Analysis and modeling of the variable region of camelid single-domain antibodies

Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures

Antibodies are attractive therapeutic candidates due to their ability to bind cognate antigens with high affinity and specificity. Still, the underlying molecular rules governing the antibody-antigen interface remain poorly understood, making in silico antibody design inherently difficult and keeping the discovery and design of novel antibodies a costly and laborious process. This study investigates the characteristics of antibody-antigen binding interfaces through a computational analysis of more than 850,000 atom-atom contacts from the largest reported set of antibody-antigen complexes with 1833 nonredundant, experimentally determined structures. The analysis compares binding characteristics of conventional antibodies and single-domain antibodies (sdAbs) targeting both protein- and peptide antigens. We find clear patterns in the number antibody-antigen contacts and amino acid frequencies in the paratope. The direct comparison of sdAbs and conventional antibodies helps elucidate the mechanisms employed by sdAbs to compensate for their smaller size and the fact that they harbor only half the number of complementarity-determining regions compared to conventional antibodies. Furthermore, we pinpoint antibody interface hotspot residues that are often found at the binding interface and the amino acid frequencies at these positions. These findings have direct potential applications in antibody engineering and the design of improved antibody libraries.

Single-cell 5' RNA sequencing of camelid peripheral B cells provides insights into cellular basis of heavy-chain antibody production

Camelids produce both conventional tetrameric antibodies (Abs) and dimeric heavy-chain antibodies (HCAbs). Although B cells that generate these two types of Abs exhibit distinct B cell receptors (BCRs), whether these two B cell populations differ in their phenotypes and developmental processes remains unclear. Here, we performed single-cell 5' RNA profiling of peripheral blood mononuclear cell samples from Bactrian camels before and after immunization. We characterized the functional subtypes and differentiation trajectories of circulating B cells in camels, and reconstructed single-cell BCR sequences. We found that in contrast to humans, the proportion of T-bet+ B cells was high among camelid peripheral B cells. Several marker genes of human B cell subtypes, including CD27 and IGHD, were expressed at low levels in the corresponding camel B cell subtypes. Camelid B cells expressing variable genes of HACbs (VHH) were widely present in various functional subtypes and showed highly overlapping differentiation trajectories with B cells expressing variable genes of conventional Abs (VH). After immunization, the transcriptional changes in VHH+ and VH+ B cells were largely consistent. Through structure modeling, we identified a variety of scaffold types among the reconstructed VHH sequences. Our study provides insights into the cellular context of HCAb production in camels and lays the foundation for developing single-B cell-based camelid single-domain Ab screening.

Characterization of a Novel Monoclonal Antibody with High Affinity and Specificity against Aflatoxins: A Discovery from Rosetta Antibody-Ligand Computational Simulation

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While the sensitivity and specificity of these antibodies have been extensively studied, information regarding the atomic-level docking of AFB1 (and its derivatives) with these antibodies is limited. Such information is crucial for understanding the key interactions that are required for high affinity and specificity in aflatoxin binding. First, a 3D comparative model of anti-AFB1 antibody (Ab-4B5G6) was predicted from the sequence using RosettaAntibody. We then utilized RosettaLigand to dock AFB1 onto ten homology models, producing a total of 10,000 binding modes. Interestingly, the best-scoring mode predicted strong interactions involving four sites within the heavy chain: ALA33, ASN52, HIS95, and TRP99. Importantly, these strong binding interactions exclusively involve the variable domain of the heavy chain. The best-scoring mode with AFB1 was also obtained through AF multimer combined with RosettaLigand, and two interactions at TRP and HIS were consistent with those found by Rosetta antibody-ligand computational simulation. The role of tryptophan in π interactions in antibodies was confirmed through mutation experiments, and the resulting mutant (W99A) exhibited a >1000-fold reduction in binding affinity for AFB1 and analogs, indicating the effect of tryptophan on the stability of CDR-H3 region. Additionally, we evaluated the binding of two glycolic acid-derived molecular derivatives (with impaired hydrogen bonding potential), and these derivatives (AFB2-GA and AFG2-GA) demonstrated a very weak binding affinity for Ab-4B5G6. The heavy chain was successfully isolated, and its sensitivity and specificity were consistent with those of the intact antibody. The homology models of variable heavy (VH) single-domain antibodies were established by RosettaAntibody, and the docking analysis revealed the same residues, including Ala, His, and Trp. Compared to the potential binding mode of fragment variable (FV) region, the results from a model of VH indicated that there are seven models involved in hydrophobic interaction with TYR32, which is usually referred to as polar amino acid and has both hydrophobic and hydrophilic features depending on the circumstances. Our work encompasses the entire process of Rosetta antibody-ligand computational simulation, highlighting the significance of variable heavy domain structural design in enhancing molecular interactions.

Development of novel humanized VHH synthetic libraries based on physicochemical analyses

Due to the high affinity and specificity of antibodies toward antigens, various antibody-based applications have been developed. Recently, variable antigen-binding domains of heavy-chain antibodies (VHH) have become an attractive alternative to conventional fragment antibodies due to their unique molecular characteristics. As an antibody-generating strategy, synthetic VHH libraries (including humanized VHH libraries) have been developed using distinct strategies to constrain the diversity of amino acid sequences. In this study, we designed and constructed several novel synthetic humanized VHH libraries based on biophysical analyses conducted using the complementarity determining region-grafting method and comprehensive sequence analyses of VHHs deposited in the protein data bank. We obtained VHHs from the libraries, and hit clones exhibited considerable thermal stability. We also found that VHHs from distinct libraries tended to have different epitopes. Based on our results, we propose a strategy for generating humanized VHHs with distinct epitopes toward various antigens by utilizing our library combinations.

Molecular Modeling Methods in the Development of Affine and Specific Protein-Binding Agents

High-affinity and specific agents are widely applied in various areas, including diagnostics, scientific research, and disease therapy (as drugs and drug delivery systems). It takes significant time to develop them. For this reason, development of high-affinity agents extensively utilizes computer methods at various stages for the analysis and modeling of these molecules. The review describes the main affinity and specific agents, such as monoclonal antibodies and their fragments, antibody mimetics, aptamers, and molecularly imprinted polymers. The methods of their obtaining as well as their main advantages and disadvantages are briefly described, with special attention focused on the molecular modeling methods used for their analysis and development.

Single-Domain Antibodies as Antibody-Drug Conjugates: From Promise to Practice-A Systematic Review

BACKGROUND

Antibody-drug conjugates (ADCs) represent potent cancer therapies that deliver highly toxic drugs to tumor cells precisely, thus allowing for targeted treatment and significantly reducing off-target effects. Despite their effectiveness, ADCs can face limitations due to acquired resistance and potential side effects.

OBJECTIVES

This study focuses on advances in various ADC components to improve both the efficacy and safety of these agents, and includes the analysis of several novel ADC formats. This work assesses whether the unique features of VHHs-such as their small size, enhanced tissue penetration, stability, and cost-effectiveness-make them a viable alternative to conventional antibodies for ADCs and reviews their current status in ADC development.

