S. Nakamura
@maikohaaaan.bsky.social
Pinned
S. Nakamura
@maikohaaaan.bsky.social
· Feb 9
Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning - Communications Chemistry
Designing molecules with desirable properties is a critical endeavor in drug discovery, however, synthetic accessibility remains limited in the existing compound exploration models. Here, the authors ...
doi.org
Very happy to introduce our new paper "Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning": doi.org/10.1038/s420....
#cheminformatics #CompChem
#cheminformatics #CompChem
Reposted by S. Nakamura
This week's #RDKit blog post shows how to create simple protein--ligand interaction diagrams.
I think there's potential to take this a bit further...
greglandrum.github.io/rdkit-blog/p...
I think there's potential to take this a bit further...
greglandrum.github.io/rdkit-blog/p...
Drawing simple protein–ligand interaction diagrams with the RDKit – RDKit blog
Quick, but useful
greglandrum.github.io
September 26, 2025 at 3:58 PM
This week's #RDKit blog post shows how to create simple protein--ligand interaction diagrams.
I think there's potential to take this a bit further...
greglandrum.github.io/rdkit-blog/p...
I think there's potential to take this a bit further...
greglandrum.github.io/rdkit-blog/p...
Reposted by S. Nakamura
Our new preprint PharmacoForge: Pharmacophore Generation with Diffusion Models is out now! PharmacoForge quickly generates pharmacophores for a given protein pocket that identify key binding features and find useful compounds in a pharmacophore search. Check it out! 🧪 doi.org/10.26434/che...
May 27, 2025 at 7:11 PM
Our new preprint PharmacoForge: Pharmacophore Generation with Diffusion Models is out now! PharmacoForge quickly generates pharmacophores for a given protein pocket that identify key binding features and find useful compounds in a pharmacophore search. Check it out! 🧪 doi.org/10.26434/che...
Reposted by S. Nakamura
The new #RDKit blog post, inspired by a question from @valencekjell.com, looks at the impact of molecular size on similarity thresholds.
greglandrum.github.io/rdkit-blog/p...
greglandrum.github.io/rdkit-blog/p...
The impact of molecular size on similarity. – RDKit blog
An exploration of how molecular size influences fingerprint similarity.
greglandrum.github.io
June 20, 2025 at 4:24 AM
The new #RDKit blog post, inspired by a question from @valencekjell.com, looks at the impact of molecular size on similarity thresholds.
greglandrum.github.io/rdkit-blog/p...
greglandrum.github.io/rdkit-blog/p...
Reposted by S. Nakamura
Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀
June 6, 2025 at 1:46 PM
Excited to unveil Boltz-2, our new model capable not only of predicting structures but also binding affinities! Boltz-2 is the first AI model to approach the performance of FEP simulations while being more than 1000x faster! All open-sourced under MIT license! A thread… 🤗🚀
Reposted by S. Nakamura
Stereoretentive Radical Cross-Coupling
Authors: Jiawei Sun, Jiayan He, Luca Massaro, David Cagan, Jet Tsien, Yu Wang, Flynn Attard, Jillian Smith, Jason Lee, Yu Kawamata, Phil Baran
DOI: 10.26434/chemrxiv-2025-h9snj
Authors: Jiawei Sun, Jiayan He, Luca Massaro, David Cagan, Jet Tsien, Yu Wang, Flynn Attard, Jillian Smith, Jason Lee, Yu Kawamata, Phil Baran
DOI: 10.26434/chemrxiv-2025-h9snj
March 14, 2025 at 2:23 PM
Stereoretentive Radical Cross-Coupling
Authors: Jiawei Sun, Jiayan He, Luca Massaro, David Cagan, Jet Tsien, Yu Wang, Flynn Attard, Jillian Smith, Jason Lee, Yu Kawamata, Phil Baran
DOI: 10.26434/chemrxiv-2025-h9snj
Authors: Jiawei Sun, Jiayan He, Luca Massaro, David Cagan, Jet Tsien, Yu Wang, Flynn Attard, Jillian Smith, Jason Lee, Yu Kawamata, Phil Baran
DOI: 10.26434/chemrxiv-2025-h9snj
Very happy to introduce our new paper "Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning": doi.org/10.1038/s420....
#cheminformatics #CompChem
#cheminformatics #CompChem
Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning - Communications Chemistry
Designing molecules with desirable properties is a critical endeavor in drug discovery, however, synthetic accessibility remains limited in the existing compound exploration models. Here, the authors ...
doi.org
February 9, 2025 at 11:17 AM
Very happy to introduce our new paper "Molecular optimization using a conditional transformer for reaction-aware compound exploration with reinforcement learning": doi.org/10.1038/s420....
#cheminformatics #CompChem
#cheminformatics #CompChem