ChatterjeeLab/CupOFMoCA

Target-Conditioned Molecular Ideation Model for Drug Discovery Research

NucleusDiff

Molexar-10M Base is the unconditional base model for Molexar, a unified multimodal molecular foundation model for drug design. It is trained as an autoregressive molecular language model over Fragment-SELFIES, a BRICS-fragment molecular language with validity-preserving decoding and…

Checkpoints for unconditional 3D molecular generation on QM9, GEOM-Drugs and ChEMBL3D, plus GEOM-Drugs scaffold decoration and CrossDocked scaffold decoration in protein pockets. The releases include the configurations, vocabularies and training distributions needed for their inference workflows.

This model is a lightweight model pre-trained on SELFIES (Self-Referencing Embedded Strings) representations of molecules. It is trained on 2.7M unique and valid molecules taken from COCONUTDB and ChemBL34, with 7.3M total generated masked examples.

Trained checkpoints of CausalBind.