Researchers have made significant strides in predicting a protein’s structure from its sequence using large language models. However, this method hasn’t been as effective for antibodies, primarily due to their hypervariability. This makes it challenging to identify treatments for SARS-CoV-2 and other infectious diseases. MIT researchers have developed a computational technique that more accurately predicts…
New AI model enhances antibody structure prediction for drug development
MIT researchers have developed AbMap, a computational model that predicts antibody structures with improved accuracy. This could accelerate the development of treatments for infectious diseases like SARS-CoV-2. Unlike existing AI models, AbMap focuses on antibodies’ hypervariable regions — highly diverse segments critical for binding pathogens — and overcomes limitations in previous protein modeling approaches. Using…