A consensus protocol for the in silico optimisation of antibody fragments

Locuaz: an in silico platform for protein binders optimization

MOTIVATION

Engineering high-affinity binders targeting specific antigenic determinants remains a challenging and often daunting task, requiring extensive experimental screening. Computational methods have the potential to accelerate this process, reducing costs and time, but only if they demonstrate broad applicability and efficiency in exploring mutations, evaluating affinity, and pruning unproductive mutation paths.

RESULTS

In response to these challenges, we introduce a new computational platform for optimizing protein binders towards their targets. The platform is organized as a series of modules, performing mutation selection and application, molecular dynamics simulations to sample conformations around interaction poses, and mutation prioritization using suitable scoring functions. Notably, the platform supports parallel exploration of different mutation streams, enabling in silico high-throughput screening on High Performance Computing (HPC) systems. Furthermore, the platform is highly customizable, allowing users to implement their own protocols.

AVAILABILITY AND IMPLEMENTATION

The source code is available at https://github.com/pgbarletta/locuaz and documentation is at https://locuaz.readthedocs.io/. The data underlying this article are available at https://github.com/pgbarletta/suppl_info_locuaz.

Computational Mutagenesis of Antibody Fragments: Disentangling Side Chains from ΔΔG Predictions

The development of highly potent antibodies and antibody fragments as binding agents holds significant implications in fields such as biosensing and biotherapeutics. Their binding strength is intricately linked to the arrangement and composition of residues at the binding interface. Computational techniques offer a robust means to predict the three-dimensional structure of these complexes and to assess the affinity changes resulting from mutations. Given the interdependence of structure and affinity prediction, our objective here is to disentangle their roles. We aim to evaluate independently six side-chain reconstruction methods and ten binding affinity estimation techniques. This evaluation was pivotal in predicting affinity alterations due to single mutations, a key step in computational affinity maturation protocols. Our analysis focuses on a data set comprising 27 distinct antibody/hen egg white lysozyme complexes, each with crystal structures and experimentally determined binding affinities. Using six different side-chain reconstruction methods, we transformed each structure into its corresponding mutant via in silico single-point mutations. Subsequently, these structures undergo minimization and molecular dynamics simulation. We therefore estimate ΔΔG values based on the original crystal structure, its energy-minimized form, and the ensuing molecular dynamics trajectories. Our research underscores the critical importance of selecting reliable side-chain reconstruction methods and conducting thorough molecular dynamics simulations to accurately predict the impact of mutations. In summary, our study demonstrates that the integration of conformational sampling and scoring is a potent approach to precisely characterizing mutation processes in single-point mutagenesis protocols and crucial for computational antibody design.

The use of peptides, aptamers, and variable domains of heavy chain only antibodies in tissue engineering and regenerative medicine

Over the years, much research has been focused on the use of small molecules such as peptides or aptamers or more recently on the use of variable antigen-binding domain of heavy chain only antibodies in the field of tissue engineering and regenerative medicine. The use of these molecules originated as an alternative for the larger conventional antibodies, of which most drawbacks are derived from their size and complex structure. In the field of tissue engineering and regenerative medicine, biological functionalities are often conjugated to biomaterials in order to (re-)create an in vivo like situation, especially when bioinert biomaterials are used. Those biomaterials are functionalized with these functionalities for instance for the purpose of cell attachment or cell targeting for targeted drug delivery but also for local enrichment or blocking of ligands such as growth factors or cytokines on the biomaterial surface. In this review, we further refer to peptides, aptamers, and variable antigen-binding domain of heavy chain only antibodies as biological functionalities. Here, we compare these biological functionalities within the field of tissue engineering and regenerative medicine and give an overview of recent work in which these biological functionalities have been explored. We focus on the previously mentioned purposes of the biological functionalities. We will compare structural differences, possible modifications and (chemical) conjugation strategies. In addition, we will provide an overview of biologicals that are, or have been, involved in clinical trials. Finally, we will highlight the challenges of each of these biologicals. STATEMENT OF SIGNIFICANCE: In the field of tissue engineering there is broad application of functionalized biomaterials for cell attachment, targeted drug delivery and local enrichment or blocking of growth factors. This was previously mostly done via conventional antibodies, but their large size and complex structure impose various challenges with respect of retaining biological functionality. Peptides, aptamers and VHHs may provide an alternative solution for the use of conventional antibodies. This review discusses the use of these molecules for biological functionalization of biomaterials. For each of the molecules, their characteristics, conjugation possibilities and current use in research and clinical trials is described. Furthermore, this review sets out the benefits and challenges of using these types of molecules for different fields of application.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