METHODS

Following PRISMA guidelines, this study focused on VHHs as components of ADCs, examining advancements and prospects from 1 January 2014 to 30 June 2024. Searches were conducted in PubMed, Cochrane Library, ScienceDirect and LILACS using specific terms related to ADCs and single-domain antibodies. Retrieved articles were rigorously evaluated, excluding duplicates and non-qualifying studies. The selected peer-reviewed articles were analyzed for quality and synthesized to highlight advancements, methods, payloads, and future directions in ADC research.

RESULTS

VHHs offer significant advantages for drug conjugation over conventional antibodies due to their smaller size and structure, which enhance tissue penetration and enable access to previously inaccessible epitopes. Their superior stability, solubility, and manufacturability facilitate cost-effective production and expand the range of targetable antigens. Additionally, some VHHs can naturally cross the blood-brain barrier or be easily modified to favor their penetration, making them promising for targeting brain tumors and metastases. Although no VHH-drug conjugates (nADC or nanoADC) are currently in the clinical arena, preclinical studies have explored various conjugation methods and linkers.

CONCLUSIONS

While ADCs are transforming cancer treatment, their unique mechanisms and associated toxicities challenge traditional views on bioavailability and vary with different tumor types. Severe toxicities, often linked to compound instability, off-target effects, and nonspecific blood cell interactions, highlight the need for better understanding. Conversely, the rapid distribution, tumor penetration, and clearance of VHHs could be advantageous, potentially reducing toxicity by minimizing prolonged exposure. These attributes make single-domain antibodies strong candidates for the next generation of ADCs, potentially enhancing both efficacy and safety.

Epitope Identification of an mGlu5 Receptor Nanobody Using Physics-Based Molecular Modeling and Deep Learning Techniques

The world has witnessed a revolution in therapeutics with the development of biological medicines such as antibodies and antibody fragments, notably nanobodies. These nanobodies possess unique characteristics including high specificity and modulatory activity, making them promising candidates for therapeutic applications. Identifying their binding mode is essential for their development. Experimental structural techniques are effective to get such information, but they are expensive and time-consuming. Here, we propose a computational approach, aiming to identify the epitope of a nanobody that acts as an agonist and a positive allosteric modulator at the rat metabotropic glutamate receptor 5. We employed multiple structure modeling tools, including various artificial intelligence algorithms for epitope mapping. The computationally identified epitope was experimentally validated, confirming the success of our approach. Additional dynamics studies provided further insights on the modulatory activity of the nanobody. The employed methodologies and approaches initiate a discussion on the efficacy of diverse techniques for epitope mapping and later nanobody engineering.

The role of venom proteomics and single-domain antibodies for antivenoms: Progress in snake envenoming treatment

Single-domain antibodies (sdAbs) hold promise for developing new biopharmaceuticals to treat neglected tropical diseases (NTDs), including snakebites, which are severe and occur frequently. In addition, limitations of conventional snakebite treatments, especially in terms of local action, and the global antivenom crisis incentivize the use of this biotechnological tool to design next-generation snakebite antivenoms. Conventional antivenoms for snakebite treatment are usually composed of immunoglobulin G or F(ab')2 fragments derived from the plasma of immunized animals. sdAbs, the smallest antigen-binding fragments, are derived from the variable domains of camelid heavy-chain antibodies. sdAbs may have some advantages over conventional antivenoms for local toxicity, such as better penetration into tissues due to their small size, and high solubility and affinity for venom antigens due to their unique antigen-binding loops and ability to access cryptic epitopes. We present an overview of current antivenom therapy in the context of sdAb development for toxin neutralization. Furthermore, strategies are presented for identifying snake venom's major toxins as well as for developing antisnake toxin sdAbs by employing proteomic tools for toxin neutralization.

Structural insights into the unique recognition module between α-synuclein peptide and nanobody

Nanobodies are single-domain fragments of antibodies with comparable specificity and affinity to antibodies. They are emerging as versatile tools in biology due to their relatively small size. Here, we report the crystal structure of a specific nanobody Nbα-syn01, bound to a 14 amino acid long peptide of α-synuclein (αSyn), a 140-residue protein whose aggregation is associated with Parkinson's disease. The complex structure exhibits a unique binding pattern where the αSyn peptide replaces the N-terminal region of nanobody. Recognition is mediated principally by extended main chain interaction of the αSyn peptide and specificity of the interaction lies in the central 48-52 region of αSyn peptide. Structure-guided truncation of Nbα-syn01 shows tighter binding to αSyn peptide and improved inhibition of α-synuclein aggregation. The structure of the truncated complex was subsequently determined and was indistinguishable to full length complex as the full-length form had no visible electron density for the N-terminal end. These findings reveal the molecular basis for a previously unobserved binding mode for nanobody recognition of α-synuclein, providing an explanation for the enhanced binding, and potential for an alternate framework for structure-based protein engineering of nanobodies to develop better diagnostic and therapeutic tools.

Protocol to generate fast-dissociating recombinant antibody fragments for multiplexed super-resolution microscopy

Multiplexed high-density label super-resolution microscopy image reconstruction by integrating exchangeable single-molecule localization (IRIS) enables elucidating fine structures and molecular distribution in cells and tissues. However, fast-dissociating binders are required for individual targets. Here, we present a protocol for generating antibody-based IRIS probes from existing antibody sequences. We describe steps for retrieving antibody sequences from databases. We then detail the construction, purification, and evaluation of recombinant probes after site-directed mutagenesis at the base of complementarity-determining region loops. The protocol accelerates dissociation rates without compromising the binding specificity. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2022).1.

Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens

The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeutics against a spectrum of pathologies. In cancer, immune-inspired approaches are witnessing a surge thanks to a better understanding of tumor-associated antigens and the mechanisms of their engagement or evasion from the human immune system. Here, we provide a summary of the main state-of-the-art computational approaches that are used to design antibodies and antigens, and in parallel, we review key methodologies for epitope identification for both B- and T-cell mediated responses. A special focus is devoted to the description of structure- and physics-based models, privileged over purely sequence-based approaches. We discuss the implications of novel methods in engineering biomolecules with tailored immunological properties for possible therapeutic uses. Finally, we highlight the extraordinary challenges and opportunities presented by the possible integration of structure- and physics-based methods with emerging Artificial Intelligence technologies for the prediction and design of novel antigens, epitopes, and antibodies.

