Molecular dynamics simulations and docking enable to explore the biophysical factors controlling the yields of engineered nanobodies

Nanobody engineering: computational modelling and design for biomedical and therapeutic applications

Nanobodies, the smallest functional antibody fragment derived from camelid heavy-chain-only antibodies, have emerged as powerful tools for diverse biomedical applications. In this comprehensive review, we discuss the structural characteristics, functional properties, and computational approaches driving the design and optimisation of synthetic nanobodies. We explore their unique antigen-binding domains, highlighting the critical role of complementarity-determining regions in target recognition and specificity. This review further underscores the advantages of nanobodies over conventional antibodies from a biosynthesis perspective, including their small size, stability, and solubility, which make them ideal candidates for economical antigen capture in diagnostics, therapeutics, and biosensing. We discuss the recent advancements in computational methods for nanobody modelling, epitope prediction, and affinity maturation, shedding light on their intricate antigen-binding mechanisms and conformational dynamics. Finally, we examine a direct example of how computational design strategies were implemented for improving a nanobody-based immunosensor, known as a Quenchbody. Through combining experimental findings and computational insights, this review elucidates the transformative impact of nanobodies in biotechnology and biomedical research, offering a roadmap for future advancements and applications in healthcare and diagnostics.

General Trends of the Camelidae Antibody VHHs Domain Dynamics

Conformational flexibility plays an essential role in antibodies' functional and structural stability. They facilitate and determine the strength of antigen-antibody interactions. Camelidae express an interesting subtype of single-chain antibody, named Heavy Chain only Antibody. They have only one N-terminal Variable domain (V_HH) per chain, composed of Frameworks (FRs) and Complementarity Determining regions (CDRs) like their VH and VL counterparts in IgG. Even when expressed independently, V_HH domains display excellent solubility and (thermo)stability, which helps them to retain their impressive interaction capabilities. Sequence and structural features of V_HH domains contributing to these abilities have already been studied compared to classical antibodies. To have the broadest view and understand the changes in dynamics of these macromolecules, large-scale molecular dynamics simulations for a large number of non-redundant V_HH structures have been performed for the first time. This analysis reveals the most prevalent movements in these domains. It reveals the four main classes of V_HHs dynamics. Diverse local changes were observed in CDRs with various intensities. Similarly, different types of constraints were observed in CDRs, while FRs close to CDRs were sometimes primarily impacted. This study sheds light on the changes in flexibility in different regions of V_HH that may impact their in silico design.

Antibody Affinity Maturation Using Computational Methods: From an Initial Hit to Small-Scale Expression of Optimized Binders

Nanobodies (VHHs) are engineered fragments of the camelid single-chain immunoglobulins. The VHH domain contains the highly variable segments responsible for antigen recognition. VHHs can be easily produced as recombinant proteins. Their small size is a good advantage for in silico approaches. Computer methods represent a valuable strategy for the optimization and improvement of their binding affinity. They also allow for epitope selection offering the possibility to design new VHHs for regions of a target protein that are not naturally immunogenic. Here we present an in silico mutagenic protocol developed to improve the binding affinity of nanobodies together with the first step of their in vitro production. The method, already proven successful in improving the low Kd of a nanobody hit obtained by panning, can be employed for the ex novo design of antibody fragments against selected protein target epitopes.

Protein purification strategies must consider downstream applications and individual biological characteristics

BACKGROUND

Proteins are used as reagents in a broad range of scientific fields. The reliability and reproducibility of experimental data will largely depend on the quality of the (recombinant) proteins and, consequently, these should undergo thorough structural and functional controls. Depending on the downstream application and the biochemical characteristics of the protein, different sets of specific features will need to be checked.

RESULTS

A number of examples, representative of recurrent issues and previously published strategies, has been reported that illustrate real cases of recombinant protein production in which careful strategy design at the start of the project combined with quality controls throughout the production process was imperative to obtain high-quality samples compatible with the planned downstream applications. Some proteins possess intrinsic properties (e.g., prone to aggregation, rich in cysteines, or a high affinity for nucleic acids) that require certain precautions during the expression and purification process. For other proteins, the downstream application might demand specific conditions, such as for proteins intended for animal use that need to be endotoxin-free.

