A conformation-based phage-display panning to screen neutralizing anti-VEGF VHHs with VEGFR2 mimicry behavior

Expression of VEGFR2 Ligand Binding Domain in Pichia pink™ 4 Cells and Evaluation of Its Interactions with VEGF-A165 Receptor Binding Domain

Vascular endothelial growth factor A165 (VEGF-A165) and VEGF receptor 2 (KDR) are important mediators of angiogenesis. We aimed to express the soluble KDR ligand-binding domain (sKDR1-3) and evaluate its interaction with the VEGF-A165 receptor-binding domain (VEGFA165-RBD). sKDR1-3 DNA was designed and subcloned into pPinkα-HC plasmid. The cassette was transfected into the Pichia pink™ 4 genome by homologous recombination. We optimized the expression of sKDR1-3 under the induction of different methanol concentrations. VEGFA165-RBD was expressed in E. coli BL21 harboring pET28a( +)─VEGFA165-RBD vector under induction with IPTG with/without lactose. Interaction and biological activity of sKDR1-3 and VEGFA165-RBD were investigated by ELISA and anti-proliferation tests. sKDR1-3 migrated on SDS-PAGE gel as a 35-180 kDa protein due to glycosylation. The relative expression level of sKDR1-3 under 1% methanol was higher than 0.5% and 4% methanol induction. IPTG and cysteine were suitable for induction and refolding of VEGFA165-RBD. 25 ng sKDR1-3 and 20 ng VEGFA165-RBD showed strong binding. sKDR1-3 bound to VEGFA165-RBD and VEGF-A165 with dissociation constants of 0.148 and 0.2 nM, respectively. 4-10 nM concentrations of sKDR1-3 inhibited the proliferation of HUVE cells induced by 5 nM VEGFA165-RBD. In consideration, sKDR1-3 in the nanomolar concentration range, is a promising anticancer drug to inhibit angiogenesis.

A dual computational and experimental strategy to enhance TSLP antibody affinity for improved asthma treatment

Thymic stromal lymphopoietin is a key cytokine involved in the pathogenesis of asthma and other allergic diseases. Targeting TSLP and its signaling pathways is increasingly recognized as an effective strategy for asthma treatment. This study focused on enhancing the affinity of the T6 antibody, which specifically targets TSLP, by integrating computational and experimental methods. The initial affinity of the T6 antibody for TSLP was lower than the benchmark antibody AMG157. To improve this, we utilized alanine scanning, molecular docking, and computational tools including mCSM-PPI2 and GEO-PPI to identify critical amino acid residues for site-directed mutagenesis. Subsequent mutations and experimental validations resulted in an antibody with significantly enhanced blocking capacity against TSLP. Our findings demonstrate the potential of computer-assisted techniques in expediting antibody affinity maturation, thereby reducing both the time and cost of experiments. The integration of computational methods with experimental approaches holds great promise for the development of targeted therapeutic antibodies for TSLP-related diseases.

Synergistic Screening of Peptide-Based Biotechnological Drug Candidates for Neurodegenerative Diseases Using Yeast Display and Phage Display

Peptide therapeutics are robust and promising molecules for treating diverse disease conditions. These molecules can be developed from naturally occurring or mimicking native peptides, through rational design and peptide libraries. We developed a new platform for the rapid screening of the peptide therapeutics for disease targets. In the course of the study, we aimed to employ our platform to screen a new generation of peptide therapeutic candidates against aggregation-prone protein targets. Two peptide drug candidates were screened for protein aggregation-prone diseases, namely, Parkinson's and Alzheimer's diseases. Currently, there are several therapeutic applications that are only effective in masking or slowing down symptom development. Nonetheless, different approaches are being developed for inhibiting amyloid aggregation in the secondary nucleation phase, which is critical for amyloid fibril formation. Instead of targeting secondary nucleated protein structures, we tried to inhibit the aggregation of monomeric amyloid units as a novel approach for halting the disease condition. To achieve this, we combined yeast surface display and phage display library platforms. We expressed α-synuclein, amyloid β40, and amyloid β42 on the yeast surface, and we selected peptides by using phage display library. After iterative biopanning cycles optimized for yeast cells, several peptides were selected for interaction studies. All of the peptides have been used for in vitro characterization methods, which are quartz crystal microbalance-dissipation (QCM-D) measurement, atomic force microscopy (AFM) imaging, dot-blotting, and ThT assay, and some of them have yielded promising results in blocking fibrillization. The rest of the peptides, although, interacted with amyloid units which made them usable as a sensor molecule candidate. Therefore, peptides selected by yeast surface display and phage display library combination are good choice for diverse disease-prone molecule inhibition, particularly those inhibiting fibrillization. Additionally, these selected peptides can be used as drugs and sensors to detect diseases quickly and halt disease progression.

