Toxicity Structure Alert

Toxicity Structure Alert (Skill ID: 141)

Identify potential toxic structural alerts in drug molecules.

When to Use

Key Features

See ## Features above for related details.

Dependencies

Example Usage

See ## Usage above for related details.

cd "20260318/scientific-skills/Data Analytics/toxicity-structure-alert"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan: 1. Confirm the user input, output path, and any required config values. 2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings. 3. Run python scripts/main.py with the validated inputs. 4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py --input "Audit validation sample with explicit symptoms, history, assessment, and next-step plan." --format json

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work. 2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions. 3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available. 4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items. 5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Features

Supported Alert Structures

| Alert Structure | Toxicity Type | Risk Level | |---------|---------|---------| | Aromatic Nitro | Mutagenicity | High | | Aromatic Amine | Carcinogenicity | High | | Epoxide | Alkylating Agent | High | | Aldehyde | Reactive Toxicity | Medium | | Acyl Chloride | Reactive Toxicity | Medium | | Michael Acceptor | Electrophilic Toxicity | Medium | | Hydrazine | Hepatotoxicity | High | | Haloalkyl | Alkylating Agent | High | | Quinone | Oxidative Stress | Medium | | Thiol-Reactive Groups | Protein Binding | Low-Medium |

Usage

python -m py_compile scripts/main.py
Example invocation: python scripts/main.py --input  [--format json|text]

Parameters

Examples

Basic text output
python scripts/main.py -i "O=N+c1ccccc1"
JSON format output
python scripts/main.py -i "O=C1OC1c1ccccc1" -f json
Detailed report
python scripts/main.py -i "c1ccc2c(c1)ccc1c3ccccc3ccc21" -d full

Python API

from scripts.main import ToxicityAlertScanner
scanner = ToxicityAlertScanner()
result = scanner.scan("O=N+c1ccccc1")
print(result.alerts)

Output Format

JSON Output

{
  "input": "O=N+c1ccccc1",
  "mol_weight": 123.11,
  "alert_count": 1,
  "risk_score": 0.85,
  "risk_level": "HIGH",
  "alerts": 
    {
      "name": "Aromatic Nitro",
      "type": "mutagenic",
      "smarts": "[N+[O-]",
      "risk_level": "HIGH",
      "description": "May cause DNA damage and mutagenicity"
    }
  ],
  "recommendations": [
    "Recommend Ames test validation",
    "Consider structural optimization to reduce toxicity"
  ]
}

Risk Levels

Notes

1. This tool is based on known alert structures and cannot replace comprehensive toxicological assessment 2. False positives and false negatives may both exist 3. Recommended to use with other ADMET prediction tools

References

Risk Assessment

| Risk Indicator | Assessment | Level | |----------------|------------|-------| | Code Execution | Python/R scripts executed locally | Medium | | Network Access | No external API calls | Low | | File System Access | Read input files, write output files | Medium | | Instruction Tampering | Standard prompt guidelines | Low | | Data Exposure | Output files saved to workspace | Low |

Security Checklist

Prerequisites

Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

Test Cases

Lifecycle Status

Output Requirements

Every final response should make these items explicit when they are relevant:

Error Handling

Input Validation

This skill accepts requests that match the documented purpose of toxicity-structure-alert and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

> toxicity-structure-alert only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective 2. Inputs Received 3. Assumptions 4. Workflow 5. Deliverable 6. Risks and Limits 7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

Inputs to Collect

Output Contract

Validation and Safety Rules

Basic text output
python scripts/main.py -i "O=N+c1ccccc1"
JSON format output
python scripts/main.py -i "O=C1OC1c1ccccc1" -f json
Detailed report
python scripts/main.py -i "c1ccc2c(c1)ccc1c3ccccc3ccc21" -d full

Python API

from scripts.main import ToxicityAlertScanner
scanner = ToxicityAlertScanner()
result = scanner.scan("O=N+c1ccccc1")
print(result.alerts)

Python dependencies
pip install -r requirements.txt

1. This tool is based on known alert structures and cannot replace comprehensive toxicological assessment 2. False positives and false negatives may both exist 3. Recommended to use with other ADMET prediction tools