CONCLUSIONS

This review has been designed to act as a practical reference list for researchers who wish to produce and evaluate recombinant proteins with certain specific requirements or that need particular care for their preparation and storage.

Computational Evolution Protocol for Peptide Design

Computational peptide design is useful for therapeutics, diagnostics, and vaccine development. To select the most promising peptide candidates, the key is describing accurately the peptide-target interactions at the molecular level. We here review a computational peptide design protocol whose key feature is the use of all-atom explicit solvent molecular dynamics for describing the different peptide-target complexes explored during the optimization. We describe the milestones behind the development of this protocol, which is now implemented in an open-source code called PARCE. We provide a basic tutorial to run the code for an antibody fragment design example. Finally, we describe three additional applications of the method to design peptides for different targets, illustrating the broad scope of the proposed approach.

Insights on peptide topology in the computational design of protein ligands: the example of lysozyme binding peptides

Herein, we compared the ability of linear and cyclic peptides generated in silico to target different protein sites: internal pockets and solvent-exposed sites. We selected human lysozyme (HuL) as a model target protein combined with the computational evolution of linear and cyclic peptides. The sequence evolution of these peptides was based on the PARCE algorithm. The generated peptides were screened based on their aqueous solubility and HuL binding affinity. The latter was evaluated by means of scoring functions and atomistic molecular dynamics (MD) trajectories in water, which allowed prediction of the structural features of the protein-peptide complexes. The computational results demonstrated that cyclic peptides constitute the optimal choice for solvent exposed sites, while both linear and cyclic peptides are capable of targeting the HuL pocket effectively. The most promising binders found in silico were investigated experimentally by surface plasmon resonance (SPR), nuclear magnetic resonance (NMR), and electrospray ionization mass spectrometry (ESI-MS) techniques. All tested peptides displayed dissociation constants in the micromolar range, as assessed by SPR; however, both NMR and ESI-MS suggested multiple binding modes, at least for the pocket binding peptides. A detailed NMR analysis confirmed that both linear and cyclic pocket peptides correctly target the binding site they were designed for.

Delicate balance among thermal stability, binding affinity, and conformational space explored by single-domain VHH antibodies

The high binding affinities and specificities of antibodies have led to their use as drugs and biosensors. Single-domain V_HH antibodies exhibit high specificity and affinity but have higher stability and solubility than conventional antibodies as they are single-domain proteins. In this work, based on physicochemical measurements and molecular dynamics (MD) simulations, we have gained insight that will facilitate rational design of single-chain V_HH antibodies. We first assessed two homologous V_HH antibodies by differential scanning calorimetry (DSC); one had a high (64.8 °C) and the other a low (58.6 °C) melting temperature. We then generated a series of the variants of the low stability antibody and analyzed their thermal stabilities by DSC and characterized their structures through MD simulations. We found that a single mutation that resulted in 8.2 °C improvement in melting temperature resulted in binding affinity an order of magnitude lower than the parent antibody, likely due to a shift of conformational space explored by the single-chain V_HH antibody. These results suggest that the delicate balance among conformational stability, binding capability, and conformational space explored by antibodies must be considered in design of fully functional single-chain V_HH antibodies.

Engineering of single-domain antibodies for next-generation snakebite antivenoms

Given the magnitude of the global snakebite crisis, strategies to ensure the quality of antivenom, as well as the availability and sustainability of its supply are under development by several research groups. Recombinant DNA technology has allowed the engineering of monoclonal antibodies and recombinant fragments as alternatives to conventional antivenoms. Besides having higher therapeutic efficacy, with broad neutralization capacity against local and systemic toxicity, novel antivenoms need to be safe and cost-effective. Due to the biological and physical chemical properties of camelid single-domain antibodies, with high volume of distribution to distal tissue, their modular format, and their versatility, their biotechnological application has grown considerably in recent decades. This article presents the most up-to-date developments concerning camelid single-domain-based antibodies against major toxins from snake venoms, the main venomous animals responsible for reported envenoming cases and related human deaths. A brief discussion on the composition, challenges, and perspectives of antivenoms is presented, as well as the road ahead for next-generation antivenoms based on single-domain antibodies.