VHH CDR-H3 conformation is determined by VH germline usage

VHHs or nanobodies are single antigen binding domains originating from camelid heavy-chain antibodies. They are used as diagnostic and research tools and in a variety of therapeutic molecules. Analyzing variable domain structures from llama and alpaca we found that VHHs can be classified into two large structural clusters based on their CDR-H3 conformation. Extended CDR-H3 loops protrude into the solvent, whereas kinked CDR-H3 loops fold back onto framework regions. Both major families have distinct properties in terms of their CDR-H3 secondary structure, how their CDR-H3 interacts with the framework region and how they bind to antigens. We show that the CDR-H3 conformation of VHHs correlates with the germline from which the antibodies are derived: IGHV3-3 derived antibodies almost exclusively adopt a kinked CDR-H3 conformation while the CDR-H3 adopts an extended structure in most IGHV3S53 derived antibodies. We do not observe any bias stemming from V(D)J recombination in llama immune repertoires, suggesting that the correlation is the result of selection processes during B-cell development. Our findings demonstrate a previously undescribed impact of germline usage on antigen interaction and contribute to a better understanding on how properties of the antibody framework shape the immune repertoire.

A comparison of the binding sites of antibodies and single-domain antibodies

Antibodies are the largest class of biotherapeutics. However, in recent years, single-domain antibodies have gained traction due to their smaller size and comparable binding affinity. Antibodies (Abs) and single-domain antibodies (sdAbs) differ in the structures of their binding sites: most significantly, single-domain antibodies lack a light chain and so have just three CDR loops. Given this inherent structural difference, it is important to understand whether Abs and sdAbs are distinguishable in how they engage a binding partner and thus, whether they are suited to different types of epitopes. In this study, we use non-redundant sequence and structural datasets to compare the paratopes, epitopes and antigen interactions of Abs and sdAbs. We demonstrate that even though sdAbs have smaller paratopes, they target epitopes of equal size to those targeted by Abs. To achieve this, the paratopes of sdAbs contribute more interactions per residue than the paratopes of Abs. Additionally, we find that conserved framework residues are of increased importance in the paratopes of sdAbs, suggesting that they include non-specific interactions to achieve comparable affinity. Furthermore, the epitopes of sdAbs are only marginally less accessible than those of Abs: we posit that this may be explained by differences in the orientation and compaction of sdAb and Ab CDR-H3 loops. Overall, our results have important implications for the engineering and humanization of sdAbs, as well as the selection of the best modality for targeting a particular epitope.

Bypassing the Need for Cell Permeabilization: Nanobody CDR3 Peptide Improves Binding on Living Bacteria

Membrane interaction constitutes to be an essential parameter in the mode of action of entities such as proteins, as well as cell-penetrating and antimicrobial peptides, resulting in noninvasive or lytic activities depending on the membrane compositions and interactions. Recently, a nanobody able to interact with the top priority, multidrug-resistant bacterial pathogen Acinetobacter baumannii was discovered, although binding took place with fixed cells only. To potentially overcome this limitation, linear peptides corresponding to the complementarity-determining regions (CDR) were synthesized and fluorescently labeled. Microscopy data indicated clear membrane interactions of the CDR3 sequence with living A. baumannii cells, indicating both the importance of the CDR3 as part of the parent nanobody paratope and the improved binding ability and thus avoiding the need for permeabilization of the cells. In addition, cyclization of the peptide with an additionally introduced rigidifying 1,2,3-triazole bridge retains its binding ability while proteolytically protecting the peptide. Overall, this study resulted in the discovery of novel peptides binding a multidrug-resistant pathogen.

Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies

Antibodies have the capacity to bind a diverse set of antigens, and they have become critical therapeutics and diagnostic molecules. The binding of antibodies is facilitated by a set of six hypervariable loops that are diversified through genetic recombination and mutation. Even with recent advances, accurate structural prediction of these loops remains a challenge. Here, we present IgFold, a fast deep learning method for antibody structure prediction. IgFold consists of a pre-trained language model trained on 558 million natural antibody sequences followed by graph networks that directly predict backbone atom coordinates. IgFold predicts structures of similar or better quality than alternative methods (including AlphaFold) in significantly less time (under 25 s). Accurate structure prediction on this timescale makes possible avenues of investigation that were previously infeasible. As a demonstration of IgFold's capabilities, we predicted structures for 1.4 million paired antibody sequences, providing structural insights to 500-fold more antibodies than have experimentally determined structures.

The validation of artificial anti-monkeypox antibodies by in silico and experimental approaches

As a result of smallpox immunization programs that ended more than 40 years ago, a significant portion of the world's population is not immune. Moreover, due to the lack of anti-monkeypox drugs and vaccines against monkeypox, the spread of this virus may be the beginning of another challenge. In this study, novel antibodies against monkeypox virus were modeled based on a heavy chain of human antibody and a small peptide fragment. Docking of modeled antibodies with C19L protein showed the range of docking energy, and root-mean-square deviation (RMSD) was from -124 to -154 kcal/mL and 4-6 angstrom, respectively. Also, docking of modeled antibodies-C19L complex with gamma Fc receptor type I illustrated the range of docking energy, and RMSD was from -132 to -155 kcal/ml and 5-7 angstrom, respectively. Moreover, molecular dynamics simulation showed that antibody 62 had the highest stability with the lowest energy level and RMSD. Interestingly, no modeled antibodies had immunogenicity, allergenicity, and toxicity. Although all of them had good stability, only antibodies 25, 28, 54, and 62 had a half-life of >10 h. Moreover, the interaction between C19L protein and anti-C19L antibodies (wild-type and synthetic) was evaluated by the SPR method. We found that K_D in synthetic antibodies was lower than wild antibody. In terms of δH°, TδS°, and δG°, the results were consistent with binding parameters. Here, the lowest value of thermodynamic parameters was obtained for antibody 62. These data show that the synthetic antibodies, especially antibody 62, had a higher affinity than the wild-type antibody.

Application Progress of the Single Domain Antibody in Medicine

The camelid-derived single chain antibody (sdAb), also termed VHH or nanobody, is a unique, functional heavy (H)-chain antibody (HCAb). In contrast to conventional antibodies, sdAb is a unique antibody fragment consisting of a heavy-chain variable domain. It lacks light chains and a first constant domain (CH1). With a small molecular weight of only 12~15 kDa, sdAb has a similar antigen-binding affinity to conventional Abs but a higher solubility, which exerts unique advantages for the recognition and binding of functional, versatile, target-specific antigen fragments. In recent decades, with their unique structural and functional features, nanobodies have been considered promising agents and alternatives to traditional monoclonal antibodies. As a new generation of nano-biological tools, natural and synthetic nanobodies have been used in many fields of biomedicine, including biomolecular materials, biological research, medical diagnosis and immune therapies. This article briefly overviews the biomolecular structure, biochemical properties, immune acquisition and phage library construction of nanobodies and comprehensively reviews their applications in medical research. It is expected that this review will provide a reference for the further exploration and unveiling of nanobody properties and function, as well as a bright future for the development of drugs and therapeutic methods based on nanobodies.

