (PPIs) form the foundation of any cell signaling network. Considering that PPIs are highly dynamic processes, cellular assays are often essential for their study because they closely mimic the biological complexities of cellular environments. However, incongruity may be observed across different PPI assays when investigating a protein partner of interest; these discrepancies can be partially attributed to the fusion of different large functional moieties, such as fluorescent proteins or enzymes, which can yield disparate perturbations to the protein's stability, subcellular localization, and interaction partners depending on the given cellular assay. Owing to their smaller size, epitope tags may exhibit a diminished susceptibility to instigate such perturbations. However, while they have been widely used for detecting or manipulating proteins in vitro, epitope tags lack the in vivo traceability and functionality needed for intracellular biosensors. Herein, we develop NbV5, an intracellular nanobody binding the V5-tag, which is suitable for use in cellular assays commonly used to study PPIs such as BRET, NanoBiT, and Tango. The NbV5:V5 tag system has been applied to interrogate G protein-coupled receptor signaling, specifically by replacing larger functional moieties attached to the protein interactors, such as fluorescent or luminescent proteins (∼30 kDa), by the significantly smaller V5-tag peptide (1.4 kDa), and for microscopy imaging which is successfully detected by NbV5-based biosensors. Therefore, the NbV5:V5 tag system presents itself as a versatile tool for live-cell imaging and a befitting adaptation to existing cellular assays dedicated to probing PPIs.

Animal Models of IgE Anaphylaxis

Allergies and atopy have emerged as significant public health concerns, with a progressively increasing incidence over the last two decades. Anaphylaxis is the most severe form of allergic reactions, characterized by a rapid onset and potentially fatal outcome, even in healthy individuals. Due to the unpredictable nature and potential lethality of anaphylaxis and the wide range of allergens involved, clinical studies in human patients have proven to be challenging. Diagnosis is further complicated by the lack of reliable laboratory biomarkers to confirm clinical suspicion. Thus, animal models have been developed to replicate human anaphylaxis and explore its pathophysiology. Whereas results obtained from animal models may not always be directly translatable to humans, they serve as a foundation for understanding the underlying mechanisms. Animal models are an essential tool for investigating new biomarkers that could be incorporated into the allergy workup for patients, as well as for the development of novel treatments. Two primary pathways have been described in animals and humans: classic, predominantly involving IgE and histamine, and alternative, reliant on IgG and the platelet-activating factor. This review will focus essentially on the former and aims to describe the most utilized IgE-mediated anaphylaxis animal models, including their respective advantages and limitations.

Construction of an alpaca immune antibody library for the selection of nanobodies against Drosophila melanogaster proteins

Introduction: Drosophila melanogaster is a model organism for studying developmental biology and human neural disorders. Nanobodies are the variable domains of the heavy chains of camelid heavy-chain antibodies (VHHs) with high affinity to their antigens and have applications in basic research, similar to traditional antibodies. In addition, nanobodies acting as functionalized antibodies or protein binders have become an additional valuable approach in Drosophila. This study aimed to develop a VHH library against Drosophila proteins and confirm its availability by retrieving some Drosophila protein-specific nanobodies from the library. Methods: An alpaca was first immunized with Drosophila embryo lysate and then its lymphocytes were isolated. Total RNA was extracted and cDNA was synthesized. The vhh sequences were amplified by two round PCR, which were then ligated to a phage display vector pADL-10b. The ligation products were transduced into SS320 competent cells to generate a VHH library. From this library, nanobodies against CG7544, Myc, and CyclinE was enriched and screened by phage display technology and ELISA. DNA sequences of identified nanobodies were cloned into pADL-10b-Flag-His for expression and purification in Escherichia coli SS320. Binding ability of purified nanobodies with corresponding antigens were determined by ELISA and surface plasmon resonance in vitro. Results: In this study, an immune VHH library against Drosophila embryo proteins was generated with a capacity of 3 × 10⁷. From this library, eight nanobodies against three Drosophila proteins, Myc, CyclinE, and CG7544, were identified and the DNA sequences of these nanobodies were obtained. These nanobodies were successfully expressed and purified from Escherichia coli SS320, and were demonstrated to bind corresponding antigens with high affinity in vitro. Moreover, the equilibrium constant between the highest enriched nanobodies and corresponding antigens were calculated. Conclusion: In summary, we report the availability of an immune VHH library and a highly efficient panning strategy for nanobodies against proteins in Drosophila.

