All Competitors

De novo small molecule design for protein pockets, steering a discrete flow-matching generator with gradients from a frozen Boltz-2 affinity model.

Decoder-only foundation model that unifies sequences, 3D structures, and natural language for small molecules and proteins in one shared token space.

Synthesis-aware generative model for small molecules that proposes drug-like analogs with forward routes from commercially available building blocks.

Molecular reasoning model built on DeepSeek-7B, using chain-of-thought and reinforcement learning for property prediction, generation, and reactions.

Retrieval-augmented model for matched molecular pair transformations, proposing localized analog edits guided by retrieved reference compounds.

E(3)-equivariant diffusion model for macrocycle design that turns acyclic molecules into macrocycles, with a transformer choosing where to cyclize.

Generative language model for phenotype-driven drug discovery, proposing small-molecule structures from up- and down-regulated gene signatures.

Flow-matching model that jointly samples 3D de novo molecules and several low-energy conformers, extending to pocket-conditioned ligand design.

Diffusion model for structure-based drug design that jointly generates 3D ligands and holo pocket conformations from an apo protein structure.

Pretrained language model for 3D molecule generation in protein pockets, unifying de novo and fragment-based drug design in one multi-task framework.

Discrete flow generative model over fragmented SMILES for de novo, fragment-constrained, and property-optimized small-molecule drug design.

SE(3)-equivariant chemical language model for pocket-based 3D molecule generation, used to design an HPK1 inhibitor with in vivo anti-tumor efficacy.

Structure-based drug design pipeline generating 3D molecules in binding pockets, raising zero-shot CrossDocked2020 docking success from 53% to 64%.

Molecular reasoning language model for molecule captioning and text-to-molecule generation, trained by chain-of-thought distillation then reward RL.

Structure-based drug design framework pairing pharmacophore-guided latent diffusion with training-free, pocket-aware evolutionary optimization.

Structure-based drug design model that generates 3D ligands inside a protein pocket by interpolating distribution parameters instead of samples.

Synthesizable 3D molecule generation that jointly samples building blocks, reactions, and atomic coordinates, returning a synthesis route per design.

Structure-free ligand generation conditioned on a protein sequence alone, using masked diffusion over SMILES trained on 1.2M BindingDB active pairs.

Structure-based drug design model pairing SE(3)-equivariant diffusion with retrieval of pocket-matched scaffolds to generate ligands for a target.

Structure-based drug design by diffusing medicinal-chemistry fragments into a binding pocket, yielding synthesizable, selective, drug-like molecules.

Molecular conformation description language encoding 3D geometry as SMILES plus internal-coordinate tokens, turning 3D modeling into a sequence task.

Structure-based drug design model pairing an autoregressive transformer for ligand graphs with a diffusion head for 3D binding-pose coordinates.

Chemical language model family for target-aware ligand generation, conditioning molecule design on protein embeddings from a companion protein model.