Monoclonal and Polyclonal Antibodies Research

The paper develops a method combining PURE ribosome display, NGS, and microbial secretion to identify high-affinity antibody variants.

This paper designs antibody sequences and structures using a diffusion model guided by developability properties like solubility and folding stability.

This paper develops a method to produce bifunctional antibodies with high mannose 6-phosphate glycans for lysosomal degradation of target proteins.

This paper develops a competition assay using homogenous TR-FRET to rank the affinities of high-affinity monoclonal antibodies and antibody-drug conjugates for a common antigen, enabling scalable and low-cost evaluation.

This paper introduces Nanovials for function-first antibody discovery, enabling high-affinity antibody identification against membrane-bound targets.

This paper introduces Fusion, a de novo assembler for antibody sequences, demonstrating high accuracy in reconstructing monoclonal and mixed antibody sequences from mass spectrometry data.

This study compares synthetic and recombinant BMP-2-specific affibodies, finding they have similar structure and function but synthetic ones have lower endotoxin levels and higher yield.

The paper quantifies the plasticity of antibody developability by analyzing sequence and structure-based parameters in natural and human-engineered antibodies.

This study identifies CD177 as a novel IgG Fc receptor and shows that genetic variants in CD177 affect IgG-mediated functions like ADCC.

This paper develops humanized anti-FABP4 monoclonal antibodies that inhibit breast cancer tumor growth and metastasis by targeting FABP4's role in lipid metabolism.

This paper introduces an improved AHEAD platform using a synthetic β-estradiol induction system to accelerate antibody evolution in yeast.

This study shows shrimp hemocyanin (SHC) can replace keyhole limpet hemocyanin (KLH) as a carrier protein for hapten conjugation, offering better solubility and comparable immunogenicity in mammals.

This paper introduces a method to design antibodies by integrating antigen structure and sequence using a protein structural encoder and antibody language model, achieving better performance than existing methods.

NanoLAS 2.0 updates a nanobody database with improved search, 3D visualization, docking simulation, and epitope prediction tools.

The paper develops a cell-based assay to measure non-specific endocytosis of monoclonal antibodies and shows that high non-specific uptake correlates with target-independent clearance and low bioavailability.

This paper introduces a multivalent binding model to infer antibody structural features from systems serology data, revealing insights into vaccine efficacy and disease progression.

This study evaluates the thermostability and binding properties of scFv fragments from FDA-approved antibodies, showing that stable scFvs maintain antigen binding.

This study uses DeepAb to design antibody variants with enhanced stability and affinity without antigen information, showing 91% and 94% improvements in thermal/colloidal stability and affinity, respectively.

The paper determines the atomic structure of the FLAG peptide bound to anti-FLAG M2 Fab, identifies key interactions, and proposes a shorter FLAG-tag variant with equivalent binding.

The paper develops a computational model to analyze how bispecific antibodies interact with IL-6 and IL-8 receptors, showing how binding dynamics influence therapeutic efficacy.

The paper develops deep learning models using protein language models to predict polyreactivity of antibodies, outperforming structure-based models.

The paper introduces a method to map antibody-antigen interactions using SPID platform to enhance affinity prediction and optimize antibody design.

This study presents a framework for computationally screening mutations to modify antibody viscosity, showing that hydrophobic and electrostatic patches significantly affect viscosity, with positive charges causing the most increase.

The paper introduces MAGMA-seq, a technology for quantitative analysis of antibody sequence-function relationships, demonstrating its application in mapping antibody development pathways and identifying binding determinants.

This paper introduces EvolveX, a computational pipeline for designing stable single-domain antibodies with high affinity, demonstrating improved binding affinity to human targets.

This paper describes a method to generate biepitopic antibodies that activate TNF receptors by combining single-chain antibodies with IgG light chains, enhancing agonist activity without animal immunization.

This paper introduces a simple generative model, SAM, for antibody sequence modeling that outperforms complex models and provides fast, interpretable tools for antibody sequence analysis.

The paper uses single-cell RNA sequencing to study B cell differentiation and antibody production in camels, finding that HCAb and conventional Ab B cells share similar developmental trajectories.

This paper reviews 10 monoclonal antibodies, analyzes their pharmacokinetic and pharmacodynamic properties, and uses a machine learning model to assess subcutaneous bioavailability and optimize drug delivery.

This study uses single-cell transcriptomics and germline haplotype assembly to discover antibodies from human blood post-MMR vaccination, showing neutralization of measles virus.