Applications of synthetic biology in medical and pharmaceutical fields

Synthetic biology aims to design or assemble existing bioparts or bio-components for useful bioproperties. During the past decades, progresses have been made to build delicate biocircuits, standardized biological building blocks and to develop various genomic/metabolic engineering tools and approaches. Medical and pharmaceutical demands have also pushed the development of synthetic biology, including integration of heterologous pathways into designer cells to efficiently produce medical agents, enhanced yields of natural products in cell growth media to equal or higher than that of the extracts from plants or fungi, constructions of novel genetic circuits for tumor targeting, controllable releases of therapeutic agents in response to specific biomarkers to fight diseases such as diabetes and cancers. Besides, new strategies are developed to treat complex immune diseases, infectious diseases and metabolic disorders that are hard to cure via traditional approaches. In general, synthetic biology brings new capabilities to medical and pharmaceutical researches. This review summarizes the timeline of synthetic biology developments, the past and present of synthetic biology for microbial productions of pharmaceutics, engineered cells equipped with synthetic DNA circuits for diagnosis and therapies, live and auto-assemblied biomaterials for medical treatments, cell-free synthetic biology in medical and pharmaceutical fields, and DNA engineering approaches with potentials for biomedical applications.

Design of an artificial phage-display library based on a new scaffold improved for average stability of the randomized proteins

Scaffold-based protein libraries are designed to be both diverse and rich in functional/folded proteins. However, introducing an extended diversity while preserving stability of the initial scaffold remains a challenge. Here we developed an original approach to select the ensemble of folded proteins from an initial library. The thermostable CheY protein from Thermotoga maritima was chosen as scaffold. Four loops of CheY were diversified to create a new binding surface. The subset of the library giving rise to folded proteins was first selected using a natural protein partner of the template scaffold. Then, a gene shuffling approach based on a single restriction enzyme was used to recombine DNA sequences encoding these filtrated variants. Taken together, the filtration strategy and the shuffling of the filtrated sequences were shown to enrich the library in folded and stable sequences while maintaining a large diversity in the final library (Lib-Cheytins 2.1). Binders of the Oplophorus luciferase Kaz domain were then selected by phage display from the final library, showing affinities in the μM range. One of the best variants induced a loss of 92% of luminescent activity, suggesting that this Cheytin preferentially binds to the Kaz active site.

Homology Modeling of Antibody Variable Regions: Methods and Applications

Adaptive immunity specifically protects us from antigenic challenges. Antibodies are key effector proteins of adaptive immunity, and they are remarkable in their ability to recognize a virtually limitless number of antigens. Fragment variable (F_V), the antigen-binding region of antibodies, can be split into two main components, namely, framework and complementarity determining regions. The framework (FR) consists of light-chain framework (FR_L) and heavy-chain framework (FR_H). Similarly, the complementarity determining regions (CDRs) comprises of light-chain CDRs 1-3 (CDRs L1-3) and heavy-chain CDRs 1-3 (CDRs H1-3). While FRs are relatively constant in sequence and structure across diverse antibodies, sequence variation in CDRs leading to differential conformations of CDR loops accounts for the distinct antigenic specificities of diverse antibodies. The conserved structural features in FRs and conformity of CDRs to a limited set of standard conformations allow for the accurate prediction of F_V models using homology modeling techniques. Antibody structure prediction from its amino acid sequence has numerous important applications including prediction of antibody-antigen interaction interfaces and redesign of therapeutically and biotechnologically useful antibodies with improved affinity. This chapter summarizes the current practices employed in the successful homology modeling of antibody variable regions and the potential applications of the generated homology models.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Camels' biological fluids contained nanobodies: promising avenue in cancer therapy

Cancer is a major health concern and accounts for one of the main causes of death worldwide. Innovative strategies are needed to aid in the diagnosis and treatment of different types of cancers. Recently, there has been an evolving interest in utilizing nanobodies of camel origin as therapeutic tools against cancer. Nanotechnology uses nanobodies an emerging attractive field that provides promises to researchers in advancing different scientific sectors including medicine and oncology. Nanobodies are characteristically small-sized biologics featured with the ability for deep tissue penetration and dissemination and harbour high stability at high pH and temperatures. The current review highlights the potential use of nanobodies that are naturally secreted in camels’ biological fluids, both milk and urine, in the development of nanotechnology-based therapy for treating different typesQuery of cancers and other diseases. Moreover, the role of nano proteomics in the invention of novel therapeutic agents specifically used for cancer intervention is also illustrated.

