PLACER

github.com/baker-laboratory/placer
Idle267updated 11 months ago
Python
NOASSERTION

Graph neural network operating entirely at the atomic level for protein-ligand conformational ensemble prediction and docking, generating diverse solutions through rapid stochastic denoising to model conformational heterogeneity (Baker Lab, bioRxiv 2025)

Sourced from

  • Awesome AI for Science — github.com/baker-laboratory/placer
  • GitHub — github.com/baker-laboratory/placer

Related resources

Diffusion-based molecular docking achieving SOTA blind docking performance, treating ligand pose prediction as generative diffusion over SE(3), with DiffDock-L update for improved generalization (MIT CSAIL, ICLR 2023)

Idle1.6K1 year ago
Python
MIT

RxDock is a fast and versatile open-source docking program that can be used to dock small molecules against proteins and nucleic acids. It is designed for high-throughput virtual screening (HTVS) campaigns and binding mode prediction studies.

Stale754 years ago
AWK
Other

Protein structure prediction

Active14.9K5 months ago
Python
Apache-2.0

AlphaFold 3 inference pipeline for unified biomolecular structure prediction of proteins, nucleic acids, small molecules, ions, and post-translational modifications (Google DeepMind, Nature 2024)

Active8.5K1 month ago
Python
Apache-2.0

Deep learning library for Chemistry based on Tensorflow

Active7K1 month ago
Python
MIT

First fully open-source model achieving AlphaFold3-level accuracy with 1000x faster binding affinity prediction (MIT)

Active4.2K4 months ago
Python
MIT