Progress on Phage Display Technology: Tailoring Antibodies for Cancer Immunotherapy

The search for innovative anti-cancer drugs remains a challenge. Over the past three decades, antibodies have emerged as an essential asset in successful cancer therapy. The major obstacle in developing anti-cancer antibodies is the need for non-immunogenic antibodies against human antigens. This unique requirement highlights a disadvantage to using traditional hybridoma technology and thus demands alternative approaches, such as humanizing murine monoclonal antibodies. To overcome these hurdles, human monoclonal antibodies can be obtained directly from Phage Display libraries, a groundbreaking tool for antibody selection. These libraries consist of genetically engineered viruses, or phages, which can exhibit antibody fragments, such as scFv or Fab on their capsid. This innovation allows the in vitro selection of novel molecules directed towards cancer antigens. As foreseen when Phage Display was first described, nowadays, several Phage Display-derived antibodies have entered clinical settings or are undergoing clinical evaluation. This comprehensive review unveils the remarkable progress in this field and the possibilities of using clever strategies for phage selection and tailoring the refinement of antibodies aimed at increasingly specific targets. Moreover, the use of selected antibodies in cutting-edge formats is discussed, such as CAR (chimeric antigen receptor) in CAR T-cell therapy or ADC (antibody drug conjugate), amplifying the spectrum of potential therapeutic avenues.

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.

VHH Structural Modelling Approaches: A Critical Review

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

Discovery of a New Analgesic Peptide, Leptucin, from the Iranian Scorpion, Hemiscorpius lepturus

Hemiscorpius lepturus scorpion stings do not induce considerable pain based on epidemiological surveys conducted in the southwest part of Iran. Accordingly, this study was aimed to identify the analgesic molecule in H. lepturus venom by analyzing a cDNA library of the scorpion venom gland looking for sequences having homology with known animal venom analgesic peptides. The analgesic molecule is a cysteine rich peptide of 55 amino acids. the synthetic peptide was deprotected and refolded. RP-HPLC, Ellman's, and DLS assays confirmed the refolding accuracy. Circular dichroism (CD) showed helix and beta sheet contents. This peptide, called leptucin, demonstrated 95% analgesic activity at the dose of 0.48 mg/kg in hot plate assay. Leptucin at the doses of 0.32, 0.48, and 0.64 mg/kg showed 100% activity in thermal tail flick test. No hemolysis or cytotoxicity was observed at 8 and 16 µg. Histopathology evaluations indicated no hepatotoxicity, nephrotoxicity, and cardiotoxicity. We thus report that leptucin is the analgesic agent of H. lepturus venom. Regarding the high in vivo efficacy of leptucin and the fact it shows no observable toxicity, it could be suggested as a drug lead in a preclinical study of acute pain as well as the study of its mechanism of action.

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 phage display-mediated immunoassay for the detection of vascular endothelial growth factor

Because of the critical role of vascular endothelial growth factor (VEGF) in angiogenesis and its significantly increased serum levels in early stages of cancer, VEGF is considered an important prognostic biomarker in different cancers. Herein, the amplification power of PCR combined with phage displaying anti-VEGF VHH, a sensitive real-time immunoassay, was precisely designed based on phage display-mediated immuno-PCR (PD-IPCR) for the detection of VEGF. This system benefits from strong and specific binding of antigen and antibody in a sandwich immunosorbent assay platform using avastin (anti-VEGF monoclonal antibody) as the capture antibody. The anti-VEGF phage particles were used as both anti-VEGF agent and DNA template in the PD-IPCR. Anti-VEGF phage ELISA showed a linear range of 3-250 ng/ml and a limit of detection (LOD) of 1.1 ng/ml. Using the PD-IPCR method, the linear range of VEGF detection was found to be 0.06-700 ng/ml, with a detection limit of 3 pg/ml. The recovery rate in serum ranged from 83% to 99%, with a relative standard deviation of 1.2-4.9%. These values indicate that the method has good sensitivity for use in clinical analysis. The proposed method was successfully applied to the clinical determination of VEGF in human serum samples, and the results showed excellent correlation with conventional ELISA (R² = 0.995). The novel immunoassay provides a specific and sensitive immunoassay protocol for VEGF detection at very low levels. Graphical abstract.

Enhanced sensitivity of VEGF detection using catalase-mediated chemiluminescence immunoassay based on CdTe QD/H2O2 system

Background

Since vascular endothelial growth factor (VEGF) is a significant regulator of cancer angiogenesis, it is essential to develop a technology for its sensitive detection. Herein, we sensitized a chemiluminescence (CL) immunoassay through the combination of H₂O₂-sensitive TGA-CdTe quantum dot (QD) as signal transduction, dextran as a cross-linker to prepare enzyme-labeled antigen and the ultrahigh bioactivity of catalase (CAT) as reporter enzyme.

Results

Under the optimized experimental conditions, the chemiluminescence enzyme-linked immunosorbent assay (CL-ELISA) method can detect VEGF in the excellent linear range of 2–35,000 pg mL⁻¹, with a detection limit (S/N = 3) of 0.5 pg mL⁻¹ which was approximately ten times lower than the commercial colorimetric immunoassay. This proposed method has been successfully applied to the clinical determination of VEGF in the human serum samples, and the results illustrated an excellent correlation with the conventional ELISA method (R² = 0.997). The suitable recovery rate of the method in the serum ranged from 97 to 107%, with a relative standard deviation of 1.2% to 13.4%.

Conclusions

The novel immunoassay proposes a highly sensitive, specific, and stable method for very low levels detection of VEGF that can be used in the primary diagnosis of tumors. With the well-designed sensing platform, this approach has a broad potential to be applied for quantitative analysis of numerous disease-related protein biomarkers for which antibodies are available.

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

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