Camelid Single-Domain Antibodies: Promises and Challenges as Lifesaving Treatments

Since the discovery of camelid heavy-chain antibodies in 1993, there has been tremendous excitement for these antibody domains (VHHs/sdAbs/nanobodies) as research tools, diagnostics, and therapeutics. Commercially, several patents were granted to pioneering research groups in Belgium and the Netherlands between 1996–2001. Ablynx was established in 2001 with the aim of exploring the therapeutic applications and development of nanobody drugs. Extensive efforts over two decades at Ablynx led to the first approved nanobody drug, caplacizumab (Cablivi) by the EMA and FDA (2018–2019) for the treatment of rare blood clotting disorders in adults with acquired thrombotic thrombocytopenic purpura (TPP). The relatively long development time between camelid sdAb discovery and their entry into the market reflects the novelty of the approach, together with intellectual property restrictions and freedom-to-operate issues. The approval of the first sdAb drug, together with the expiration of key patents, may open a new horizon for the emergence of camelid sdAbs as mainstream biotherapeutics in the years to come. It remains to be seen if nanobody-based drugs will be cheaper than traditional antibodies. In this review, I provide critical perspectives on camelid sdAbs and present the promises and challenges to their widespread adoption as diagnostic and therapeutic agents.

Bivalent EGFR-Targeting DARPin-MMAE Conjugates

Epidermal growth factor receptor (EGFR) is a validated tumor marker overexpressed in various cancers such as squamous cell carcinoma (SSC) of the head and neck and gliomas. We constructed protein-drug conjugates based on the anti-EGFR Designed Ankyrin Repeat Protein (DARPin) E01, and compared the bivalent DARPin dimer (DD1) and a DARPin-Fc (DFc) to the monomeric DARPin (DM) and the antibody derived scFv425-Fc (scFvFc) in cell culture and a mouse model. The modular conjugation system, which was successfully applied for the preparation of protein-drug and -dye conjugates, uses bio-orthogonal protein-aldehyde generation by the formylglycine-generating enzyme (FGE). The generated carbonyl moiety is addressed by a bifunctional linker with a pyrazolone for a tandem Knoevenagel reaction and an azide for strain-promoted azide-alkyne cycloaddition (SPAAC). The latter reaction with a PEGylated linker containing a dibenzocyclooctyne (DBCO) for SPAAC and monomethyl auristatin E (MMAE) as the toxin provided the stable conjugates DD1-MMAE (drug-antibody ratio, DAR = 2.0) and DFc-MMAE (DAR = 4.0) with sub-nanomolar cytotoxicity against the human squamous carcinoma derived A431 cells. In vivo imaging of Alexa Fluor 647-dye conjugates in A431-xenografted mice bearing subcutaneous tumors as the SCC model revealed unspecific binding of bivalent DARPins to the ubiquitously expressed EGFR. Tumor-targeting was verified 6 h post-injection solely for DD1 and scFvFc. The total of four administrations of 6.5 mg/kg DD1-MMAE or DFc-MMAE twice weekly did not cause any sequela in mice. MMAE conjugates showed no significant anti-tumor efficacy in vivo, but a trend towards increased necrotic areas (p = 0.2213) was observed for the DD1-MMAE (n = 5).

Camelization of a murine single-domain antibody against aflatoxin B1 and its antigen-binding analysis

Aflatoxin B1 (AFB1), a highly toxic mycotoxin, always contaminated in a variety of agricultural products. Camelid variable domain of heavy chain antibody (VHH) is a noteworthy reagent in immunoassay, owing to its excellent characteristics. Immunization of camelid animals is a straightforward strategy to produce VHHs. In this study, to avoid the dependence on the large animals, the camelized, murine antibody (cVHs) against AFB1 was prepared in vitro based on the identities between murine VH and camelid VHH and then to develop an immunoassay for AFB1. A murine anti-AFB1 VH fragment (VH-2E6) was selected for camelization through replacement of conserved hydrophobic residues in framework region 2 (FR2) (cVH-FR2), point mutation at position 103 in the FR4 region (cVH-103), and CDR3-grafted with a high AFB1-affinity VHH (cVH-Nb26). The cVH-Nb26 had a yield of 5 mg/L as refolded protein expressed from Escherichia coli and 10 mg/L expressed from Pichia pastoris. Compared with anti-AFB1 single-chain fragment variable (scFv) 2E6, cVH-Nb26 performed more than 20-fold enhancement of AFB1-binding interactions. Although the AFB1-affinity of cVH-Nb26 cannot meet the application requirement in the present form, our study provides effective strategies for preparation of camelized antibody in vitro, which could be a promising immunoreagent for AFB1 detection.

