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Every biological foundation model, evaluated and ranked by the bio.rodeo team
Showing 241–264 of 392 filtered models
Protein binder design that inverts the frozen Boltz-1 all-atom predictor, targeting small molecules, nucleic acids, metals, and modified residues.
Structure-based drug design model pairing an autoregressive transformer for ligand graphs with a diffusion head for 3D binding-pose coordinates.
Open therapeutics foundation models from Google, built on Gemma-2, for drug-discovery property prediction and conversational reasoning.
De novo binder design across small molecules, peptides, and antibodies from one geometric latent diffusion model over graphs of molecular blocks.
Ames mutagenicity prediction conditioned on bacterial tester strain and S9 metabolic activation, holding sensitivity on chemically novel compounds.
Transferable coarse-grained force field for molecular dynamics of proteins, RNA, and lipids, built on the MACE equivariant graph architecture.
Autoregressive 3D structure model built on an octree tokenizer, spanning molecule generation, molecular docking, and protein pocket prediction.
Chemical language model family for target-aware ligand generation, conditioning molecule design on protein embeddings from a companion protein model.
Small-molecule foundation model pairing a graph encoder with a Transformer SMILES decoder so compounds can be optimized directly in encoding space.
Binding affinity scoring for protein-ligand and lipid-protein pairs without a docked pose, used to rank the protein corona on candidate liposomes.
Synthesis planning model that generates full synthetic routes from Enamine building blocks and reaction templates for any target small molecule.
Natural product chemistry prediction from biosynthetic gene clusters, assigning ChemOnt ontology classes from the cluster's Pfam domain composition.
Enzyme turnover number (kcat) prediction from sequence and substrate SMILES, scaling to genome-wide kinetic parameters for metabolic modeling.
All-atom generative foundation model for biomolecular structure, unifying protein-ligand docking, structure-based drug design, and peptide design.
Structure-based drug design framework that scores interaction-aware fragments against protein subpockets, then diffuses a 3D scaffold to link them.
Generative foundation model that co-generates sequence and 3D coordinates for proteins, small molecules, and crystals under functional objectives.
Cross-domain molecular foundation model encoding small molecules, protein pockets, and their complexes in 2D and 3D on one Transformer backbone.
Full-atom flow matching model that generates a ligand and the induced-fit holo pocket together, starting from an apo binding site.
Latent diffusion model generating 3D drug-like molecules and inorganic crystals from one shared all-atom autoencoder and Transformer denoiser.
Drug-combination safety prediction that fuses molecular structure, pathway knowledge, cell viability, and transcriptomic response to perturbation.
Secondary metabolite structure prediction from microbial biosynthetic gene clusters, generating SMILES strings from Pfam functional-domain tokens.
Structure-based 3D molecule generation that denoises a ligand at atom level and motif level at once, conditioned on the target protein's pocket.
Bacterial protein-compound binding affinity prediction from amino acid sequence and SMILES, evaluated zero-shot on two species held out of training.
PROTAC degradation prediction from molecular graphs of the target, linker, and E3 ligase, combining cross-attention with contrastive learning.