askcos
Retrosynthetic template relevance prediction using a locally deployed ASKCOS TorchServe service. Returns ranked precursor suggestions with confidence scores from 5 template sets (reaxys, pistachio, pistachio_ringbreaker, bkms_metabolic, reaxys_biocatalysis). Requires local deployment at http://localhost:9410.
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- lamm-mit/scienceclaw
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- March 14, 2026 at 06:18
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- askcos
- description
- Retrosynthetic template relevance prediction using a locally deployed ASKCOS TorchServe service. Returns ranked precursor suggestions with confidence scores from 5 template sets (reaxys, pistachio, pistachio_ringbreaker, bkms_metabolic, reaxys_biocatalysis). Requires local deployment at http://localhost:9410.
- license
- MIT License
- metadata
- {"skill-author":"K-Dense Inc."}
# ASKCOS - Retrosynthetic Template Relevance
## Overview
ASKCOS template_relevance predicts retrosynthetic disconnections using reaction template libraries.
The service runs locally as a TorchServe container (`retro_template_relevance`) and requires a
SMILES input, returning ranked precursor SMILES with template match scores.
Deployment: https://gitlab.com/mlpds_mit/askcosv2/retro/template_relevance
Docs: https://askcos-docs.mit.edu/guide/4-Deployment/4.2-Standalone-deployment-of-individual-modules.html
## Requirements
- Docker container `retro_template_relevance` running at `http://localhost:9410`
- Start/stop: `docker start retro_template_relevance` / `docker stop retro_template_relevance`
## Usage
### Basic Retrosynthesis (JSON output — default)
```bash
python3 skills/askcos/scripts/askcos_retro.py \
--smiles "CC(C)C1CCC(C)CC1O"
```
### Human-readable summary
```bash
python3 skills/askcos/scripts/askcos_retro.py \
--smiles "CC(C)C1CCC(C)CC1O" \
--model reaxys \
--top 10 \
--format summary
```
### Select template set
```bash
python3 skills/askcos/scripts/askcos_retro.py \
--smiles "CC(C)C1CCC(C)CC1O" \
--model pistachio
```
## Parameters
| Flag | Default | Description |
|------|---------|-------------|
| `--smiles` / `-s` | required | Target molecule SMILES |
| `--model` / `-m` | `reaxys` | Template set: `reaxys`, `pistachio`, `pistachio_ringbreaker`, `bkms_metabolic`, `reaxys_biocatalysis` |
| `--top` / `-n` | `10` | Number of top suggestions to return |
| `--base-url` | `http://localhost:9410` | TorchServe base URL |
| `--format` / `-f` | `json` | Output format: `json` or `summary` |
## Environment Variables
| Variable | Default | Description |
|----------|---------|-------------|
| `ASKCOS_BASE_URL` | `http://localhost:9410` | Override TorchServe URL |
| `ASKCOS_MODEL` | `reaxys` | Default template set |
## Output Format (JSON)
```json
{
"target": "CC(C)C1CCC(C)CC1O",
"model": "reaxys",
"total_templates_matched": 191,
"status": "success",
"suggestions": [
{
"rank": 1,
"reactants_smiles": "CC1CCC(C(C)C)C(=O)C1",
"score": 0.4562,
"template_smarts": "[C:1]-[CH;D3;+0:2](-[C:3])-[OH;D1;+0:4]>>[C:1]-[C;H0;D3;+0:2](-[C:3])=[O;H0;D1;+0:4]",
"template_id": "5e1f4b6e6348832850995dbf",
"template_count": 8688,
"necessary_reagent": ""
}
]
}
```
## Example Output (menthol)
```
ASKCOS (reaxys) — CC(C)C1CCC(C)CC1O
Templates matched: 191
# 1 score=0.4562 n= 8688 precursors: CC1CCC(C(C)C)C(=O)C1
# 2 score=0.0387 n= 20 precursors: CC1CCC2C(C1)OC(=O)C2C
# 3 score=0.0387 n= 20 precursors: CC(C)C1CCC2CC1OC2=O
# 4 score=0.0321 n= 245 precursors: CC1C=CC(C(C)C)CC1 reagent: [O]
# 5 score=0.0279 n=26868 precursors: CC(=O)OC1CC(C)CCC1C(C)C
```
Top hit (menthone → menthol via reduction) correctly recovers the industrial Takasago process.
## Integration with Other Skills
```bash
# Get SMILES from RDKit, then run retrosynthesis
SMILES="CC(C)C1CCC(C)CC1O"
# Retrosynthesis
python3 skills/askcos/scripts/askcos_retro.py --smiles "$SMILES" --top 5 --format json
# Analyse top precursor with RDKit
PRECURSOR="CC1CCC(C(C)C)C(=O)C1"
python3 skills/rdkit/scripts/molecular_properties.py --smiles "$PRECURSOR"
```
## References
- ASKCOS: Coley et al., Science 2019. DOI: 10.1126/science.aax1566
- Template relevance: Coley et al., ACS Central Science 2017. DOI: 10.1021/acscentsci.7b00355
- GitLab: https://gitlab.com/mlpds_mit/askcosv2/retro/template_relevance
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