directmultistep 1.0.0rc1

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DirectMultiStep: Direct Route Generation for Multi-Step Retrosynthesis

Overview

The preprint for this work is posted on arXiv.

How to use

Here's a quick example to generate a retrosynthesis route (you can get relevant checkpoints by running bash download_files.sh).

from directmultistep.generate import generate_routes
from pathlib import Path

data_path = Path(__file__).resolve().parents[1] / "data"
ckpt_path = data_path / "checkpoints"
fig_path = data_path / "figures"
config_path = data_path / "configs" / "dms_dictionary.yaml"

# Generate a route for a target molecule
target = "CNCc1cc(-c2ccccc2F)n(S(=O)(=O)c2cccnc2)c1"
starting_material = "CN"

# Find routes with different models:
# Using flash model with starting material
paths = generate_routes(
    target, 
    n_steps=2, 
    starting_material=starting_material, 
    model="flash", beam_size=5,
    config_path=config_path, ckpt_dir=ckpt_path
)

# Or use explorer model to automatically determine steps
paths = generate_routes(
    target,
    starting_material=starting_material,
    model="explorer",
    beam_size=5,
    config_path=config_path, ckpt_dir=ckpt_path
)

See use-examples/generate-route.py to see more examples with other models. Other example scripts include:

• train-model.py: Train a new model with customizable configuration for local or cluster environments
• eval-subset.py: Evaluate a trained model on a subset of data
• paper-figures.py: Reproduce figures from the paper
• visualize-train-curves.py: Plot training curves and metrics

Licenses

All code is licensed under MIT License. The content of the pre-print on arXiv is licensed under CC-BY 4.0.