An antibody scanning method for the detection of α-synuclein oligomers in the serum of Parkinson's disease patients

Improved Imaging Surface for Quantitative Single-Molecule Microscopy

Preventing nonspecific binding is essential for sensitive surface-based quantitative single-molecule microscopy. Here we report a much-simplified RainX-F127 (RF-127) surface with improved passivation. This surface achieves up to 100-fold less nonspecific binding from protein aggregates compared to commonly used polyethylene glycol (PEG) surfaces. The method is compatible with common single-molecule techniques including single-molecule pull-down (SiMPull), super-resolution imaging, antibody-binding screening and single exosome visualization. This method is also able to specifically detect alpha-synuclein (α-syn) and tau aggregates from a wide range of biofluids including human serum, brain extracts, cerebrospinal fluid (CSF) and saliva. The simplicity of this method further allows the functionalization of microplates for robot-assisted high-throughput single-molecule experiments. Overall, this simple but improved surface offers a versatile platform for quantitative single-molecule microscopy without the need for specialized equipment or personnel.

A Potent Sybody Selectively Inhibits α-Synuclein Amyloid Formation by Binding to the P1 Region

Increasing research efforts focus on exploiting antibodies to inhibit the amyloid formation of neurodegenerative proteins. Nevertheless, it is challenging to discover antibodies that inhibit this process in a specific manner. Using ribosome display, we screened for synthetic single-domain antibodies, i.e., sybodies, of the P1 region of α-synuclein (residues 36-42), a protein that forms amyloid in Parkinson's disease and multiple-system atrophy. Hits were assessed for direct binding to a P1 peptide and the inhibition of amyloid formation. We discovered a sybody, named αSP1, that inhibits amyloid formation of α-synuclein at substoichiometric concentrations in a specific manner, even within highly crowded heterogeneous mixtures. Fluorescence resonance energy transfer-based binding assays and seeding experiments with and without αSP1 further demonstrate the importance of the P1 region for both primary and secondary nucleation mechanisms of amyloid assembly.

Single-domain antibody-based protein degrader for synucleinopathies

Synucleinopathies are a group of neurodegenerative diseases characterized by the accumulation of α-synuclein (α-syn) in the brain, leading to motor and neuropsychiatric symptoms. Currently, there are no known cures for synucleinopathies, and treatments mainly focus on symptom management. In this study, we developed a single-domain antibody (sdAb)-based protein degrader with features designed to enhance proteasomal degradation of α-syn. This sdAb derivative targets both α-syn and Cereblon (CRBN), a substrate-receptor for the E3-ubiquitin ligase CRL4CRBN, and thereby induces α-syn ubiquitination and proteasomal degradation. Our results indicate that this therapeutic candidate enhances proteasomal degradation of α-syn, in addition to the endogenous lysosomal degradation machinery. By promoting proteasomal degradation of α-syn, we improved clearance of α-syn in primary culture and mouse models of synucleinopathy. These findings indicate that our sdAb-based protein degrader is a promising therapeutic candidate for synucleinopathies. Considering that only a small percentage of antibodies enter the brain, more potent sdAbs with greater brain entry than whole antibodies could enhance clinical benefits of antibody-based therapies.

Single-Domain Antibody-Based Protein Degrader for Synucleinopathies

Synucleinopathies are a group of neurodegenerative diseases characterized by the accumulation of α-synuclein (α-syn) in the brain, leading to motor and neuropsychiatric symptoms. Currently, there are no known cures for synucleinopathies, and treatments mainly focus on symptom management. In this study, we developed a single-domain antibody (sdAb)-based protein degrader with features designed to enhance proteasomal degradation of α-syn. This sdAb derivative targets both α-syn and Cereblon (CRBN), a substrate-receptor for the E3-ubiquitin ligase CRL4CRBN, and thereby induces α-syn ubiquitination and proteasomal degradation. Our results indicate that this therapeutic candidate enhances proteasomal degradation of α-syn, in addition to the endogenous lysosomal degradation machinery. By promoting proteasomal degradation of α-syn, we improved clearance of α-syn in primary culture and mouse models of synucleinopathy. These findings indicate that our sdAb-based protein degrader is a promising therapeutic candidate for synucleinopathies. Considering that only a small percentage of antibodies enter the brain, more potent sdAbs with greater brain entry than whole antibodies could enhance clinical benefits of antibody-based therapies.

Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties

Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.