Affinity maturation of a CDR3-grafted VHH using in silico analysis and surface plasmon resonance

In Vitro Affinity Maturation of Nanobodies against Mpox Virus A29 Protein Based on Computer-Aided Design

Mpox virus (MPXV), the most pathogenic zoonotic orthopoxvirus, caused worldwide concern during the SARS-CoV-2 epidemic. Growing evidence suggests that the MPXV surface protein A29 could be a specific diagnostic marker for immunological detection. In this study, a fully synthetic phage display library was screened, revealing two nanobodies (A1 and H8) that specifically recognize A29. Subsequently, an in vitro affinity maturation strategy based on computer-aided design was proposed by building and docking the A29 and A1 three-dimensional structures. Ligand-receptor binding and molecular dynamics simulations were performed to predict binding modes and key residues. Three mutant antibodies were predicted using the platform, increasing the affinity by approximately 10-fold compared with the parental form. These results will facilitate the application of computers in antibody optimization and reduce the cost of antibody development; moreover, the predicted antibodies provide a reference for establishing an immunological response against MPXV.

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.

Generating the Engineered Form of a Nanobody Against Placenta Growth Factor with High Antiangiogenesis Potential

Antibody engineering is a dynamic field in antibody industry. Over 30% of novel monoclonal antibodies (mAbs) in R&D and clinical trials are engineered forms. Affinity enhancement contributes to the development of new binders that are not only effective in low dose and cost but also improve some drawbacks of antibody production. After previous successful work on in silico affinity maturation of nanobody against placenta growth factor and finding the best engineered nanobodies (Mut2:S31D and Mut4:R45E), according to bioinformatic parameters and molecular dynamics (MD) simulation results, in this study we focused on experimental confirmation of affinity enhancement of a mutant form of nanobody. So, we cloned and expressed two of four mutant forms in pHEN6c vector. Affinity binding was assayed by enzyme-linked immunosorbent assay on purified mutants, with results showing that 10-time enhancement in affinity compared with the native form associated with MD simulation results. We checked the effectiveness of these mutant nanobodies in angiogenesis inhibition by human umbilical vein endothelial cell proliferation and 3D capillary tube formation. EC50 of mut2, mut4, and native in proliferation assay was 110, 140, and 190 ng/mL, respectively, and that in 3D capillary tube formation was 80, 83, and 100 ng/mL. The results of functional studies revealed strong effectiveness of Mut2 followed by Mut4 compared with the native form. Our study confirmed that in silico approach could facilitate development of novel versions of mAb with better characteristics, which could save cost and time.

Antibody Structure and Function: The Basis for Engineering Therapeutics

Antibodies and antibody-derived macromolecules have established themselves as the mainstay in protein-based therapeutic molecules (biologics). Our knowledge of the structure–function relationships of antibodies provides a platform for protein engineering that has been exploited to generate a wide range of biologics for a host of therapeutic indications. In this review, our basic understanding of the antibody structure is described along with how that knowledge has leveraged the engineering of antibody and antibody-related therapeutics having the appropriate antigen affinity, effector function, and biophysical properties. The platforms examined include the development of antibodies, antibody fragments, bispecific antibody, and antibody fusion products, whose efficacy and manufacturability can be improved via humanization, affinity modulation, and stability enhancement. We also review the design and selection of binding arms, and avidity modulation. Different strategies of preparing bispecific and multispecific molecules for an array of therapeutic applications are included.

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.

Alteration of Electrostatic Surface Potential Enhances Affinity and Tumor Killing Properties of Anti-ganglioside GD2 Monoclonal Antibody hu3F8

Ganglioside GD2 is highly expressed on neuroectodermal tumors and an attractive therapeutic target for antibodies that have already shown some clinical efficacy. To further improve the current antibodies, which have modest affinity, we sought to improve affinity by using a combined method of random mutagenesis and in silico assisted design to affinity-mature the anti-GD2 monoclonal antibody hu3F8. Using yeast display, mutants in the Fv with enhanced binding over the parental clone were FACS-sorted and cloned. In silico modeling identified the minimal key interacting residues involved in the important charged interactions with the sialic acid groups of GD2. Two mutations, D32H (L-CDR1) and E1K (L-FR1) altered the electrostatic surface potential of the antigen binding site, allowing for an increase in positive charge to enhance the interaction with the negatively charged GD2-pentasaccharide headgroup. Purified scFv and IgG mutant forms were then tested for antigen specificity by ELISA, for tissue specificity by immunohistochemistry, for affinity by BIACORE, for antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-mediated cytotoxicity in vitro, and for anti-tumor efficacy in xenografted humanized mice. The nearly 7-fold improvement in affinity of hu3F8 with a single D32H (L-CDR1) mutation translated into a ∼12-fold improvement in NK92MI-transfected CD16-mediated ADCC, a 6-fold improvement in CD32-mediated ADCC, and a 2.5-fold improvement in complement-mediated cytotoxicity while maintaining restricted normal tissue cross-reactivity and achieving substantial improvement in tumor ablation in vivo. Despite increasing GD2 affinity, the double mutation D32H (L-CDR1) and E1K (L-FR1) did not further improve anti-tumor efficacy.