A universal in silico V(D)J recombination strategy for developing humanized monoclonal antibodies

BACKGROUND

Humanization of mouse monoclonal antibodies (mAbs) is crucial for reducing their immunogenicity in humans. However, humanized mAbs often lose their binding affinities. Therefore, an in silico humanization method that can prevent the loss of the binding affinity of mAbs is needed.

METHODS

We developed an in silico V(D)J recombination platform in which we used V(D)J human germline gene sequences to design five humanized candidates of anti-tumor necrosis factor (TNF)-α mAbs (C1-C5) by using different human germline templates. The candidates were subjected to molecular dynamics simulation. In addition, the structural similarities of their complementarity-determining regions (CDRs) to those of original mouse mAbs were estimated to derive the weighted interatomic root mean squared deviation (wRMSDi) value. Subsequently, the correlation of the derived wRMSDi value with the half maximal effective concentration (EC50) and the binding affinity (KD) of the humanized anti-TNF-α candidates was examined. To confirm whether our in silico estimation method can be used for other humanized mAbs, we tested our method using the anti-epidermal growth factor receptor (EGFR) a4.6.1, anti-glypican-3 (GPC3) YP9.1 and anti-α4β1 integrin HP1/2L mAbs.

RESULTS

The R2 value for the correlation between the wRMSDi and log(EC50) of the recombinant Remicade and those of the humanized anti-TNF-α candidates was 0.901, and the R2 value for the correlation between wRMSDi and log(KD) was 0.9921. The results indicated that our in silico V(D)J recombination platform could predict the binding affinity of humanized candidates and successfully identify the high-affinity humanized anti-TNF-α antibody (Ab) C1 with a binding affinity similar to that of the parental chimeric mAb (5.13 × 10-10). For the anti-EGFR a4.6.1, anti-GPC3 YP9.1, and anti-α4β1 integrin HP1/2L mAbs, the wRMSDi and log(EC50) exhibited strong correlations (R2 = 0.9908, 0.9999, and 0.8907, respectively).

CONCLUSIONS

Our in silico V(D)J recombination platform can facilitate the development of humanized mAbs with low immunogenicity and high binding affinities. This platform can directly transform numerous mAbs with therapeutic potential to humanized or even human therapeutic Abs for clinical use.

Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics

Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies. Features obtained from molecular dynamics simulations of the full-length antibody and sequences were used for machine learning model construction. We found a k-nearest neighbors regression model with two features, spatial positive charge map on the CDRH2 and solvent-accessible surface area of hydrophobic residues on the variable fragment, gives the best performance for predicting antibody aggregation rates (r = 0.89). For the viscosity classification model, the model with the highest accuracy is a logistic regression model with two features, spatial negative charge map on the heavy chain variable region and spatial negative charge map on the light chain variable region. The accuracy and the area under precision recall curve of the classification model from validation tests are 0.86 and 0.70, respectively. In addition, we combined data from another 27 commercial mAbs to develop a viscosity predictive model. The best model is a logistic regression model with two features, number of hydrophobic residues on the light chain variable region and net charges on the light chain variable region. The accuracy and the area under precision recall curve of the classification model are 0.85 and 0.6, respectively. The aggregation rates and viscosity models can be used to predict antibody stability to facilitate pharmaceutical development.

Recombinant antibodies and their use for food immunoanalysis

Antibodies are widely employed as biorecognition elements for the detection of a plethora of compounds including food and environmental contaminants, biomarkers, or illicit drugs. They are also applied in therapeutics for the treatment of several disorders. Recent recommendations from the EU on animal protection and the replacement of animal-derived antibodies by non-animal-derived ones have raised a great controversy in the scientific community. The application of recombinant antibodies is expected to achieve a high growth rate in the years to come thanks to their versatility and beneficial characteristics in comparison to monoclonal and polyclonal antibodies, such as stability in harsh conditions, small size, relatively low production costs, and batch-to-batch reproducibility. This review describes the characteristics, advantages, and disadvantages of recombinant antibodies including antigen-binding fragments (Fab), single-chain fragment variable (scFv), and single-domain antibodies (VHH) and their application in food analysis with especial emphasis on the analysis of biotoxins, antibiotics, pesticides, and foodborne pathogens. Although the wide application of recombinant antibodies has been hampered by a number of challenges, this review demonstrates their potential for the sensitive, selective, and rapid detection of food contaminants.