Structural Classification of CDR-H3 in Single-Domain VHH Antibodies

The immune systems protect vertebrates from foreign molecules or antigens, and antibodies are important mediators of this system. The sequences and structural features of antibodies vary depending on species. Many of antibodies from vertebrates, including camelids, have both heavy and light chain variable domains, but camelids also have antibodies that lack the light chains. In antibodies that lack light chains, the C-terminal variable region is called the V_HH domain. Antibodies recognize antigens through six complementarity-determining regions (CDRs). The third CDR of the heavy chain (CDR-H3) is at the center of the antigen-binding site and is diverse in terms of sequence and structure. Due to the importance of antibodies in basic science as well as in medical applications, there have been many studies of CDR-H3s of antibodies that possess both light and heavy chains. However, nature of CDR-H3s of single-domain V_HH antibodies is less well studied. In this chapter, we describe current knowledge of sequence-structure-function correlations of single-domain V_HH antibodies with emphasis on CDR-H3. Based on the 370 crystal structures in the Protein Data Bank, we also attempt structural classification of CDR-H3 in single-domain V_HH antibodies and discuss lessons learned from the ever-increasing number of the structures.

Molecular basis for thermal stability and affinity in a VHH: Contribution of the framework region and its influence in the conformation of the CDR3

The camelid single domain antibody, referred to VHH or Nanobody, is considered a versatile tool for various biotechnological and clinical applications because of its favorable biophysical properties. To take advantage of these characteristics and for its application in biotechnology and therapy, research on VHH engineering is currently vigorously conducted. To humanize a camelid VHH, we performed complementarity determining region (CDR) grafting using a humanized VHH currently in clinical trials, and investigated the effects of these changes on the biophysical properties of the resulting VHH. The chimeric VHH exhibited a significant decrease in affinity and thermal stability and a large conformational change in the CDR3. To elucidate the molecular basis for these changes, we performed mutational analyses on the framework regions revealing the contribution of individual residues within the framework region. It is demonstrated that the mutations resulted in the loss of affinity and lower thermal stability, revealing the significance of bulky residues in the vicinity of the CDR3, and the importance of intramolecular interactions between the CDR3 and the framework-2 region. Subsequently, we performed back-mutational analyses on the chimeric VHH. Back-mutations resulted in an increase of the thermal stability and affinity. These data suggested that back-mutations restored the intramolecular interactions, and proper positioning and/or dynamics of the CDR3, resulting in the gain of thermal stability and affinity. These observations revealed the molecular contribution of the framework region on VHHs and further designability of the framework region of VHHs without modifying the CDRs.

Engineered fast-dissociating antibody fragments for multiplexed super-resolution microscopy

Image reconstruction by integrating exchangeable single-molecule localization (IRIS) achieves multiplexed super-resolution imaging by high-density labeling with fast exchangeable fluorescent probes. However, previous methods to develop probes for individual targets required a great amount of time and effort. Here, we introduce a method for generating recombinant IRIS probes with a new mutagenesis strategy that can be widely applied to existing antibody sequences. Several conserved tyrosine residues at the base of complementarity-determining regions were identified as candidate sites for site-directed mutagenesis. With a high probability, mutations at candidate sites accelerated the off rate of recombinant antibody-based probes without compromising specific binding. We were able to develop IRIS probes from five monoclonal antibodies and three single-domain antibodies. We demonstrate multiplexed localization of endogenous proteins in primary neurons that visualizes small synaptic connections with high binding density. It is now practically feasible to generate fast-dissociating fluorescent probes for multitarget super-resolution imaging.

NanoNet: Rapid and accurate end-to-end nanobody modeling by deep learning

Antibodies are a rapidly growing class of therapeutics. Recently, single domain camelid VHH antibodies, and their recognition nanobody domain (Nb) appeared as a cost-effective highly stable alternative to full-length antibodies. There is a growing need for high-throughput epitope mapping based on accurate structural modeling of the variable domains that share a common fold and differ in the Complementarity Determining Regions (CDRs). We develop a deep learning end-to-end model, NanoNet, that given a sequence directly produces the 3D coordinates of the backbone and Cβ atoms of the entire VH domain. For the Nb test set, NanoNet achieves 3.16Å average RMSD for the most variable CDR3 loops and 2.65Å, 1.73Å for the CDR1, CDR2 loops, respectively. The accuracy for antibody VH domains is even higher: 2.38Å RMSD for CDR3 and 0.89Å, 0.96Å for the CDR1, CDR2 loops, respectively. NanoNet run times allow generation of ∼1M nanobody structures in less than 4 hours on a standard CPU computer enabling high-throughput structure modeling. NanoNet is available at GitHub: https://github.com/dina-lab3D/NanoNet.

Coevolved Canonical Loops Conformations of Single-Domain Antibodies: A Tale of Three Pockets Playing Musical Chairs

Single-domain antibodies (sdAbs) are a promising class of biotherapeutics with unique structural traits within their paratope region. The distribution of canonical conformations explored by their complementarity determining region (CDR) loops differs to some extent from conventional two-chain Fv fragments of monoclonal antibodies (mAbs). In this study, we explored in detail the canonical structures of sdAb CDR-H1 and CDR-H2 loops and compared those with mAbs from the IGHV3 and IGHV1 gene families. We surveyed the antibody structures catalogued in SAbDab and clustered the CDR canonical loops in Cartesian space. While most of the sdAb clusters were sub-populations of previously defined canonical Fv conformations of CDR-H1 and CDR-H2, our stricter clustering approach defined narrower clusters in sequence-space. Meticulous visual inspection of sub-populations allowed a clearer understanding of sequence-structure relationships. The packing densities within structural pockets contacted by CDR-H1 and CDR-H2 canonical conformations were analyzed on the premise that these pockets cannot be left vacant as they would leave exposed supportive hydrophobic residues. The fine resolution of the canonical clusters defined here revealed unique signatures within these pockets, including distinct structural complementarities between CDR-H1 and CDR-H2 canonical clusters, which could not be perceived with the previous coarser clusters. We highlight examples where a single residue change in CDR-H1 sequence is sufficient to induce a dramatic population shift in CDR-H2 conformation. This suggests that preferences in combining CDR-H1 and CDR-H2 emerged naturally during antibody evolution, leading to preferred sets of conserved amino acids at key positions in the framework as well as within the CDR loops. We outline a game of musical chairs that is necessary to maintain the integrity of the antibody structures that arose during evolution. Our study also provides refined CDR-H1 and CDR-H2 structural templates for sdAb homology modeling that could be leveraged for improved antibody design.

VHH Structural Modelling Approaches: A Critical Review

VHH, i.e., VH domains of camelid single-chain antibodies, are very promising therapeutic agents due to their significant physicochemical advantages compared to classical mammalian antibodies. The number of experimentally solved VHH structures has significantly improved recently, which is of great help, because it offers the ability to directly work on 3D structures to humanise or improve them. Unfortunately, most VHHs do not have 3D structures. Thus, it is essential to find alternative ways to get structural information. The methods of structure prediction from the primary amino acid sequence appear essential to bypass this limitation. This review presents the most extensive overview of structure prediction methods applied for the 3D modelling of a given VHH sequence (a total of 21). Besides the historical overview, it aims at showing how model software programs have been shaping the structural predictions of VHHs. A brief explanation of each methodology is supplied, and pertinent examples of their usage are provided. Finally, we present a structure prediction case study of a recently solved VHH structure. According to some recent studies and the present analysis, AlphaFold 2 and NanoNet appear to be the best tools to predict a structural model of VHH from its sequence.

