Computational Chemistry & Molecular Analysis
Structured molecular intelligence — drug-likeness assessment via Lipinski's Rule of Five, blood-brain barrier penetration prediction, binding affinity interpretation from IC50/Ki data, target overlap analysis, and synergy scoring using PubChem, ChEMBL, and Open Targets data.
Key Mechanisms
- Lipinski Rule of Five drug-likeness filtering
- LogP-based BBB penetration prediction
- IC50/Ki binding affinity contextualization
- Target overlap and polypharmacology analysis
- Synergy prediction from complementary target coverage
Notable Compounds
- Metformin (AMPK/mTOR)
- Rapamycin (mTOR)
- Curcumin (multi-target)
- Fenbendazole (tubulin)
- NMN (NAD+ precursor)
Disease-Specific Research
- Computational Chemistry & Molecular Analysis for ALS (Amyotrophic Lateral Sclerosis)
- Computational Chemistry & Molecular Analysis for Stage IV Cancer
- Computational Chemistry & Molecular Analysis for Alzheimer's Disease
- Computational Chemistry & Molecular Analysis for Parkinson's Disease
- Computational Chemistry & Molecular Analysis for Autoimmune Diseases