Replica-exchange optimization of antibody fragments

In the framework of the rational design of macromolecules capable of binding to a specific target for biosensing applications, we here further develop an evolutionary protocol designed to optimize the binding affinity of protein binders. In particular we focus on the optimization of the binding portion of small antibody fragments known as nanobodies (or VHH) and choose the hen egg white lysozyme (HEWL) as our target. By implementing a replica exchange scheme for this optimization, we show that an initial hit is not needed and similar solutions can be found by either optimizing an already known anti-HEWL VHH or a randomly selected binder (here a VHH selective towards another macromolecule). While we believe that exhaustive searches of the mutation space are most appropriate when only few key residues have to be optimized, in case a lead binder is not available the proposed evolutionary algorithm should be instead the method of choice.

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.

DNA-Directed Protein Anchoring on Oligo/Alkanethiol-Coated Gold Nanoparticles: A Versatile Platform for Biosensing Applications

Herein, we report on a smart biosensing platform that exploits gold nanoparticles (AuNPs) functionalized through ssDNA self-assembled monolayers (SAM) and the DNA-directed immobilization (DDI) of DNA-protein conjugates; a novel, high-sensitivity optical characterization technique based on a miniaturized gel electrophoresis chip integrated with online thermal lens spectrometry (MGEC-TLS), for the high-sensitivity detection of antigen binding events. Specifically, we characterized the physicochemical properties of 20 nm AuNPs covered with mixed SAMs of thiolated single-stranded DNA and bio-repellent molecules, referred to as top-terminated oligo-ethylene glycol (TOEG6), demonstrating high colloidal stability, optimal binder surface density, and proper hybridization capacity. Further, to explore the design in the frame of cancer-associated antigen detection, complementary ssDNA fragments conjugated with a nanobody, called C8, were loaded on the particles and employed to detect the presence of the HER2-ECD antigen in liquid. At variance with conventional surface plasmon resonance detection, MGEC-TLS characterization confirmed the capability of the assay to titrate the HER2-ECD antigen down to concentrations of 440 ng/mL. The high versatility of the directed protein-DNA conjugates immobilization through DNA hybridization on plasmonic scaffolds and coupled with the high sensitivity of the MGEC-TLS detection qualifies the proposed assay as a potential, easily operated biosensing strategy for the fast and label-free detection of disease-relevant antigens.

Design of nanobody-based bispecific constructs by in silico affinity maturation and umbrella sampling simulations

Random mutagenesis is the natural opportunity for proteins to evolve and biotechnologically it has been exploited to create diversity and identify variants with improved characteristics in the mutant pools. Rational mutagenesis based on biophysical assumptions and supported by computational power has been proposed as a faster and more predictable strategy to reach the same aim. In this work we confirm that substantial improvements in terms of both affinity and stability of nanobodies can be obtained by using combinations of algorithms, even for binders with already high affinity and elevated thermal stability. Furthermore, in silico approaches allowed the development of an optimized bispecific construct able to bind simultaneously the two clinically relevant antigens TNF-α and IL-23 and, by means of its enhanced avidity, to inhibit effectively the apoptosis of TNF-α-sensitive L929 cells. The results revealed that salt bridges, hydrogen bonds, aromatic-aromatic and cation-pi interactions had a critical role in increasing affinity. We provided a platform for the construction of high-affinity bispecific constructs based on nanobodies that can have relevant applications for the control of all those biological mechanisms in which more than a single antigen must be targeted to increase the treatment effectiveness and avoid resistance mechanisms.