Construction of a Humanized Artificial VHH Library Reproducing Structural Features of Camelid VHHs for Therapeutics

A variable domain of heavy chain antibody (VHH) has different binding properties than conventional antibodies. Conventional antibodies prefer binding to the convex portion of the antigen, whereas VHHs prefer epitopes, such as crevices and clefts on the antigen. Therefore, developing candidates with the binding characteristics of camelid VHHs is important. Thus, To this end, a synthetic VHH library that reproduces the structural properties of camelid VHHs was constructed. First, the characteristics of VHHs were classified according to the paratope formation based on crystal structure analyses of the complex structures of VHHs and antigens. Then, we classified 330 complementarity-determining region 3 (CDR3) structures of VHHs from the Protein Data Bank (PDB) into three loop structures: Upright, Half-Roll, and Roll. Moreover, these structures depended on the number of amino acid residues within CDR3. Furthermore, in the Upright loops, several amino acid residues in the FR2 are involved in the paratope formation, along with CDR3, suggesting that the FR2 design in the synthetic library is important. A humanized synthetic VHH library, comprising two sub-libraries, Upright and Roll, was constructed and named PharmaLogical. A validation study confirmed that our PharmaLogical library reproduces VHHs with the characteristics of the paratope formation of the camelid VHHs, and shows good performance in VHH screening.

INDI-integrated nanobody database for immunoinformatics

Nanobodies, a subclass of antibodies found in camelids, are versatile molecular binding scaffolds composed of a single polypeptide chain. The small size of nanobodies bestows multiple therapeutic advantages (stability, tumor penetration) with the first therapeutic approval in 2018 cementing the clinical viability of this format. Structured data and sequence information of nanobodies will enable the accelerated clinical development of nanobody-based therapeutics. Though the nanobody sequence and structure data are deposited in the public domain at an accelerating pace, the heterogeneity of sources and lack of standardization hampers reliable harvesting of nanobody information. We address this issue by creating the Integrated Database of Nanobodies for Immunoinformatics (INDI, http://naturalantibody.com/nanobodies). INDI collates nanobodies from all the major public outlets of biological sequences: patents, GenBank, next-generation sequencing repositories, structures and scientific publications. We equip INDI with powerful nanobody-specific sequence and text search facilitating access to >11 million nanobody sequences. INDI should facilitate development of novel nanobody-specific computational protocols helping to deliver on the therapeutic promise of this drug format.

Humanization of Camelid Single-Domain Antibodies

Humanization of therapeutic antibodies derived from animal immunizations is often required to minimize immunogenicity risks in humans, which can cause potentially harmful and serious side effects and reduce antibody efficacy. Humanization is typically applied to conventional monoclonal antibodies derived in rodents as well as single-domain antibodies isolated from camelids and sharks (VHHs and VNARs). A streamlined protocol is described here for sequence humanization of camelid VHHs, which represent a promising biotherapeutic format with many desirable attributes. From human framework selection and complementarity-determining region grafting strategies to empirical scoring for prioritization of back-mutations, step-by-step instructions, and templates are provided along with bioinformatics resources to assist each step of the humanization process. Alternative approaches, warnings, and caveats are also presented.

Downsizing antibodies: Towards complementarity-determining region (CDR)-based peptide mimetics

Monoclonal antibodies emerged as an important therapeutic drug class with remarkable specificity and binding affinity. Nonetheless, these heterotetrameric immunoglobulin proteins come with high manufacturing and therapeutic costs which can take extraordinary proportions, besides other limitations such as their limited in cellulo access imposed by their molecular size (ca. 150 kDa). These drawbacks stimulated the development of downsized functional antibody fragments (ca. 15-50 kDa), together with smaller synthetic peptides (ca. 1-3 kDa) derived from the antibodies' crucial complementarity-determining regions (CDR). Despite the general lack of success in the literal translation of CDR loops in peptide mimetics, rational structure-based and computational approaches have shown their potential for obtaining functional CDR-based peptide mimetics. In this review, we describe the efforts made in the development of antibody and nanobody paratope-derived peptide mimetics with particular focus on the used design strategies, in addition to highlighting the challenges associated with their development.

High-resolution structure of the vWF A1 domain in complex with caplacizumab, the first nanobody-based medicine for treating acquired TTP

von Willebrand factor (vWF) is a huge oligomeric glycoprotein involved in blood homeostasis. However, this protein is also implicated in acquired thrombotic thrombocytopenic purpura (TTP). The blocking of its binding with platelets has been recognized as an attractive therapeutic strategy for treating acquired TTP. Caplacizumab, a bivalent single-domain antibody (VHH), is the first FDA-approved nanobody drug against vWF for the treatment of acquired TTP. Here, we describe the crystal structure of the A1 domain of vWF in complex with the caplacizumab nanobody at the resolution of 1.60 Å. This structure elucidates the precise epitope and binding mode of caplacizumab. Unexpectedly, caplacizumab binds to the bottom face of the vWF A1 domain and does not create any steric clash with platelet-receptor glycoprotein Ib (GPIb) bound to vWF. However, its binding can stabilize the different conformation within the N-terminus and α1β2 loop from the GPIb bound structure, suggesting that the mechanisms of caplacizumab would not be the direct competition of GPIb binding to vWF A1 domain but the conformational arrestment of vWF in an inappropriate state to platelet adhesion. This high-resolution structure would provide helpful information for the design of improved anti-vWF therapeutics for the treatment of acquired TTP.