Molecular Mechanisms of Cardiac Amyloidosis

Cardiac involvement has a profound effect on the prognosis of patients with systemic amyloidosis. Therapeutic methods for suppressing the production of causative proteins have been developed for ATTR amyloidosis and AL amyloidosis, which show cardiac involvement, and the prognosis has been improved. However, a method for removing deposited amyloid has not been established. Methods for reducing cytotoxicity caused by amyloid deposition and amyloid precursor protein to protect cardiovascular cells are also needed. In this review, we outline the molecular mechanisms and treatments of cardiac amyloidosis.

A comprehensive comparison between camelid nanobodies and single chain variable fragments

By the emergence of recombinant DNA technology, many antibody fragments have been developed devoid of undesired properties of natural immunoglobulins. Among them, camelid heavy-chain variable domains (VHHs) and single-chain variable fragments (scFvs) are the most favored ones. While scFv is used widely in various applications, camelid antibodies (VHHs) can serve as an alternative because of their superior chemical and physical properties such as higher solubility, stability, smaller size, and lower production cost. Here, these two counterparts are compared in structure and properties to identify which one is more suitable for each of their various therapeutic, diagnosis, and research applications.

Central Nervous System Delivery of Antibodies and Their Single-Domain Antibodies and Variable Fragment Derivatives with Focus on Intranasal Nose to Brain Administration

IgG antibodies are some of the most important biopharmaceutical molecules with a high market volume. In spite of the fact that clinical therapies with antibodies are broadly utilized in oncology, immunology and hematology, their delivery strategies and biodistribution need improvement, their limitations being due to their size and poor ability to penetrate into tissues. In view of their small size, there is a rising interest in derivatives, such as single-domain antibodies and single-chain variable fragments, for clinical diagnostic but also therapeutic applications. Smaller antibody formats combine several benefits for clinical applications and can be manufactured at reduced production costs compared with full-length IgGs. Moreover, such formats have a relevant potential for targeted drug delivery that directs drug cargo to a specific tissue or across the blood–brain barrier. In this review, we give an overview of the challenges for antibody drug delivery in general and focus on intranasal delivery to the central nervous system with antibody formats of different sizes.

Nanobodies - Little helpers unravelling intracellular signaling

The identification of diagnostic and therapeutic targets requires a comprehensive understanding of cellular processes, for which advanced technologies in biomedical research are needed. The emergence of nanobodies (Nbs) derived from antibody fragments of camelid heavy chain-only antibodies as intracellular research tools offers new possibilities to study and modulate target antigens in living cells. Here we summarize this rapidly changing field, beginning with a brief introduction of Nbs, followed by an overview of how target-specific Nbs can be generated, and introduce the selection of intrabodies as research tools. Intrabodies, by definition, are intracellular functional Nbs that target ectopic or endogenous intracellular antigens within living cells. Such binders can be applied in various formats, e.g. as chromobodies for live cell microscopy or as biosensors to decipher complex intracellular signaling pathways. In addition, protein knockouts can be achieved by target-specific Nbs, while modulating Nbs have the potential as future therapeutics. The development of fine-tunable and switchable Nb-based systems that simultaneously provide spatial and temporal control has recently taken the application of these binders to the next level.

Differences in human IgG1 and IgG4 S228P monoclonal antibodies viscosity and self-interactions: Experimental assessment and computational predictions of domain interactions

Human/humanized IgG4 antibodies have reduced effector function relative to IgG1 antibodies, which is desirable for certain therapeutic purposes. However, the developability and biophysical properties for IgG4 antibodies are not well understood. This work focuses on the head-to-head comparison of key biophysical properties, such as self-interaction and viscosity, for 14 human/humanized, and chimeric IgG1 and IgG4 S228P monoclonal antibody pairs that contain the identical variable regions. Experimental measurements showed that the IgG4 S228P antibodies have similar or higher self-interaction and viscosity than that of IgG1 antibodies in 20 mM sodium acetate, pH 5.5. We report sequence and structural drivers for the increased viscosity and self-interaction detected in IgG4 S228P antibodies through a combination of experimental data and computational models. Further, we applied and extended a previously established computational model for IgG1 antibodies to predict the self-interaction and viscosity behavior for each antibody pair, providing insight into the structural characteristics and differences of these two isotypes. Interestingly, we observed that the IgG4 S228P swapped variants, where the CH3 domain was swapped for that of an IgG1, showed reduced self-interaction behavior. These domain swapped IgG4 S228P molecules also showed reduced viscosity from experiment and coarse-grained simulations. We also observed that experimental diffusion interaction parameter (kD) values have a high correlation with computational diffusivity prediction for both IgG1 and IgG4 S228P isotypes.

