HEDGEHOG

HEDGEHOG: Hierarchical Evaluation of Drug GEnerators tHrOugh riGorous filtration.

PyPI Docs CI License: MIT Python 3.10+

HEDGEHOG Terminal UI

Quick Start

HEDGEHOG is a stage-based molecular design evaluation pipeline for:

  • molecule preparation
  • descriptor calculation
  • structural filtering
  • retrosynthesis filtering
  • docking
  • docking pose filtering
  • final reports

The full pipeline can require optional external tools and receptor inputs. Start with the safe smoke run below to verify the Python environment, bundled example molecules, descriptor calculation, and structural filters before enabling retrosynthesis or docking.

Public documentation

Recommended install: source checkout

git clone https://github.com/LigandPro/hedgehog.git
cd hedgehog
uv sync

This is the recommended way to run HEDGEHOG end to end. The repository checkout contains the editable configs, bundled examples, TUI sources, and the modules/ workspace used to store optional tool assets such as AiZynthFinder public data.

Requirements:

  • Python 3.10+
  • uv
  • optional: Node.js >= 18 and npm for the TUI
  • optional: AiZynthFinder for retrosynthesis
  • optional: GNINA, SMINA, or Matcha for docking

PyPI install

python -m pip install hedgehog
hedgehog --help

Use the PyPI package only if you already manage your own config files and input paths. The default quick start, hedgehog setup ... workflows, and TUI usage are designed around a source checkout.

First safe run

uv run hedgehog --stage descriptors --stage struct_filters --force-new

This avoids docking and retrosynthesis. Use it as the first validation that the local environment, bundled examples, descriptor calculation, and structural filters are working.

Full pipeline

uv run hedgehog setup aizynthfinder
uv run hedgehog --auto-install

Full pipeline execution may require AiZynthFinder, GNINA/SMINA/Matcha, valid receptor structures, reference ligands, and enough CPU/GPU resources.

Input Format

Recommended molecule input is CSV/TSV with a smiles header:

smiles,model_name
CCO,demo
CCN,demo
c1ccccc1,demo

Required:

  • smiles

Optional:

  • model_name or name
  • mol_idx

If mol_idx is missing, HEDGEHOG assigns a stable ID and uses it to join stage outputs, docking scores, and report data.

Common Commands

# Safe smoke run
uv run hedgehog --stage descriptors --stage struct_filters --force-new

# Full pipeline after optional tools are available
uv run hedgehog --auto-install

# Run with your own molecules
uv run hedgehog --mols input/my_molecules.csv

# Run a single stage
uv run hedgehog --stage descriptors

# Run multiple selected stages
uv run hedgehog --stage descriptors --stage struct_filters

# Run docking with a live progress bar
uv run hedgehog --stage docking --progress

# Run docking without progress bar (default)
uv run hedgehog --stage docking

# Regenerate report for an existing run
uv run hedgehog report results/run_10

# Show stages / version
uv run hedgehog info
uv run hedgehog version

# Launch terminal UI
uv run hedgehog tui

Progress bar behavior in CLI runs:

  • Enabled: add --progress
  • Disabled: omit --progress (default)

Results

Results are written under the configured output directory, usually as an auto-numbered run folder:

results/run_N/
├── stages/
├── output/
└── report.html

Benchmark Results

Filtering pass rates by model class

Percentages are computed relative to the initial set for each model class. Unconditional and protein-based models each start from 8,000 molecules, and ligand-based models start from 6,000 molecules.

Stage / Pass Rate Unconditional Ligand-based Protein-based
#mols% #mols% #mols%
Initial 8,000100 6,000100 8,000100
Preprocessing / Init 60,40775.51 68,85898.37 77,39696.75
Descriptors / Init 19,94124.93 19,97828.54 19,41224.27
Structural Filters / Init 4,6525.82 4,1325.90 2,8963.62
Synthesis Feasibility / Init 2,7783.47 1,4832.12 1,3161.65
Docking & Binding Aff. / Init 1,4411.80 1,0841.55 7680.96
3D Filters / Init 6090.76 3960.57 4850.61

Top generators by final pass count

Best-performing generators within each model class, ranked by the number of molecules that pass the full HEDGEHOG pipeline.