Research progress on unique paratope structure, antigen binding modes, and systematic mutagenesis strategies of single-domain antibodies

Single-domain antibodies (sdAbs) showed the incredible advantages of small molecular weight, excellent affinity, specificity, and stability compared with traditional IgG antibodies, so their potential in binding hidden antigen epitopes and hazard detection in food, agricultural and veterinary fields were gradually explored. Moreover, its low immunogenicity, easy-to-carry target drugs, and penetration of the blood-brain barrier have made sdAbs remarkable achievements in medical treatment, toxin neutralization, and medical imaging. With the continuous development and maturity of modern molecular biology, protein analysis software and database with different algorithms, and next-generation sequencing technology, the unique paratope structure and different antigen binding modes of sdAbs compared with traditional IgG antibodies have aroused the broad interests of researchers with the increased related studies. However, the corresponding related summaries are lacking and needed. Different antigens, especially hapten antigens, show distinct binding modes with sdAbs. So, in this paper, the unique paratope structure of sdAbs, different antigen binding cases, and the current maturation strategy of sdAbs were classified and summarized. We hope this review lays a theoretical foundation to elucidate the antigen-binding mechanism of sdAbs and broaden the further application of sdAbs.

In Silico Maturation of a Nanomolar Antibody against the Human CXCR2

The steady increase in computational power in the last 50 years is opening unprecedented opportunities in biology, as computer simulations of biological systems have become more accessible and can reproduce experimental results more accurately. Here, we wanted to test the ability of computer simulations to replace experiments in the limited but practically useful scope of improving the biochemical characteristics of the abN48 antibody, a nanomolar antagonist of the CXC chemokine receptor 2 (CXCR2) that was initially selected from a combinatorial antibody library. Our results showed a good correlation between the computed binding energies of the antibody to the peptide target and the experimental binding affinities. Moreover, we showed that it is possible to design new antibody sequences in silico with a higher affinity to the desired target using a Monte Carlo Metropolis algorithm. The newly designed sequences had an affinity comparable to the best ones obtained using in vitro affinity maturation and could be obtained within a similar timeframe. The methodology proposed here could represent a valid alternative for improving antibodies in cases in which experiments are too expensive or technically tricky and could open an opportunity for designing antibodies for targets that have been elusive so far.

Lifting the Veil: Characteristics, Clinical Significance, and Application of β-2-Microglobulin as Biomarkers and Its Detection with Biosensors

Because β-2-microglobulin (β₂M) is a surface protein that is present on most nucleated cells, it plays a key role in the human immune system and the kidney glomeruli to regulate homeostasis. The primary clinical significance of β₂M is in dialysis-related amyloidosis, a complication of end-stage renal disease caused by a gradual accumulation of β₂M in the blood. Therefore, the function of β₂M in kidney-related diseases has been extensively studied to evaluate its glomerular and tubular functions. Because increased β₂M shedding due to rapid cell turnover may indicate other underlying medical conditions, the possibility to use β₂M as a versatile biomarker rose in prominence across multiple disciplines for various applications. Therefore, this work has reviewed the recent use of β₂M to detect various diseases and its progress as a biomarker. While the use of state-of-the-art β₂M detection requires sophisticated tools, high maintenance, and labor cost, this work also has reported the use of biosensor to quantify β₂M over the past decade. It is hoped that a portable and highly efficient β₂M biosensor device will soon be incorporated in point-of-care testing to provide safe, rapid, and reliable test results.