Development of a platform process for the production and purification of single-domain antibodies

Single‐domain antibodies (sdAbs) offer the affinity and therapeutic value of conventional antibodies, with increased stability and solubility. Unlike conventional antibodies, however, sdAbs do not benefit from a platform manufacturing process. While successful production of a variety of sdAbs has been shown in numerous hosts, purification methods are often molecule specific or require affinity tags, which generally cannot be used in clinical manufacturing due to regulatory concerns. Here, we have developed a broadly applicable production and purification process for sdAbs in Komagataella phaffii (Pichia pastoris) and demonstrated the production of eight different sdAbs at a quality appropriate for nonclinical studies. We developed a two‐step, integrated purification process without the use of affinity resins and showed that modification of a single process parameter, pH of the bridging buffer, was required for the successful purification of a variety of sdAbs. Further, we determined that this parameter can be predicted based only on the biophysical characteristics of the target molecule. Using these methods, we produced nonclinical quality sdAbs as few as 5 weeks after identifying the product sequence. Nonclinical studies of three different sdAbs showed that molecules produced using our platform process conferred protection against viral shedding of rotavirus or H1N1 influenza and were equivalent to similar molecules produced in Escherichia coli and purified using affinity tags.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Integrative proteomics identifies thousands of distinct, multi-epitope, and high-affinity nanobodies

The antibody immune response is essential for the survival of mammals. However, we still lack a systematic understanding of the antibody repertoire. Here, we developed a proteomic strategy to survey, at an unprecedented scale, the landscape of antigen-engaged, circulating camelid heavy-chain antibodies, whose minimal binding fragments are called VHH antibodies or nanobodies. The sensitivity and robustness of this approach were validated with three antigens spanning orders of magnitude in immune responses; thousands of distinct, high-affinity nanobody families were reliably identified and quantified. Using high-throughput structural modeling, cross-linking mass spectrometry, mutagenesis, and deep learning, we mapped and analyzed the epitopes of >100,000 antigen-nanobody complexes. Our results revealed a surprising diversity of ultrahigh-affinity camelid nanobodies for specific antigen binding on various dominant epitope clusters. Nanobodies utilize both shape and charge complementarity to enable highly selective antigen binding. Interestingly, we found that nanobody-antigen binding can mimic conserved intracellular protein-protein interactions. A record of this paper's Transparent Peer Review process is included in the Supplemental information.

Structure prediction, molecular simulations of RmlD from Mycobacterium tuberculosis, and interaction studies of Rhodanine derivatives for anti-tuberculosis activity

Tuberculosis is the most dangerous disease causing maximum deaths than any other, caused by single infectious agent. Due to multidrug resistant of Mycobacterium tuberculosis strains, there is a need of new drugs and drug targets. In this work, we have selected RmlD (α-dTDP-6-deoxy-lyxo-4-hexulose reductase) in the dTDP Rhamnose pathway as drug target to control tuberculosis using Rhodanine analogues. In order to study interaction of RmlD with Rhodanine analogues, a three-dimensional model based on crystal structures such as 1VLO from Clostridium, 1KBZ from Salmonella typhimurium, and 2GGS from Sulfolobus was generated using Modeller 9v7. The modeled structure reliability has been checked using programs such as Procheck, What if, Prosa, Verify 3D, and Errat. In an attempt to find new inhibitors for RmlD enzyme, docking studies were done with a series of Rhodanine and its analogues. Detailed analysis of enzyme-inhibitor interactions identified specific key residues, SER5, VAL9, ILE51, HIS54, and GLY55 which were important in forming hydrogen bonds in binding affinity. Homology modeling and docking studies on RmlD model provided valuable insight information for designing better inhibitors as novel anti-tuberculosis drugs by rational method.

Plant systemic acquired resistance compound salicylic acid as a potent inhibitor against SCF (SKP1-CUL1-F-box protein) mediated complex in Fusarium oxysporum by homology modeling and molecular dynamics simulations

Fusarium oxysporum causes significant economic losses in many crop plants by causing root rot, necrosis, and wilting symptoms. Homology and molecular dynamics studies are promising tools for the detection in F. oxysporum of the systemic resistance compound, salicylic acid, for control of the SKP1-CUL1-F-box protein complex. The structure of SKP1-CUL1-F-box subunit Skp1 from F. oxysporum is produced by Modeler 9v7 for the conduct of docking studies. The Skp1 structure is based on the yeast Cdc4/Skp1 (PDB ID: 3MKS A) crystal structure collected by the Protein data bank. Applying molecular dynamic model simulation methods to the final predicted structure and further evaluated by 3D and PROCHECK test programmers, the final model is verified to be accurate. Applying GOLD 3.0.1, SCF Complex Skp1 is used to prevent stress-tolerant operation. The SKP1-CUL1-F-box model is predicted to be stabilized and tested as a stable docking structure. The predicted model of the SCF structure has been stabilized and confirmed to be a reliable structure for docking studies. The results indicated that GLN8, LYS9, VAL10, TRP11, GLU48, ASN49 in SCF complex are important determinant residues in binding as they have strong hydrogen bonding with salicylic acid, which showed best docking results with SKP1-CUL1-F-box complex subunit Skp1 with docking score 25.25KJ/mol. Insilco studies have been used to determine the mode of action of salicylic acid for Fusarium control. Salicylic acid hinders the SKP1-CUL1-F-box complex, which is important in protein-like interactions through hydrogen bodings. Results from docking studies have shown that the best energy for SKP1-CUL1-F-box was salicylic acid.Communicated by Ramaswamy H. Sarma.

Camelid-derived single-chain antibodies in hemostasis: Mechanistic, diagnostic, and therapeutic applications

Hemostasis is a complex process involving the concerted action of molecular and vascular components. Its basic understanding as well as diagnostic and therapeutic aspects have greatly benefited from the use of monoclonal antibodies. Interestingly, camelid-derived single-domain antibodies (sdAbs), also known as VHH or nanobodies, have become available during the previous 2 decades as alternative tools in this regard. Compared to classic antibodies, sdAbs are easier to produce and their small size facilitates their engineering and functionalization. It is not surprising, therefore, that sdAbs are increasingly used in hemostasis-related research. In addition, they have the capacity to recognize unique epitopes unavailable to full monoclonal antibodies. This property can be used to develop novel diagnostic tests identifying conformational variants of hemostatic proteins. Examples include sdAbs that bind active but not globular von Willebrand factor or free factor VIIa but not tissue factor-bound factor VIIa. Finally, sdAbs have a high therapeutic potential, exemplified by caplacizumab, a homodimeric sdAb targeting von Willebrand factor that is approved for the treatment of thrombotic thrombocytopenic purpura. In this review, the various applications of sdAbs in thrombosis and hemostasis-related research, diagnostics, and therapeutic strategies will be discussed.

Computational approaches to therapeutic antibody design: established methods and emerging trends

Antibodies are proteins that recognize the molecular surfaces of potentially noxious molecules to mount an adaptive immune response or, in the case of autoimmune diseases, molecules that are part of healthy cells and tissues. Due to their binding versatility, antibodies are currently the largest class of biotherapeutics, with five monoclonal antibodies ranked in the top 10 blockbuster drugs. Computational advances in protein modelling and design can have a tangible impact on antibody-based therapeutic development. Antibody-specific computational protocols currently benefit from an increasing volume of data provided by next generation sequencing and application to related drug modalities based on traditional antibodies, such as nanobodies. Here we present a structured overview of available databases, methods and emerging trends in computational antibody analysis and contextualize them towards the engineering of candidate antibody therapeutics.