Documentation

HEDGEHOG Pipeline

For full details, use the documentation instead of this README:

To run the docs site locally:

cd docs
pnpm install
pnpm dev

License

MIT

RankUnconditionalLigand-basedProtein-based
GeneratorFinal GeneratorFinal GeneratorFinal
1 REINVENT4102.0 ± 5.0 REINVENT4 (P) 61.3 ± 11.9 Dragonfly127.0 ± 18.1
2 MoLeR92.7 ± 9.7 PGMG24.3 ± 2.3 DrugFlow58.0 ± 8.5
3 HierGraphVAE91.7 ± 9.5 MolFinder (TL)12.0 ± 0.0 Pocket2Mol31.0 ± 11.5
4 JT-VAE74.7 ± 12.0 GCPG3.3 ± 1.5 Dragonfly (b)9.7 ± 3.1
5 MolGPT73.0 ± 6.6 GENTRL3.3 ± 1.5 ProtoBind-Diff6.0 ± 2.6
6 ShEPhERD4.0 ± 1.0 REINVENT4 (TL)0.0 ± 0.0 DiffSBDD0.7 ± 1.2
7 TGM-DLM3.0 ± 0.0 —— TargetDiff0.3 ± 0.6
8 EDM0.3 ± 0.6 — — ResGen0.0 ± 0.0

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.1.45)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for fader.refits2r from gravatar.com fader.refits2r

Requires

Python >=3.10

Provides Extra

docking-gpu lint retrosynthesis shepherd sync test

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

hedgehog-1.1.43.tar.gz (11.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

hedgehog-1.1.43-py3-none-any.whl (11.9 MB view details)

Uploaded Python 3

File details

Details for the file hedgehog-1.1.43.tar.gz.

File metadata

  • Download URL: hedgehog-1.1.43.tar.gz
  • Upload date:
  • Size: 11.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for hedgehog-1.1.43.tar.gz
Algorithm Hash digest
SHA256 a04b5bc4f3827fb3f60b6d54a30523d8e3574b8de504c656ea3759d48a51522a
MD5 6254e07844125d20ae79bef2aa156023
BLAKE2b-256 4863cbd8f06271be8fb31abffa3c2e6a8c49cb724d065b32ecb4938c2ce780fb

See more details on using hashes here.

File details

Details for the file hedgehog-1.1.43-py3-none-any.whl.

File metadata

  • Download URL: hedgehog-1.1.43-py3-none-any.whl
  • Upload date:
  • Size: 11.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for hedgehog-1.1.43-py3-none-any.whl
Algorithm Hash digest
SHA256 783393712c5d63d740087a25dd4a1bc97c20b1b3d6a0401986ffba6ec19e7ce1
MD5 ef7bb8107e0c54b92d618a449d8c7594
BLAKE2b-256 215566103da1c6425890e7c8e000a57008c7d8bd6ea8668afd7c7bf9964a4783

See more details on using hashes here.

Release history Release notifications | RSS feed

1.1.45

2 files

1.1.44

2 files

This release

1.1.43 This release

2 files

1.1.42

2 files

1.1.41

2 files

1.1.40

2 files

1.1.39

2 files

1.1.38

2 files

1.1.37

2 files

1.1.36

2 files

1.1.35

2 files

1.1.34

2 files

1.1.33

2 files

1.1.32

2 files

1.1.31

2 files

1.1.30

2 files

1.1.29

2 files

1.1.28

2 files

1.1.27

2 files

1.1.26

2 files

1.1.25

2 files

1.1.24

2 files

1.1.23

2 files

1.1.19

2 files

1.1.18

2 files

1.1.17

2 files

1.1.16

2 files

1.1.15

2 files

1.1.14

2 files

1.1.13

2 files

1.1.12

2 files

1.1.11

2 files

1.1.10

2 files

1.1.9

2 files

1.1.8

2 files

1.1.7

2 files

1.1.6

2 files

1.1.5

2 files

1.1.4

2 files

1.1.3

2 files

1.1.2

2 files

1.1.1

2 files

1.0.46

2 files

1.0.45

2 files

1.0.44

2 files

1.0.43

2 files

1.0.42

2 files

1.0.41

2 files

1.0.40

2 files

1.0.39

2 files

1.0.38

2 files

1.0.37

2 files

1.0.36

2 files

1.0.35

2 files

1.0.34

2 files

1.0.33

2 files

1.0.32

2 files

1.0.31

2 files

1.0.30

2 files

1.0.29

2 files

1.0.28

2 files

1.0.27

2 files

1.0.26

2 files

1.0.25

2 files

1.0.24

2 files

1.0.23

2 files

1.0.22

2 files

1.0.21

2 files

1.0.20

2 files

1.0.19

2 files

1.0.18

2 files

1.0.17

2 files

1.0.16

2 files

1.0.15

2 files

1.0.14

2 files

1.0.13

2 files

1.0.12

2 files

1.0.11

2 files

1.0.10

2 files

1.0.9

2 files

1.0.8

2 files

1.0.7

2 files

1.0.6

2 files

1.0.5

2 files

1.0.4

2 files

1.0.3

2 files

1.0.2

2 files

1.0.1

2 files

1.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page