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protein design framework integrating Boltz, AlphaFold2, OpenFold3, ProteinMPNN, and ESM via JAX-based

protein binder design pipeline using AlphaFold2 backpropagation, MPNN, and PyRosetta

AlphaFold/ESMFold accessible implementation with AF3 JSON export, database updates

protein equilibrium conformations 100,000× faster than MD simulations, predicting

protein folding model using only general-purpose transformer layers, scaled

Cross-platform system optimizations for accelerating AlphaFold3 training with 1.73

Learning the language of protein-protein interactions

protein structure determination from electron density with high accuracy (3DEM/EMBL

proteins via backpropagation through compositional design constraints parameterized by structure

First fully open-source model achieving AlphaFold3-level accuracy with

protein conformational ensembles, covering both experimental PDB states and molecular

protein language model using 3D structural vocabulary (Foldseek) for joint

protein language model translating between protein sequence and structure, finetuned

protein sequence design over evolutionary-scale databases, supporting unconditional generation

protein-ligand complex structures with dynamic receptor conformational flexibility, enabling

protein language models via sparse autoencoders, enabling mechanistic understanding of PLM representations

protein binding pocket, enabling scaffold hopping and linker design workflows

Universal 3D molecular pretraining framework with 209M conformations, scaling to

proteins trained on thousands of GPUs and Google TPUs using

Diffusion-based molecular docking achieving SOTA blind docking performance, treating

protein sequence design in the context of small-molecule ligands

Large-scale biomolecular instruction dataset for chemistry/biology LLMs (ICLR2024)

protein sequence design (inverse folding) from backbone structures, achieving 52.4% sequence