Abbreviations: AHc, constant region Hamaker constant; AHv, variable region Hamaker constant; CDRs, Complementarity-determining regions; CG, Coarse-grained model; CH1, Constant heavy chain 1; CH2 Constant heavy chain 2; CH3 Constant heavy chain 3; chgCH3 Effective charge on the CH3 region; CL Constant light chain; cP, Centipoise; DLS, Dynamic light scattering; Fab, Fragment antigen-binding; Fc, Fragment crystallizable; Fv, Variable domaing; (r) Radial distribution function; H1 CDR1 of Heavy Chain; H2 CDR2 of Heavy Chain; H3 CDR3 of Heavy Chain; HVI, High viscosity index; IgG1 human immunoglobulin of IgG1 subclass; IgG4 human immunoglobulin of IgG4 subclass; kD, Diffusion interaction parameter; L1 CDR1 of Light Chain; L2 CDR2 of Light Chain; L3 CDR3 of Light Chain; mAb, Monoclonal antibody; MD, Molecular dynamics; PPI Protein–protein interactions; SCM, Spatial charge map; UP-SEC, Ultra-high-performance size-exclusion chromatography; VH, Variable domain of Heavy Chain; VL, Variable domain of Light Chain

Stress-dependent flexibility of a full-length human monoclonal antibody: Insights from molecular dynamics to support biopharmaceutical development

After several decades of advancements in drug discovery, product development of biopharmaceuticals remains a time- and resource-consuming endeavor. One of the main reasons is associated to the lack of fundamental understanding of conformational dynamics of such biologic entities, and how they respond to various stresses encountered during manufacturing. In this work, we have studied the conformational dynamics of human IgG₁κ b12 monoclonal antibody (mAb) using molecular dynamics simulations. The hundreds of nanoseconds long trajectories reveal that b12 mAb is highly flexible. Its variable domains show greater conformational fluctuations than the constant domains. Additionally, it collapses towards a more globular shape in response to thermal stress, leading to decrease in the total solvent exposed surface area and radius of gyration. This behavior is more pronounced for the deglycosylated b12 mAb, and it appears to correlate with increase in inter-domain contacts between specific regions of the antibody. Conformational fluctuations also cause temporary formation and disruption of hydrophobic and charged patches on the antibody surface, which is particularly important for the prediction of CMC properties during development phases of antibody-based biotherapeutics. The insights gained through these simulations may help the development of biologic drugs, especially with regards to manufacturing processes where antibodies may undergo significant thermal stress.

Heavy chain-only antibody genes in fish evolved to generate unique CDR3 repertoire

In addition to conventional immunoglobulin, camelids and cartilaginous fish express a special class of antibody that consists only of heavy (H) chain (HCAbs). In the holocephalan elephantfish, there are two HCAb classes, one of which has evolved surprising features. The H-chain genes in cartilaginous fish are organized as 20-200 minigenes, or clusters, each consisting of VH, 1-3 DH, JH gene segments with one set of constant region exons. We report that HHC2 (holocephalan H-chain antibody 2) evolved from IgM H-chain clusters, but its DH gene segments have diverged considerably. The three DH in HHC2 clusters are A-rich, so that one to three potential reading frames for each DH encode lysine and arginine. All three are incorporated into the rearranged VDJ, ensuring that the ligand-binding site carries multiple basic residues, as cDNA sequences demonstrate. The electropositive character in HHC2 CDR3 is accompanied by a paucity of aromatic amino acids, the latter feature at variance to the established, interactive role of tyrosine not only in ligand-binding but generally at interfaces of protein complexes. The selection for these divergent HHC2 features challenges currently accepted ideas on what determines antibody reactivity and molecular recognition.

Nanotechnology-based approaches in the fight against SARS-CoV-2

The COVID-19 pandemic caused by highly-infectious virus namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in infection of millions of individuals and deaths across the world. The need of an hour is to find the innovative solution for diagnosis, prevention, and cure of the COVID-19 disease. Nanotechnology is emerging as one of the important tool for the same. In the present review we discuss the applications of nanotechnology-based approaches that are being implemented to speed up the development of diagnostic kits for SARS-CoV-2, development of personal protective equipments, and development of therapeutics of COVID-19 especially the vaccine development.