An anti-HER2 nanobody binds to its antigen HER2 via two independent paratopes

High-resolution structural data of complexes between antibodies and membrane receptors still represent a demanding task. In this study, we used complementary sets of experimental data to obtain a structural model of the complex formed by the human epidermal growth factor receptor 2 (HER2) and its specific nanobody A10. First we identified by NMR the residues that bind or rearrange as a consequence of the complex formation. In parallel, the complex was cross-linked, digested and the resulting peptides were characterized by mass-spectrometry to define maximal distance restraints between HER2 and A10 amino acids in their complex. These independent datasets guided a docking process, refined by molecular dynamics simulations, to develop a model of the complex and estimate per-residue free-energy contributions. Such a model explains the experimental data and identifies a second, non-canonical paratope, located in the region opposite to the conventional nanobody paratope, formed by the hypervariable loop regions LH1 and LH3. Both paratopes contributed substantially to the overall affinity by binding to independent HER2 epitopes. Nanobody mutants with substitution of key interaction residues, as indicated by the model, possess significantly lower affinity for HER2. This is the first described case of a "natural" biparatopic nanobody, directly selected by in-vitro panning.

Effect of Humanizing Mutations on the Stability of the Llama Single-Domain Variable Region

In vivo clinical applications of nanobodies (VHHs) require molecules that induce minimal immunoresponse and therefore possess sequences as similar as possible to the human VH domain. Although the relative sequence variability in llama nanobodies has been used to identify scaffolds with partially humanized signature, the transformation of the Camelidae hallmarks in the framework2 still represents a major problem. We assessed a set of mutants in silico and experimentally to elucidate what is the contribution of single residues to the VHH stability and how their combinations affect the mutant nanobody stability. We described at molecular level how the interaction among residues belonging to different structural elements enabled a model llama nanobody (C8WT, isolated from a naïve library) to be functional and maintain its stability, despite the analysis of its primary sequence would classify it as aggregation-prone. Five chimeras formed by grafting CDRs isolated from different nanobodies into C8WT scaffold were successfully expressed as soluble proteins and both tested clones preserved their antigen binding specificity. We identified a nanobody with human hallmarks that seems suitable for humanizing selected camelid VHHs by grafting heterologous CDRs in its scaffold and could serve for the preparation of a synthetic library of human-like single domains.

Computational Evolution of Beta-2-Microglobulin Binding Peptides for Nanopatterned Surface Sensors

The bottom-up design of smart nanodevices largely depends on the accuracy by which each of the inherent nanometric components can be functionally designed with predictive methods. Here, we present a rationally designed, self-assembled nanochip capable of capturing a target protein by means of pre-selected binding sites. The sensing elements comprise computationally evolved peptides, designed to target an arbitrarily selected binding site on the surface of beta-2-Microglobulin (β2m), a globular protein that lacks well-defined pockets. The nanopatterned surface was generated by an atomic force microscopy (AFM)-based, tip force-driven nanolithography technique termed nanografting to construct laterally confined self-assembled nanopatches of single stranded (ss)DNA. These were subsequently associated with an ssDNA-peptide conjugate by means of DNA-directed immobilization, therefore allowing control of the peptide's spatial orientation. We characterized the sensitivity of such peptide-containing systems against β2m in solution by means of AFM-based differential topographic imaging and surface plasmon resonance (SPR) spectroscopy. Our results show that the confined peptides are capable of specifically capturing β2m from the surface-liquid interface with micromolar affinity, hence providing a viable proof-of-concept for our approach to peptide design.