Multiple-Allele MHC Class II Epitope Engineering by a Molecular Dynamics-Based Evolution Protocol

Epitopes that bind simultaneously to all human alleles of Major Histocompatibility Complex class II (MHC II) are considered one of the key factors for the development of improved vaccines and cancer immunotherapies. To engineer MHC II multiple-allele binders, we developed a protocol called PanMHC-PARCE, based on the unsupervised optimization of the epitope sequence by single-point mutations, parallel explicit-solvent molecular dynamics simulations and scoring of the MHC II-epitope complexes. The key idea is accepting mutations that not only improve the affinity but also reduce the affinity gap between the alleles. We applied this methodology to enhance a Plasmodium vivax epitope for multiple-allele binding. In vitro rate-binding assays showed that four engineered peptides were able to bind with improved affinity toward multiple human MHC II alleles. Moreover, we demonstrated that mice immunized with the peptides exhibited interferon-gamma cellular immune response. Overall, the method enables the engineering of peptides with improved binding properties that can be used for the generation of new immunotherapies.

Multiscale affinity maturation simulations to elicit broadly neutralizing antibodies against HIV

The design of vaccines against highly mutable pathogens, such as HIV and influenza, requires a detailed understanding of how the adaptive immune system responds to encountering multiple variant antigens (Ags). Here, we describe a multiscale model of B cell receptor (BCR) affinity maturation that employs actual BCR nucleotide sequences and treats BCR/Ag interactions in atomistic detail. We apply the model to simulate the maturation of a broadly neutralizing Ab (bnAb) against HIV. Starting from a germline precursor sequence of the VRC01 anti-HIV Ab, we simulate BCR evolution in response to different vaccination protocols and different Ags, which were previously designed by us. The simulation results provide qualitative guidelines for future vaccine design and reveal unique insights into bnAb evolution against the CD4 binding site of HIV. Our model makes possible direct comparisons of simulated BCR populations with results of deep sequencing data, which will be explored in future applications.

Vaccination has saved more lives than any other medical procedure. But, we do not have robust ways to develop vaccines against highly mutable pathogens. For example, there is no effective vaccine against HIV, and a universal vaccine against diverse strains of influenza is also not available. The development of immunization strategies to elicit antibodies that can neutralize diverse strains of highly mutable pathogens (so-called ‘broadly neutralizing antibodies’, or bnAbs) would enable the design of universal vaccines against such pathogens, as well as other viruses that may emerge in the future. In this paper, we present an agent-based model of affinity maturation–the Darwinian process by which antibodies evolve against a pathogen–that, for the first time, enables the in silico investigation of real germline nucleotide sequences of antibodies known to evolve into potent bnAbs, evolving against real amino acid sequences of HIV-based vaccine-candidate proteins. Our results provide new insights into bnAb evolution against HIV, and can be used to qualitatively guide the future design of vaccines against highly mutable pathogens.

Affinity-based isolation of extracellular vesicles by means of single-domain antibodies bound to macroporous methacrylate-based copolymer

Correct elucidation of physiological and pathological processes mediated by extracellular vesicles (EV) is highly dependent on the reliability of the method used for their purification. Currently available chemical/physical protocols for sample fractionation are time-consuming, often scarcely reproducible and their yields are low. Immuno-capture based approaches could represent an effective purification alternative to obtain homogeneous EV samples. An easy-to-operate chromatography system was set-up for the purification of intact EVs based on a single domain (VHH) antibodies-copolymer matrix suitable for biological samples as different as conditioned cell culture medium and human plasma. Methacrylate-based copolymer is a porous solid support, the chemical versatility of which enables its efficient functionalization with VHHs. The combined analyses of morphological features and biomarker (CD9, CD63 and CD81) presence indicated that the recovered EVs were exosomes. The lipoprotein markers APO-A1 and APO-B were both negative in tested samples. This is the first report demonstrating the successful application of spherical porous methacrylate-based copolymer coupled with VHHs for the exosome isolation from biological fluids. This inexpensive immunoaffinity method has the potential to be applied for the isolation of EVs belonging to different morphological and physiological classes.

