ADME Property Predictor

ADME Property Predictor

Overview

Comprehensive pharmacokinetic prediction tool that assesses drug-likeness and ADME properties of small molecules using validated cheminformatics models, molecular descriptors, and structure-property relationships.

Key Capabilities:

• Multi-Property Prediction: Absorption, Distribution, Metabolism, Excretion
• Drug-Likeness Scoring: Lipinski's Rule of 5, Veber rules, QED score
• Batch Processing: Analyze compound libraries efficiently
• Structure-Based Insights: Identify liability hotspots and optimization opportunities
• Comparative Analysis: Rank candidates by predicted PK profile

When to Use

✅ Use this skill when:

• Screening compound libraries for drug-like properties in early discovery
• Prioritizing lead compounds for advancement based on predicted PK
• Identifying ADME liabilities requiring structural optimization
• Comparing analogs to select candidates with optimal ADME profiles
• Filtering virtual screening hits before synthesis
• Generating ADME data for regulatory pre-submission packages
• Teaching pharmacokinetics and drug design principles

❌ Do NOT use when:

• Exact PK parameters needed for dosing → Use experimental PK studies
• Biologics (antibodies, proteins) → Use antibody-pk-predictor
• Natural products with complex structures → Models trained on synthetic small molecules
• Prodrugs requiring metabolic activation → Use prodrug-activation-predictor
• Prediction for clinical dosing decisions → CRITICAL: Experimental validation required
• Assessing toxicity or safety → Use toxicity-structure-alert or admetox-predictor

Related Skills:

• 上游: chemical-structure-converter (structure preparation), lipinski-rule-filter (rule-based filtering)
• 下游: drug-candidate-evaluator (integrated scoring), molecular-dynamics-sim (detailed binding)

Integration with Other Skills

Upstream Skills:

• chemical-structure-converter: Convert between SMILES, InChI, MOL formats