Monoclonal antibodies are the largest class of biotherapeutics and development of a good antibody drug begins with engineering and selection of candidates with the desired properties. Many technologies are used to generate and optimize antibodies such as immunization, yeast-surface and phage display, next-gen sequencing, molecular biology, and computational tools such as Rosetta and AlphaFold. Beyond antibodies, the same approaches can be used to develop tools and therapeutics from engineered ligands, receptors, and enzymes.
This Bench Tips webinar will delve into some combinatorial and computational approaches used to engineer antibodies, as well as methods to characterize the properties of antibodies including, binding affinity and structural interactions. The speakers will share their knowledge and expertise with the community and answer questions posed by the audience
In this webinar, you will hear about
- Approaches for antibody design including structure-guided design and sequence optimization
- How to generate antibodies using combinatorial libraries and affinity maturation
- Tools and assays to analyze and characterize antibody structure, design, and function
- Improving the drug-like properties of antibodies like stability, half-life, and specificity
- Current methods using AI/ML for protein design, including sequence or structure design, property prediction, and scoring metrics
- Challenges with designing and engineering antibodies, ligands and receptors, and enzymes
Researchers interested in the following should attend
- Antibody drug development
- Assay development and protein characterization
- Immunology and immunotherapy
- Protein engineering
- Computational design and analysis
- Machine learning for protein design