Aggrescan3D (A3D) 2.0: prediction and engineering of protein solubility

Protein aggregation is a hallmark of a growing number of human disorders and constitutes a major bottleneck in the manufacturing of therapeutic proteins. Therefore, there is a strong need of in-silico methods that can anticipate the aggregative properties of protein variants linked to disease and assist the engineering of soluble protein-based drugs. A few years ago, we developed a method for structure-based prediction of aggregation properties that takes into account the dynamic fluctuations of proteins. The method has been made available as the Aggrescan3D (A3D) web server and applied in numerous studies of protein structure-aggregation relationship. Here, we present a major update of the A3D web server to version 2.0. The new features include: extension of dynamic calculations to significantly larger and multimeric proteins, simultaneous prediction of changes in protein solubility and stability upon mutation, rapid screening for functional protein variants with improved solubility, a REST-ful service to incorporate A3D calculations in automatic pipelines, and a new, enhanced web server interface. A3D 2.0 is freely available at: http://biocomp.chem.uw.edu.pl/A3D2/

Recombinant expression of nanobodies and nanobody-derived immunoreagents

Antibody fragments for which the sequence is available are suitable for straightforward engineering and expression in both eukaryotic and prokaryotic systems. When produced as fusions with convenient tags, they become reagents which pair their selective binding capacity to an orthogonal function. Several kinds of immunoreagents composed by nanobodies and either large proteins or short sequences have been designed for providing inexpensive ready-to-use biological tools. The possibility to choose among alternative expression strategies is critical because the fusion moieties might require specific conditions for correct folding or post-translational modifications. In the case of nanobody production, the trend is towards simpler but reliable (bacterial) methods that can substitute for more cumbersome processes requiring the use of eukaryotic systems. The use of these will not disappear, but will be restricted to those cases in which the final immunoconstructs must have features that cannot be obtained in prokaryotic cells. At the same time, bacterial expression has evolved from the conventional procedure which considered exclusively the nanobody and nanobody-fusion accumulation in the periplasm. Several reports show the advantage of cytoplasmic expression, surface-display and secretion for at least some applications. Finally, there is an increasing interest to use as a model the short nanobody sequence for the development of in silico methodologies aimed at optimizing the yields, stability and affinity of recombinant antibodies.

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There is an increasing request for immunoreagents based on nanobodies.

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The multiplicity of their applications requires constructs with different structural complexity.

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Alternative expression methods are necessary to achieve such structural requirements.

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In silico optimization of nanobody biophysical characteristics becomes more and more reliable.

Electrochemical immunosensor functionalized with nanobodies for the detection of the toxic microalgae Alexandrium minutum using glassy carbon electrode modified with gold nanoparticles

In this work an electrochemical immunosensor for the toxic microalgae Alexandrium minutum (A. minutum AL9T) detection is described. A glassy carbon electrode (GCE) was modified by depositing gold nanoparticles followed by L-cysteine for obtaining a self-assembled monolayer. The SpyTagged nanobody C1, specific for the A. minutum toxic strain AL9T, was then covalently immobilized via SpyCatcher on the surface of the modified electrode and used for the selective capture of such microalgae strain. Electrochemical impedance spectroscopy (EIS) was used for the quantification of A. minutum cells present in water samples by measuring the charge-transfer resistance changes of the electrode with a hexacyanoferrate probe. Each electrode modification step was accompanied by cyclic voltammetry (CV) and scanning electron microscopy (SEM). The immunosensor provided highly reproducible data, was simple to fabricate at low cost, exhibited higher sensitivity than previously described alternative diagnostic methods and showed a broad linear range between 10³ and 10⁹ cells L^-1 with detection limit of 3 × 10³ cells L^-1 of A. minutum AL9T. The immunosensor was successfully applied to quantify A. minutum AL9T in seawater and brackish water samples proving that it can be used for early detection of harmful microalgae without the necessity of pre-concentration or dialysis steps.

