Explore how epitope characterization enhances antibody therapeutics, ensuring specificity, reducing cross-reactivity, and advancing targeted treatment strategies.

MAGMA-seq is an integrated technology for antibody wide mutational scanning. DOI:10.1038/s41467-024-48072-zThe use of bioinformatics and computational methods were of high interest in several papers published this past week. Protein language models, akin to natural language processing tools, p

Fc-mediated antibody effector functions play an important role in the humoral immune response and form a necessary link between innate and adaptive immunity. The constant (Fc) region is the tail portion of an antibody that interacts with other components of the immune system, such as immune cells and complement proteins. Well-known functions include opsonization, antibody-dependent cell-mediated cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and complement activation.

Explore the process of custom antibody development – from antigen design & immunization to production & characterization – for precise research & clinical applications.

Explore how deep learning models like DeepH3 & DeepAb predict antibody structures, aiding in the design of high-affinity antibodies by modeling CDR loops & FV regions.

Learn how in silico tools like SCM & TAP assess antibody developability, predicting properties like viscosity, immunogenicity & stability for therapeutic success.

Explore how sequence, structural, therapeutic, and experimental databases revolutionize antibody engineering, enhancing discovery, design, and therapeutic development.

Learn how platforms like AlphaFold2 and IgFold transform antibody research with precise protein structure predictions, boosting antibody-antigen interaction studies.

Explore how AI models like CNNs and LSTMs optimize antibody research, predicting antigen specificity and advancing lead candidate generation for biotech innovation.