Predicting Protein Conformational States with AI (2026)
How AI is moving beyond static AlphaFold structures to predict protein conformational states and ensembles in 2026, the methods, the limits, and why it matters.
Cryo-EM Meets AI: Structure Prediction in Drug Discovery
How cryo-EM and AI structure prediction work together in 2026 drug discovery — the pipeline, what AlphaFold-class models add, and the honest limitations.
RFdiffusion 2: How AI Now Designs Functional Proteins (2026)
RFdiffusion 2 explained — what changed, how it pairs with ProteinMPNN, success rates on real binder campaigns, and the open problems.
AlphaGenome Explained: Variant Effect Prediction at Scale (2026)
AlphaGenome explained — the long-range DNA model that predicts non-coding variant effects, how the architecture works, and what it changes for biology.
AlphaFold 3 Protein-Ligand Co-Folding: Architecture & Use Cases
AlphaFold 3 architecture explained — diffusion-based co-folding, protein-ligand prediction, training data, accuracy limits, and drug-discovery applications.
AlphaFold 3 and Protein Structure Prediction Explained
AlphaFold 3 explained — how the diffusion-based model predicts protein, DNA, and ligand structures, why it matters, and its real limitations.