Proteomics

Protein artificial intelligence is, without question, the most mature and publicly celebrated discipline within the “omics” family. When we discuss AI in biology, the conversation inevitably drifts toward the 2024 Nobel Prize in Chemistry—awarded jointly to David Baker for computational protein design, and to Demis Hassabis and John Jumper for protein structure prediction via AlphaFold. However, structure prediction was merely the opening act. Today, the frontier has rapidly shifted from static structure prediction to protein design (creating entirely new proteins), function prediction, and complex interaction modeling. In this seventh installment of the Agentic Omics series, we will dissect the current state of AI in proteomics, evaluate the monumental shifts from AlphaFold 2 to AlphaFold 3 and ESM-3, explore generative models like ProGen and RFdiffusion, and critically assess their real-world clinical impact in drug discovery. ...

Welcome to the first installment of Agentic Omics: When AI Reads the Book of Life. In this 24-part series, we will systematically review the state of the art of Artificial Intelligence (AI) across all major omics disciplines. We will explore how large language models, foundational transformer architectures, and eventually fully autonomous “Agentic Omics” systems are orchestrating domain-specific models to accelerate drug discovery, personalized medicine, and our fundamental understanding of biology. ...