Cytoplasmic Production of Nanobodies and Nanobody-Based Reagents by Co-Expression of Sulfhydryl Oxidase and DsbC Isomerase

Nanobodies are stable molecules that can often fold correctly even in the absence of the disulfide bond(s) that stabilize their three-dimensional conformation. Nevertheless, some nanobodies require the formation of disulfide bonds, and therefore they are commonly expressed from vectors that promote their secretion into the oxidizing environment of the Escherichia coli periplasm. As an alternative, the bacterial cytoplasm can be an effective compartment for producing correctly folded nanobodies when sulfhydryl oxidase and disulfide-bond isomerase activities are co-expressed from a recombinant vector. The larger volume and wider chaperone/foldase availability of the cytoplasm enable the achievement of high yields of both nanobodies and nanobody-tag fusions, independently of their redox requirements. Among other examples, the protocol described here was used to successfully produce nanobody fusions with fluorescent proteins that do not fold correctly in the periplasm, nanobodies with Fc domains, and nanobodies containing free cysteine tags.

Research Progress and Applications of Multivalent, Multispecific and Modified Nanobodies for Disease Treatment

Recombinant antibodies such as nanobodies are progressively demonstrating to be a valid alternative to conventional monoclonal antibodies also for clinical applications. Furthermore, they do not solely represent a substitute for monoclonal antibodies but their unique features allow expanding the applications of biotherapeutics and changes the pattern of disease treatment. Nanobodies possess the double advantage of being small and simple to engineer. This combination has promoted extremely diversified approaches to design nanobody-based constructs suitable for particular applications. Both the format geometry possibilities and the functionalization strategies have been widely explored to provide macromolecules with better efficacy with respect to single nanobodies or their combination. Nanobody multimers and nanobody-derived reagents were developed to image and contrast several cancer diseases and have shown their effectiveness in animal models. Their capacity to block more independent signaling pathways simultaneously is considered a critical advantage to avoid tumor resistance, whereas the mass of these multimeric compounds still remains significantly smaller than that of an IgG, enabling deeper penetration in solid tumors. When applied to CAR-T cell therapy, nanobodies can effectively improve the specificity by targeting multiple epitopes and consequently reduce the side effects. This represents a great potential in treating malignant lymphomas, acute myeloid leukemia, acute lymphoblastic leukemia, multiple myeloma and solid tumors. Apart from cancer treatment, multispecific drugs and imaging reagents built with nanobody blocks have demonstrated their value also for detecting and tackling neurodegenerative, autoimmune, metabolic, and infectious diseases and as antidotes for toxins. In particular, multi-paratopic nanobody-based constructs have been developed recently as drugs for passive immunization against SARS-CoV-2 with the goal of impairing variant survival due to resistance to antibodies targeting single epitopes. Given the enormous research activity in the field, it can be expected that more and more multimeric nanobody molecules will undergo late clinical trials in the next future. Systematic Review Registration.

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.

Native llama Nanobody Library Panning Performed by Phage and Yeast Display Provides Binders Suitable for C-Reactive Protein Detection

C-reactive protein (CRP) is an inflammation biomarker that should be quantified accurately during infections and healing processes. Nanobodies are good candidates to replace conventional antibodies in immunodiagnostics due to their inexpensive production, simple engineering, and the possibility to obtain higher binder density on capture surfaces. Starting from the same pre-immune library, we compared the selection output resulting from two independent panning strategies, one exclusively exploiting the phage display and another in which a first round of phage display was followed by a second round of yeast display. There was a partial output convergence between the two methods, since two clones were identified using both panning protocols but the first provided several further different sequences, whereas the second favored the recovery of many copies of few clones. The isolated anti-CRP nanobodies had affinity in the low nanomolar range and were suitable for ELISA and immunoprecipitation. One of them was fused to SpyTag and exploited in combination with SpyCatcher as the immunocapture element to quantify CRP using electrochemical impedance spectroscopy. The sensitivity of the biosensor was calculated as low as 0.21 μg/mL.

