Understanding how molecules interact is central to biology: from decoding how living organisms function to uncovering disease mechanisms and developing life-saving drugs. In recent years, models like ...

Artificial intelligence was used to aid the discovery of high-affinity antibodies, which are typically identified through directed evolution—a process that requires rounds of mutagenesis and selection ...

UM researchers have developed a deep learning model to predict compound protein interactions. GraphBAN is an inductive graph-based approach. The model is all about discovering new drug candidates in ...

Scientists developed an artificial intelligence tool that could accelerate the development of new high affinity antibody drugs. Scientists at University of California San Diego School of Medicine have ...

Exploring the biomedical interactions about chemical compounds and protein targets is crucial for drug discovery. Determining these interactions (DDI/DTI) not only reveals the potential synergistic ...

Scientists at University of California San Diego School of Medicine have developed an artificial intelligence (AI)-based strategy for discovering high-affinity antibody drugs. In the study, published ...

Researchers discover that some low-affinity immunomodulatory antibodies have greater anticancer activity than those with high affinity. Antibodies’ ability to bind specifically and tightly to target ...

DUBLIN--(BUSINESS WIRE)--The "Constrained Peptide Drugs Market - A Global and Regional Analysis: Focus on Peptide Type, Product, and Region-Wise Analysis - Analysis and Forecast, 2024-2040" report has ...