AI-Designed Mutation-Resistant Broad Neutralization Antibodies Against Multiple SARS-CoV-2 Strains
Artificial intelligence allows the analysis of big, ever-changing data such as the genome of a constantly evolving virus. In this study, AI was applied to the computational design of broad neutralization antibodies against over 1,300 historical SARS-CoV-2 strains at very small computational cost.
The AI-designed antibodies showed high potency against multiple strains in pseudo-virus and real virus neutralization assays, and a very high cross-binding hit rate against different RBD mutants in ELISA — shedding light on future therapeutic designs for pandemic preparedness.
Key Learning Objectives
- AI can design antibodies with in vitro efficacy and drastically reduce the time and cost of antibody engineering such as affinity maturation
- AI can design cross-binding antibodies against large antigen populations such as viral mutant strains
- AI can reveal patterns of viral evolution and allow the design of antibodies against future strains
Watch Now: AI-Designed Mutation-Resistant Broad Neutralization Antibodies Against Multiple SARS-CoV-2 Strains
This webinar is available on demand. Fill in the form to watch the full recording — we'll email you the link too.
- April 6, 2022
- kbiinfo@krishgen.com
- +91 22 49198700
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