A consensus protocol for the in silico optimisation of antibody fragments

We present an in silico mutagenetic protocol for improving the binding affinity of single domain antibodies (or nanobodies, VHHs). The method iteratively attempts random mutations in the interacting region of the protein and evaluates the resulting binding affinity towards the target by scoring, with a collection of scoring functions, short explicit solvent molecular dynamics trajectories of the binder-target complexes. The acceptance/rejection of each attempted mutation is carried out by a consensus decision-making algorithm, which considers all individual assessments derived from each scoring function. The method was benchmarked by evolving a single complementary determining region (CDR) of an anti-HER2 VHH hit obtained by direct panning of a phage display library. The optimised VHH mutant showed significantly enhanced experimental affinity with respect to the original VHH it matured from. The protocol can be employed as it is for the optimization of peptides, antibody fragments, and (given enough computational power) larger antibodies.

Homology Modeling-Based in Silico Affinity Maturation Improves the Affinity of a Nanobody

Affinity maturation and rational design have a raised importance in the application of nanobody (VHH), and its unique structure guaranteed these processes quickly done in vitro. An anti-CD47 nanobody, Nb02, was screened via a synthetic phage display library with 278 nM of K_D value. In this study, a new strategy based on homology modeling and Rational Mutation Hotspots Design Protocol (RMHDP) was presented for building a fast and efficient platform for nanobody affinity maturation. A three-dimensional analytical structural model of Nb02 was constructed and then docked with the antigen, the CD47 extracellular domain (CD47^ext). Mutants with high binding affinity are predicted by the scoring of nanobody-antigen complexes based on molecular dynamics trajectories and simulation. Ultimately, an improved mutant with an 87.4-fold affinity (3.2 nM) and 7.36 °C higher thermal stability was obtained. These findings might contribute to computational affinity maturation of nanobodies via homology modeling using the recent advancements in computational power. The add-in of aromatic residues which formed aromatic-aromatic interaction plays a pivotal role in affinity and thermostability improvement. In a word, the methods used in this study might provide a reference for rapid and efficient in vitro affinity maturation of nanobodies.

Novel Benzene-Based Carbamates for AChE/BChE Inhibition: Synthesis and Ligand/Structure-Oriented SAR Study

A series of new benzene-based derivatives was designed, synthesized and comprehensively characterized. All of the tested compounds were evaluated for their in vitro ability to potentially inhibit the acetyl- and butyrylcholinesterase enzymes. The selectivity index of individual molecules to cholinesterases was also determined. Generally, the inhibitory potency was stronger against butyryl- compared to acetylcholinesterase; however, some of the compounds showed a promising inhibition of both enzymes. In fact, two compounds (23, benzyl ethyl(1-oxo-1-phenylpropan-2-yl)carbamate and 28, benzyl (1-(3-chlorophenyl)-1-oxopropan-2-yl) (methyl)carbamate) had a very high selectivity index, while the second one (28) reached the lowest inhibitory concentration IC₅₀ value, which corresponds quite well with galanthamine. Moreover, comparative receptor-independent and receptor-dependent structure–activity studies were conducted to explain the observed variations in inhibiting the potential of the investigated carbamate series. The principal objective of the ligand-based study was to comparatively analyze the molecular surface to gain insight into the electronic and/or steric factors that govern the ability to inhibit enzyme activities. The spatial distribution of potentially important steric and electrostatic factors was determined using the probability-guided pharmacophore mapping procedure, which is based on the iterative variable elimination method. Additionally, planar and spatial maps of the host–target interactions were created for all of the active compounds and compared with the drug molecules using the docking methodology.

Current Trends in Biotherapeutic Higher Order Structure Characterization by Irreversible Covalent Footprinting Mass Spectrometry

BACKGROUND

Biotherapeutics, particularly monoclonal antibodies (mAbs), are a maturing class of drugs capable of treating a wide range of diseases. Therapeutic function and solutionstability are linked to the proper three-dimensional organization of the primary sequence into Higher Order Structure (HOS) as well as the timescales of protein motions (dynamics). Methods that directly monitor protein HOS and dynamics are important for mapping therapeutically relevant protein-protein interactions and assessing properly folded structures. Irreversible covalent protein footprinting Mass Spectrometry (MS) tools, such as site-specific amino acid labeling and hydroxyl radical footprinting are analytical techniques capable of monitoring the side chain solvent accessibility influenced by tertiary and quaternary structure. Here we discuss the methodology, examples of biotherapeutic applications, and the future directions of irreversible covalent protein footprinting MS in biotherapeutic research and development.