Novel sampling strategies and a coarse-grained score function for docking homomers, flexible heteromers, and oligosaccharides using Rosetta in CAPRI rounds 37-45

Critical Assessment of PRediction of Interactions (CAPRI) rounds 37 through 45 introduced larger complexes, new macromolecules, and multistage assemblies. For these rounds, we used and expanded docking methods in Rosetta to model 23 target complexes. We successfully predicted 14 target complexes and recognized and refined near-native models generated by other groups for two further targets. Notably, for targets T110 and T136, we achieved the closest prediction of any CAPRI participant. We created several innovative approaches during these rounds. Since round 39 (target 122), we have used the new RosettaDock 4.0, which has a revamped coarse-grained energy function and the ability to perform conformer selection during docking with hundreds of pregenerated protein backbones. Ten of the complexes had some degree of symmetry in their interactions, so we tested Rosetta SymDock, realized its shortcomings, and developed the next-generation symmetric docking protocol, SymDock2, which includes docking of multiple backbones and induced-fit refinement. Since the last CAPRI assessment, we also developed methods for modeling and designing carbohydrates in Rosetta, and we used them to successfully model oligosaccharide-protein complexes in round 41. Although the results were broadly encouraging, they also highlighted the pressing need to invest in (a) flexible docking algorithms with the ability to model loop and linker motions and in (b) new sampling and scoring methods for oligosaccharide-protein interactions.

In Silico Studies on Anti-Stress Compounds of Ethanolic Root Extract of Hemidesmus indicus L

BACKGROUND

Alternative medicine is available for those diseases which cannot be treated by conventional medicine. Ayurveda and herbal medicines are important alternative methods in which the treatment is done with extracts of different medicinal plants. This work is concerned with the evaluation of anti-stress bioactive compounds from the ethanolic root extract of Hemidesmus indicus.

METHODS

Gas chromatography and Mass Spectrum studies are used to identify the compounds present in the ethanolic extract based on the retention time, area. In order to perform docking studies, Vasopressin model is generated using modeling by Modeller 9v7. Vasopressin structure is developed based on the crystal structure of neurophysin-oxytocin from Bos taurus (PDB ID: 1NPO_A) collected from the PDB data bank. Using molecular dynamics simulation methods, the final predicted structure is obtained and further analyzed by verifying 3D and PROCHECK programs, confirmed that the final model is reliable. The identified compounds are docked to vasopressin for the prediction of anti-stress activity using GOLD 3.0.1 software.

RESULTS

The predicted model of Vasopressin structure is stabilized and confirmed that it is a reliable structure for docking studies. The results indicated ARG4, THR7, ASP9, ASP26, ALA32, ALA 80 in Vasopressin are important determinant residues in binding as they have strong hydrogen bonding with phytocompounds. Among the 21 phytocompounds identified and docked, molecule Deoxiinositol, pentakis- O-(trimethylsilyl) showed the best docking results with Vasopressin.

CONCLUSION

The identified compounds were used for anti-stress activity by insilico method with Vasopressin which plays an important role in causing stress and hence selected for inhibitory studies with phytocompounds. The phytocompounds are inhibiting vasopressin through hydrogen bodings and are important in protein-ligand interactions. Docking results showed that out of twenty-one compounds, Deoxiinositol, pentakis-O-(trimethylsilyl) showed best docking energy to the Vasopressin.

Macromolecular modeling and design in Rosetta: recent methods and frameworks

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.

Generation of synthetic nanobodies against delicate proteins

Here, we provide a protocol to generate synthetic nanobodies, known as sybodies, against any purified protein or protein complex within a 3-week period. Unlike methods that require animals for antibody generation, sybody selections are carried out entirely in vitro under controlled experimental conditions. This is particularly relevant for the generation of conformation-specific binders against labile membrane proteins or protein complexes and allows selections in the presence of non-covalent ligands. Sybodies are especially suited for cases where binder generation via immune libraries fails due to high sequence conservation, toxicity or insufficient stability of the target protein. The procedure entails a single round of ribosome display using the sybody libraries encoded by mRNA, followed by two rounds of phage display and binder identification by ELISA. The protocol is optimized to avoid undesired reduction in binder diversity and enrichment of non-specific binders to ensure the best possible selection outcome. Using the efficient fragment exchange (FX) cloning method, the sybody sequences are transferred from the phagemid to different expression vectors without the need to amplify them by PCR, which avoids unintentional shuffling of complementary determining regions. Using quantitative PCR (qPCR), the efficiency of each selection round is monitored to provide immediate feedback and guide troubleshooting. Our protocol can be carried out by any trained biochemist or molecular biologist using commercially available reagents and typically gives rise to 10-30 unique sybodies exhibiting binding affinities in the range of 500 pM-500 nM.

Discrete analysis of camelid variable domains: sequences, structures, and in-silico structure prediction

Antigen binding by antibodies requires precise orientation of the complementarity- determining region (CDR) loops in the variable domain to establish the correct contact surface. Members of the family Camelidae have a modified form of immunoglobulin gamma (IgG) with only heavy chains, called Heavy Chain only Antibodies (HCAb). Antigen binding in HCAbs is mediated by only three CDR loops from the single variable domain (V_HH) at the N-terminus of each heavy chain. This feature of the V_HH, along with their other important features, e.g., easy expression, small size, thermo-stability and hydrophilicity, made them promising candidates for therapeutics and diagnostics. Thus, to design better V_HH domains, it is important to thoroughly understand their sequence and structure characteristics and relationship. In this study, sequence characteristics of V_HH domains have been analysed in depth, along with their structural features using innovative approaches, namely a structural alphabet. An elaborate summary of various studies proposing structural models of V_HH domains showed diversity in the algorithms used. Finally, a case study to elucidate the differences in structural models from single and multiple templates is presented. In this case study, along with the above-mentioned aspects of V_HH, an exciting view of various factors in structure prediction of V_HH, like template framework selection, is also discussed.

Isolation and structural characterization of a Zn2+-bound single-domain antibody against NorC, a putative multidrug efflux transporter in bacteria

Single-chain antibodies from camelids have served as powerful tools ranging from diagnostics and therapeutics to crystallization chaperones meant to study protein structure and function. In this study, we isolated a single-chain antibody from an Indian dromedary camel (ICab) immunized against a bacterial 14TM helix transporter, NorC, from Staphylococcus aureus We identified this antibody in a yeast display screen built from mononuclear cells isolated from the immunized camel and purified the antibody from Escherichia coli after refolding it from inclusion bodies. The X-ray structure of the antibody at 2.15 Å resolution revealed a unique feature within its CDR3 loop, which harbors a Zn2+-binding site that substitutes for a loop-stabilizing disulfide bond. We performed mutagenesis to compromise the Zn2+-binding site and observed that this change severely hampered antibody stability and its ability to interact with the antigen. The lack of bound Zn2+ also made the CDR3 loop highly flexible, as observed in all-atom simulations. Using confocal imaging of NorC-expressing E. coli spheroplasts, we found that the ICab interacts with the extracellular surface of NorC. This suggests that the ICab could be a valuable tool for detecting methicillin-resistant S. aureus strains that express efflux transporters such as NorC in hospital and community settings.

