sekijima-lab / DiffIntLinks
☆17Updated 3 months ago
Alternatives and similar repositories for DiffInt
Users that are interested in DiffInt are comparing it to the libraries listed below
Sorting:
- Implementation of the Paper "iScore: A ML-Based Scoring Function for de novo Drug Discovery" by S.J. Mahdizadeh, and L.A. Eriksson (https…☆16Updated last year
- Code and notebook for our paper "Assessing interaction recovery of predicted protein-ligand poses"☆18Updated 11 months ago
- ☆16Updated 6 months ago
- AI-augmented R-group exploration in medicinal chemistry☆18Updated 11 months ago
- Augmented Memory and Beam Enumeration implementation☆25Updated last year
- This Code is for Fragment-wise 3D Structure-based Molecular Generation with Reliable Geometry☆27Updated 5 months ago
- ☆11Updated last year
- ☆23Updated 7 months ago
- ☆16Updated last year
- CReM-dock: generation of chemically reasonable molecules guided by molecular docking☆27Updated last week
- ☆51Updated 4 months ago
- Deep Learning-based Bioisosteric Replacements for Optimization of Multiple Molecular Properties☆21Updated last week
- A versatile workflow for the generation of receptor-based pharmacophore models for virtual screening☆30Updated 3 months ago
- ☆21Updated last week
- ☆13Updated last year
- Scaffold decoration and fragment linking with chemical language models and RL☆26Updated 5 months ago
- ☆12Updated 2 years ago
- EXPRORER: Rational cosolvents set construction method for cosolvent molecular dynamics (CMD) with large-scale computation☆11Updated 3 years ago
- A distance distribution-based visualization method for atomic pair energy and precise prediction of absolute binding free energy.☆13Updated 7 months ago
- ☆17Updated 2 years ago
- Augmenting a training dataset of the generative diffusion model for molecular docking with artificial binding pockets☆10Updated last month
- Code Space of SynLlama☆22Updated 3 months ago
- ☆12Updated last year
- ML-guided visual inspection for molecular docking☆20Updated 3 months ago
- ☆26Updated 2 years ago
- PackDock: a Diffusion Based Side Chain Packing Model for Flexible Protein-Ligand Docking☆34Updated 11 months ago
- Machine Learning Boosted Docking (HASTEN): Accelerate Structure-based Virtual Screening☆39Updated last year
- ☆27Updated last year
- This is the first model that can simultaneously predict the RMSD of the ligand docking pose and the binding strength against the target.☆19Updated 8 months ago
- Tool to predict water molecules placement and energy in ligand binding sites☆28Updated 3 weeks ago