CONCLUSION

Bottom-up mass spectrometry using irreversible labeling techniques provide valuable information for characterizing solution-phase protein structure. Examples range from epitope mapping and protein-ligand interactions, to probing challenging structures of membrane proteins. By paring these techniques with hydrogen-deuterium exchange, spectroscopic analysis, or static-phase structural data such as crystallography or electron microscopy, a comprehensive understanding of protein structure can be obtained.

Binding affinity prediction of nanobody-protein complexes by scoring of molecular dynamics trajectories

Nanobodies offer a viable alternative to antibodies for engineering high affinity binders. Their small size has an additional advantage: it allows exploiting computational protocols for optimizing their biophysical features, such as the binding affinity. The efficient prediction of this quantity is still considered a daunting task especially for modelled complexes. We show how molecular dynamics can successfully assist in the binding affinity prediction of modelled nanobody-protein complexes. The approximate initial configurations obtained by in silico design must undergo large rearrangements before achieving a stable conformation, in which the binding affinity can be meaningfully estimated. The scoring functions developed for the affinity evaluation of crystal structures will provide accurate estimates for modelled binding complexes if the scores are averaged over long finite temperature molecular dynamics simulations.

Enhanced Thermostability of Glucose Oxidase through Computer-Aided Molecular Design

Glucose oxidase (GOD, EC.1.1.3.4) specifically catalyzes the reaction of β-d-glucose to gluconic acid and hydrogen peroxide in the presence of oxygen, which has become widely used in the food industry, gluconic acid production and the feed industry. However, the poor thermostability of the current commercial GOD is a key limiting factor preventing its widespread application. In the present study, amino acids closely related to the thermostability of glucose oxidase from Penicillium notatum were predicted with a computer-aided molecular simulation analysis, and mutant libraries were established following a saturation mutagenesis strategy. Two mutants with significantly improved thermostabilities, S100A and D408W, were subsequently obtained. Their protein denaturing temperatures were enhanced by about 4.4 °C and 1.2 °C, respectively, compared with the wild-type enzyme. Treated at 55 °C for 3 h, the residual activities of the mutants were greater than 72%, while that of the wild-type enzyme was only 20%. The half-lives of S100A and D408W were 5.13- and 4.41-fold greater, respectively, than that of the wild-type enzyme at the same temperature. This work provides novel and efficient approaches for enhancing the thermostability of GOD by reducing the protein free unfolding energy or increasing the interaction of amino acids with the coenzyme.

Quantification of Circulating Cancer Biomarkers via Sensitive Topographic Measurements on Single Binder Nanoarrays

Early detection of cancer plays a crucial role in disease prognosis. It requires the recognition and quantification of low amounts of specific molecular biomarkers, either free or transported inside nanovesicles, through the development of novel sensitive diagnostic technologies. In this context, we have developed a nanoarray platform for the noninvasive quantification of cancer biomarkers circulating in the bloodstream. The assay is based on molecular manipulation to create functional spots of surface-immobilized binders and differential topography measurements. It is label-free and requires just a single binder per antigen, and when it is implemented with fluorescence labeling/readout, it can be used for epitope mapping. As a benchmark, we focused on the plasma release of Her2 extracellular domain (ECD), a proposed biomarker for the progression of Her2-positive tumors and response to anticancer therapies. By employing robust, easily engineered camelid nanobodies as binders, we measured ECD-Her2 concentrations in the range of the actual clinical cutoff value for Her2-positive breast cancer. The specificity for Her2 detection was preserved when it was measured in parallel with other potential biomarkers, demonstrating a forthcoming implementation of this approach for multiplexing analysis. Prospectively, this nanorarray platform may be customized to allow for the detection of promising new classes of circulating biomarkers, such as exosomes and microvesicles.