Designing, docking and molecular dynamics simulation studies of novel cloperastine analogues as anti-allergic agents: homology modeling and active site prediction for the human histamine H1 receptor

The present study predicts a three-dimensional model for the histamine H1 receptor and the design of antihistamine inhibitors using cloperastine as the core molecule by docking studies. In this work, we predicted a three-dimensional structure of the histamine H1 receptor using the MODELLER9V7 software. The protein structure was developed based on the crystal structure of the histamine H1 receptor, the lysozyme chimera of Escherichia virus T4 (PDB ID: 3RZE_A) target collected from the PDB data bank. Using molecular dynamics simulation methods, the final predicted structure is obtained and further analyzed by VERIFY3D and PROCHECK programs, confirming that the final model is reliable. The drug derivatives of cloperastine were designed and docking was performed with the designed ligands along with the drug. The predicted model of the histamine H1 receptor structure is stable and confirms that it is a reliable structure for docking studies. The results indicate that MET 183, THR 184 and ILE 187 in the histamine H1 receptor are important determinant residues for binding as they have strong hydrogen bonding with cloperastine derivatives. The drug derivatives were docked to the histamine H1 receptor protein by hydrogen bonding interactions and these interactions played an important role in the binding studies. The molecule 1-{2-[(4-chlorophenyl) (phenyl) methoxy] ethyl}-4-methylenepiperidine showed the best docking results with the histamine H1 receptor. The docking results predicted the best compounds, which may act as better drugs than cloperastine and in the future, these may be developed for anti-allergy therapy.

The present study predicts a three-dimensional model for the histamine H1 receptor and the design of antihistamine inhibitors using cloperastine as the core molecule by docking studies.

Structural and thermodynamic basis for the recognition of the substrate-binding cleft on hen egg lysozyme by a single-domain antibody

Single-domain antibodies (VHHs or nanobodies), developed from heavy chain-only antibodies of camelids, are gaining attention as next-generation therapeutic agents. Despite their small size, the high affinity and specificity displayed by VHHs for antigen molecules rival those of IgGs. How such small antibodies achieve that level of performance? Structural studies have revealed that VHHs tend to recognize concave surfaces of their antigens with high shape-complementarity. However, the energetic contribution of individual residues located at the binding interface has not been addressed in detail, obscuring the actual mechanism by which VHHs target the concave surfaces of proteins. Herein, we show that a VHH specific for hen egg lysozyme, D3-L11, not only displayed the characteristic binding of VHHs to a concave region of the surface of the antigen, but also exhibited a distribution of energetic hot-spots like those of IgGs and conventional protein-protein complexes. The highly preorganized and energetically compact interface of D3-L11 recognizes the concave epitope with high shape complementarity by the classical lock-and-key mechanism. Our results shed light on the fundamental basis by which a particular VHH accommodate to the concave surface of an antigens with high affinity in a specific manner, enriching the mechanistic landscape of VHHs.

A Broad Role for Cysteines in Bovine Antibody Diversity

Ab diversity in most vertebrates results from the assortment of amino acid side chains on CDR loops formed through V(D)J recombination. Cows (Bos taurus) have a low combinatorial diversity potential because of a small number of highly homologous V, D, and J gene segments. Despite this, a subset of the Ab repertoire (~10%) contains exceptionally long CDR H chain (HC) 3 (H3) regions with a rich diversity of cysteines and disulfide-bonded loops that diversify through a single V-D-J recombination event followed by massive somatic hypermutation. However, the much larger portion of the repertoire, encoding shorter CDR H3s, has not been examined in detail. Analysis of germline gene segments reveals noncanonical cysteines in the HC V regions and significant cysteine content in the HC D regions. Deep sequencing analysis of naturally occurring shorter CDR H3 (<40 aa) Ab genes shows that HC V and HC D regions preferentially combine to form a functional gene with an even number of total cysteines in the final V region, suggesting that disulfide bonds contribute to diversity not only in ultralong CDR H3 bovine Abs but in shorter CDR H3 bovine Abs as well. In addition to germline “hard-coded” cysteines, the bovine Ab repertoire can produce additional cysteine codons through somatic hypermutation, further diversifying the repertoire. Given the limited combinatorial diversity at the bovine Ig loci, this helps to explain how diversity is created in shorter CDR H3 Abs and potentially provides novel structural paratopes in bovine Ab combining sites.

Structure of a VHH isolated from a naïve phage display library

OBJECTIVE

To determine the X-ray structure and biophysical properties of a Camelid V_HH isolated from a naïve phage display library.

RESULTS

Single domain antibodies (V_HH) derived from the unique immune system of the Camelidae family have gained traction as useful tools for biotechnology as well as a source of potentially novel therapeutics. Here we report the structure and biophysical characterization of a V_HH originally isolated from a naïve camelid phage display library. V_HH R419 has a melting temperate of 66 °C and was found to be a monomer in solution. The protein crystallized in space group P6₅22 and the structure was solved by molecular replacement to a resolution of 1.5 Å. The structure revealed a flat paratope with CDR loops that could be classified into existing canonical loop structures. A combination of high expression yield, stability and rapid crystallization might make R419 into a candidate scaffold for CDR grafting and homology modeling.

Structural basis for chemically-induced homodimerization of a single domain antibody

Chemically-induced dimerization (CID) systems are essential tools to interrogate and control biological systems. AcVHH is a single domain antibody homo-dimerizing upon caffeine binding. AcVHH has a strong potential for clinical applications through caffeine-mediated in vivo control of therapeutic gene networks. Here we provide the structural basis for caffeine-induced homo-dimerization of acVHH.

Computational affinity maturation of camelid single-domain intrabodies against the nonamyloid component of alpha-synuclein

Improving the affinity of protein-protein interactions is a challenging problem that is particularly important in the development of antibodies for diagnostic and clinical use. Here, we used structure-based computational methods to optimize the binding affinity of V_HNAC1, a single-domain intracellular antibody (intrabody) from the camelid family that was selected for its specific binding to the nonamyloid component (NAC) of human α-synuclein (α-syn), a natively disordered protein, implicated in the pathogenesis of Parkinson's disease (PD) and related neurological disorders. Specifically, we performed ab initio modeling that revealed several possible modes of V_HNAC1 binding to the NAC region of α-syn as well as mutations that potentially enhance the affinity between these interacting proteins. While our initial design strategy did not lead to improved affinity, it ultimately guided us towards a model that aligned more closely with experimental observations, revealing a key residue on the paratope and the participation of H4 loop residues in binding, as well as confirming the importance of electrostatic interactions. The binding activity of the best intrabody mutant, which involved just a single amino acid mutation compared to parental V_HNAC1, was significantly enhanced primarily through a large increase in association rate. Our results indicate that structure-based computational design can be used to successfully improve the affinity of antibodies against natively disordered and weakly immunogenic antigens such as α-syn, even in cases such as ours where crystal structures are unavailable.