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.

CDR1 Composition Can Affect Nanobody Recombinant Expression Yields

The isolation of nanobodies from pre-immune libraries by means of biopanning is a straightforward process. Nevertheless, the recovered candidates often require optimization to improve some of their biophysical characteristics. In principle, CDRs are not mutated because they are likely to be part of the antibody paratope, but in this work, we describe a mutagenesis strategy that specifically addresses CDR1. Its sequence was identified as an instability hot spot by the PROSS program, and the available structural information indicated that four CDR1 residues bound directly to the antigen. We therefore modified the loop flexibility with the addition of an extra glycine rather than by mutating single amino acids. This approach significantly increased the nanobody yields but traded-off with moderate affinity loss. Accurate modeling coupled with atomistic molecular dynamics simulations enabled the modifications induced by the glycine insertion and the rationale behind the engineering design to be described in detail.

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.

Computationally-obtained structural insights into the molecular interactions between Pidilizumab and binding partners DLL1 and PD-1

Pidilizumab is a monoclonal antibody tested against several types of malignancies, such as lymphoma and metastatic melanoma, showing promising results. In 2016, the FDA put Pidilizumab's clinical studies on partial hold due to emerging evidence pointing to the antibody target uncertainty. Although initial studies indicated an interaction with the PD-1 checkpoint receptor, recent updates assert that Pidilizumab binds primarily to Notch ligand DLL1. However, a detailed description of which interactions coordinate antibody-antigen complex formation is lacking. Therefore, this study uses computational tools to identify molecular interactions between Pidilizumab and its reported targets PD-1 and DLL1. A docking methodology was validated and applied to determine the binding modes between modeled Pidilizumab scFvs and the two antigens. We used Molecular Dynamics (MD) simulations to verify the complexes' stability and submitted the resulting trajectory files to MM/PBSA and Principal Component Analysis. A set of different prediction tools determined scFv interface hot-spots. Whereas docking and MD simulations revealed that the antibody fragments do not interact straightforwardly with PD-1, ten scFv hot-spots, including Met93 and Leu112, mediated the interaction with the DLL1 C2 domain. The interaction triggered a conformational selection-like effect on DLL1, allowing new hydrogen bonds on the β3-β4 interface loop. The unprecedented structural data on Pidilizumab's interactions provided novel evidence that its legitimate target is the DLL1 protein and offered structural insight on how these molecules interact, shedding light on the pathways that could be affected by the use of this essential immunobiological.Communicated by Ramaswamy H. Sarma.

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.

Toward Drug-Like Multispecific Antibodies by Design

The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.

In vitro affinity maturation to improve the efficacy of a hypoxia-inducible factor 1α single-domain intrabody

Affinity is an important property of therapeutic antibodies, so improving affinity is critical to the biological activity and clinical efficacy. An anti-HIF-1α nanobody, VHH212, was screened via a native ribosome display library with a 26.6 nM of K_D value was used as the parent. In this paper, a Venn-intersection of multi-algorithms screening (VIMAS) strategy for computer-aided binding affinity prediction was designed. Homology modeling and protein docking methods were used to substitute the need for a crystal structure. Finally, a mutant with a 17.5-fold enhancement in binding affinity (1.52 nM) was obtained by using the VIMAS strategy. Furthermore, the biological activity of mutants was verified at the cellular level. Targeting HIF-1α can sensitize PDAC (pancreatic ductal adenocarcinoma) tumors to gemcitabine, which is a potential co-treatment method for pancreatic cancer patients. Our results showed that the cytotoxicity of gemcitabine on pancreatic cancer cell lines increased with the enhanced-affinity of an intrabody under combined treatment.

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.