Rational affinity enhancement of fragmented antibody by ligand-based affinity improvement approach

Physicochemical Stimulus-Responsive Systems Targeted with Antibody Derivatives

The application of monoclonal antibodies and antibody fragments with the advent of recombinant antibody technology has made notable progress in clinical trials to provide a regulated drug release and extra targeting to the special conditions in the function site. Modification of antibodies has facilitated using mAbs and antibody fragments in numerous models of therapeutic and detection utilizations, such as stimuliresponsive systems. Antibodies and antibody derivatives conjugated with diverse stimuliresponsive materials have been constructed for drug delivery in response to a wide range of endogenous (electric, magnetic, light, radiation, ultrasound) and exogenous (temperature, pH, redox potential, enzymes) stimuli. In this report, we highlighted the recent progress on antibody-conjugated stimuli-responsive and dual/multi-responsive systems that affect modern medicine by improving a multitude of diagnostic and treatment strategies.

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.

Prediction and validation of monoclonal antibodies separation in aqueous two-phase system using molecular dynamic simulation

In order to predict how mAbs partition in 20% ethylene oxide/80% propylene oxide (v/v) random copolymer (EO₂₀PO₈₀)/water aqueous two-phase system (ATPS), a molecular dynamic simulation model was developed using Gromacs and then validated by experiments. The ATPS was applied with seven kinds of salt, including buffer salt and strong dissociation salt that were commonly employed in the purification of protein. Na₂SO₄ was shown to have the best effects on lowering EO₂₀PO₈₀ content in the aqueous phase and enhancing recovery. The content of EO₂₀PO₈₀ in the sample solution was decreased to 0.62%±0.25% and the recovery of rituximab increased to 97.88%±0.95% by adding 300 mM Na₂SO₄ into back extraction ATPS. The viability determined by ELISA was 95.57% at the same time. A strategy for constructing a prediction model for the distribution of mAbs in ATPS was proposed in consideration of this finding. Partition of trastuzumab in ATPS was predicted by the model created using this method and the prediction result was further validated by experiments. The recovery of trastuzumab reached 95.63%±2.86% under the ideal extraction conditions suggested by the prediction model.

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.

Development of a Recombinant Monospecific Anti-PLGF Bivalent Nanobody and Evaluation of it in Angiogenesis Modulation

During the past two decades, tumor therapy based on monoclonal antibody has been found as a confident therapeutic approach in solid tumors and hematologic malignancies. Nanobodies are the smallest fragment of an antigen-binding domain in heavy chain-only antibody originated from the Camelidae family. Accordingly, they are being recently developed rapidly as diagnostic and therapeutic agents. In this regard, targeting of angiogenic factors like Placenta growth factor (PLGF) via nanobodies show a high effectiveness. In the current study, we developed a recombinant anti-PLGF bivalent nanobody based on the affinity enhancement mutant form of anti-PLGF nanobody to suppress the angiogenesis progression. Thereafter, the bivalent nanobody (bi-Nb) was cloned and then expressed into a bacterial system. Afterward, the purity was authorized using western blot assay and the affinity was assessed using ELISA. In this regard, proliferation, 3D capillary tube formation, and migration assays were employed as functional assays. The obtained data were analyzed using t-test and P < 0.05 was considered as statistically significant. The results indicate that the bivalent nanobody could inhibit proliferation, mobility, and formation of endothelial cell capillary-like structure. Moreover, the EC50 was estimated for endothelial cell's proliferation and capillary tube's formation to be about 100 ng/ml and 65 ng/ml, respectively. Migration of MCF-7 was inhibited as about 69%, rather than the control. Accumulation of data have shown that targeting of angiogenic factors like VEGF via monoclonal antibodies or nanobodies can be useful in the suppression of tumor progression. Also, the inhibition of PLGF with monoclonal antibody indicated that it is significant in angiogenesis suppression. However, due to intrinsic properties of nanobodies, they are suggested to be used. Since the small size is rapidly removed through liver or kidney system, so it is important to use bivalent or polymeric forms for extending the half-life. Our findings indicated that the inhibition of PLGF can prevent growth and proliferation of endothelial cells and tumor cells through the bivalent nanobody. So, it is suggested as a novel therapeutic agent for angiogenesis suppression.

Using Omics Technologies and Systems Biology to Identify Epitope Targets for the Development of Monoclonal Antibodies Against Antibiotic-Resistant Bacteria

Over the past few decades, antimicrobial resistance has emerged as an important threat to public health due to the global dissemination of multidrug-resistant strains from several bacterial species. This worrisome trend, in addition to the paucity of new antibiotics with novel mechanisms of action in the development pipeline, warrants the development of non-antimicrobial approaches to combating infection caused by these isolates. Monoclonal antibodies (mAbs) have emerged as highly effective molecules for the treatment of multiple diseases. However, in spite of the fact that antibodies play an important role in protective immunity against bacteria, only three mAb therapies have been approved for clinical use in the treatment of bacterial infections. In the present review, we briefly outline the therapeutic potential of mAbs in the treatment of bacterial diseases and discuss how their development can be facilitated when assisted by “omics” technologies and interpreted under a systems biology paradigm. Specifically, methods employing large genomic, transcriptomic, structural, and proteomic datasets allow for the rational identification of epitopes. Ideally, these include those that are present in the majority of circulating isolates, highly conserved at the amino acid level, surface-exposed, located on antigens essential for virulence, and expressed during critical stages of infection. Therefore, these knowledge-based approaches can contribute to the identification of high-value epitopes for the development of effective mAbs against challenging bacterial clones.

Rational MD simulations for improvement the affinity of nanobody against PlGF (placenta growth factor): mutagenesis based on electrostatic interactions

AbbreviationsCOMcenter of mass distanceMDmolecular dynamicsMM-PBSAMolecular Mechanics Poisson-Boltzmann Surface AreaNbnanobodyPlGFplacenta growth factorRgradius of gyrationRMSDroot mean-square deviationSASAsolvent-accessible surface areaVEGFvascular endothelial growth factor.

Trends in therapeutic antibody affinity maturation: From in-vitro towards next-generation sequencing approaches

Current advances in antibody engineering driving the strongest growth area in biotherapeutic agents development. Affinity improvement that is mainly important for biological activity and clinical efficacy of therapeutic antibodies, has still remained a challenging task. In the human body, during a course of immune response affinity maturation increase antibody activity by several rounds of somatic hypermutation and clonal selection in the germinal center. The final outputs are antibodies representing higher affinity and specificity against a particular antigen. In the realm of biotechnology, exploring of mutations which improve antibody affinity while preserving its specificity and stability is an extremely time-consuming and laborious process. Recent advances in computational algorithms and DNA sequencing technologies help researchers to redesign antibody structure to achieve desired properties such as improved binding affinity. In this review, we briefly described the principle of affinity maturation and different corresponding in vitro techniques. Also, we recapitulated the most recent advancements in the field of antibody affinity maturation including computational approaches and next-generation sequencing (NGS).