Molecular Generation

RFdiffusion is a protein backbone diffusion project supporting unconditional generation, motif constraints and binder design.

Molecular Generation

AIDDISON Explorer is a hosted drug-discovery platform that generates and ranks molecular candidates against target profiles, design constraints, predicted properties and synthetic feasibility.

Molecular Generation · Drug Discovery

Chemistry42 is a small-molecule discovery platform combining generative design, retrosynthesis, ADMET and selectivity prediction, and physics-based prioritization for hit identification and lead optimization.

Molecular Generation · Drug Discovery

Makya is Iktos’s generative AI SaaS platform for de novo molecular design, combining project objectives, synthesis constraints, and ligand- or structure-based modeling to guide compound selection.

Molecular Generation · Drug Discovery

molSimplify generates inorganic coordination and intermolecular complexes for computational screening, with bundled neural networks for selected properties of octahedral transition metal complexes.

Molecular Generation · Computational Chemistry

FEgrow supports interactive ligand-series construction for free-energy preparation, with documented active-learning examples and Dask-based acceleration for molecular design workflows.

Molecular Generation · Drug Discovery

SELFIES is a molecular string representation and Python library for translating SMILES, preparing token encodings, and generating molecular graphs under configurable semantic constraints.

Molecular Generation · Cheminformatics

GEOM provides 37 million energy- and statistical-weight-annotated molecular conformations for over 450,000 molecules, with MessagePack data, RDKit objects, and loading and analysis tutorials.

Molecular Generation · Computational Chemistry

MOSES combines a ZINC-derived molecular dataset, generation baselines and evaluation metrics to benchmark the validity, diversity and novelty of generated molecules.

Molecular Generation

GuacaMol is a Python benchmarking package for de novo molecular design, with distribution-learning and goal-directed evaluations plus standardized ChEMBL-derived datasets.

Molecular Generation

REINVENT is a Python molecular-design toolkit that uses generative models, reinforcement learning and transfer learning for configurable small-molecule generation and optimization.

Molecular Generation · Drug Discovery

Official research code for E(3)-equivariant diffusion models that generate 3D molecules, with QM9 and GEOM-Drugs training workflows, sample analysis, and property-conditioned generation.

Molecular Generation

GeoDiff is a geometric diffusion model for molecular conformation generation, with official code for GEOM-based training, checkpoint sampling, and conformation and property evaluation.

Molecular Generation · Computational Chemistry

GraphAF is a flow-based autoregressive model for molecular graph generation, with a reference-code link and a README update pointing to an implementation in TorchDrug.

Molecular Generation

JT-VAE is the official Junction Tree Variational Autoencoder implementation for molecular graph generation, with VAE training code and scripts for Bayesian optimization and joint property-predictor training.

Molecular Generation

MoFlow is an invertible molecular graph generation model with documented workflows for QM9 and zinc250k training, reconstruction, latent-space sampling, interpolation and property optimization.

Molecular Generation

MolGPT trains a small custom GPT with next-token prediction on MOSES and Guacamol for unconditional and conditional molecular generation, with trained weights and Ecco-based saliency analysis linked.

Molecular Generation

Uni-Mol is a 3D molecular representation learning framework with molecular and protein-pocket models, supported by related tools for property prediction, conformation modeling and docking.

Molecular Property Prediction · Molecular Generation