All Competitors

Open-source Apache-2.0 reproduction of AlphaFold3 that predicts all-atom structures of proteins, RNA, DNA, small molecules, and their complexes.

Molecular graph transformer for ADMET property prediction, pretrained on 11M molecules under a joint SMILES-reconstruction and contrastive objective.

Open model that jointly predicts biomolecular structure and small-molecule binding affinity, approaching FEP+ accuracy in seconds on a single GPU.

Genomic foundation model trained on 9.3 trillion DNA base pairs across all domains of life, with 40B parameters and a 1-million-token context.

Fragment-based molecular generation by masked discrete diffusion over SAFE strings, covering de novo design, linker design, and lead optimization.

3D latent diffusion model for synthetic CT, generating volumes up to 512x512x768 voxels with paired masks across 127 anatomical structures.

Medical image segmentation foundation model for 3D CT and MRI, covering 127 anatomical classes automatically plus interactive point-prompt refinement.

Trainable, open-source reimplementation of AlphaFold2 for protein structure prediction that matches its accuracy and runs 3-5x faster.

Generalist cell instance segmentation for microscopy, pairing a SAM ViT-B encoder with flow-field decoding trained on 15K annotated images.

De novo protein design diffusion model that generates backbone structures conditioned on binding targets, symmetry constraints, and functional motifs.

Message passing neural network for fixed-backbone protein sequence design. Achieves 52.4% native sequence recovery, far surpassing Rosetta's 32.9%.

Small-molecule generation over SMILES through a fixed-size latent space dense enough that gradient-free search over it optimizes chemical properties.

Protein structure prediction from a single sequence, with no multiple sequence alignment. Folds a 384-residue protein in 14.2 seconds on one GPU.

Rigid protein-protein docking model that predicts a complex from two unbound structures in one pass, with no candidate sampling or refinement.

Protein complex structure prediction model extending AlphaFold 2 with paired MSA processing and ipTM scoring for multi-chain, multimeric assemblies.

Chemical language model for small-molecule drug discovery, embedding SMILES for property prediction and sampling new molecules from its latent space.

Protein structure prediction model that folds amino acid sequences into 3D structures with atomic accuracy, scoring a median GDT of 92.4 at CASP14.