retrosynthesis-guide

# Retrosynthesis Guide Plan synthetic routes for target molecules using retrosynthetic analysis principles and computational tools, from Corey's logic to modern AI-driven approaches. ## What Is Retrosynthesis? Retrosynthesis works backward from a target molecule to identify simpler, commercially available precursors: ``` Target Molecule (TM) | [Disconnection 1] ← Apply transform (reverse of a known reaction) | Synthon A + Synthon B | | [Available] [Disconnection 2] | Synthon C + Synthon D | | [Available] [Available] ``` Key terminology: - **Target Molecule (TM)**: The molecule you want to synthesize - **Synthon**: Idealized reactive fragment from a disconnection - **Synthetic Equivalent**: Real reagent corresponding to a synthon - **Transform**: Reverse of a chemical reaction (retro-reaction) - **FGI (Functional Group Interconversion)**: Convert one functional group to another to enable a disconnection ## Corey's Retrosynthetic Strategies ### Strategic Bond Disconnections | Strategy | Description | When to Use | |----------|-------------|------------| | **FGI** | Convert functional groups to enable disconnections | When direct disconnection is not possible | | **C-C Bond disconnection** | Break carbon-carbon bonds | Building the carbon skeleton | | **C-X Bond disconnection** | Break carbon-heteroatom bonds | Functional group installation | | **Ring disconnection** | Open rings to identify acyclic precursors | Cyclic target molecules | | **Symmetry exploitation** | Use molecular symmetry to simplify analysis | Symmetric molecules | | **Convergent synthesis** | Combine two complex fragments late | Minimize linear step count | ### Common Disconnection Patterns ``` # Alcohol (C-OH) → Carbonyl reduction R-CH(OH)-R' ⟹ R-CO-R' + NaBH4/LiAlH4 # Amine (C-N) → Reductive amination R-CH2-NH-R' ⟹ R-CHO + R'-NH2 # C-C Bond (aldol) → Aldol retro R-CH(OH)-CH2-CO-R' ⟹ R-CHO + CH3-CO-R' # C-C Bond (Grignard) → Grignard retro R-CH(OH)-R' ⟹ R-CHO + R'-MgBr # Ester (C-O) → Fischer esterification retro R-COO-R' ⟹ R-COOH + R'-OH # Amide (C-N) → Amide coupling retro R-CO-NH-R' ⟹ R-COOH + R'-NH2 # Diels-Alder → Retro Diels-Alder Cyclohexene derivative ⟹ Diene + Dienophile # Wittig → Retro Wittig R-CH=CH-R' ⟹ R-CHO + R'-CH2-PPh3 ``` ## Computational Retrosynthesis Tools ### Tool Comparison | Tool | Developer | Method | Access | |------|-----------|--------|--------| | ASKCOS | MIT | Template-based + neural | Free (askcos.mit.edu) | | IBM RXN | IBM Research | Transformer seq2seq | Free (rxn.res.ibm.com) | | Reaxys | Elsevier | Database-backed | Subscription | | SciFinder-n | CAS | Database + AI | Subscription | | Spaya | Iktos | Graph neural network | Commercial | | AiZynthFinder | AstraZeneca | Monte Carlo tree search | Open source | ### Using ASKCOS ```python import requests # ASKCOS API for retrosynthetic planning # (requires running ASKCOS locally or using the hosted version) target_smiles = "CC(=O)Oc1ccccc1C(=O)O" # Aspirin # One-step retrosynthesis response = requests.post( "https://askcos.mit.edu/api/retro/", json={ "smiles": target_smiles, "num_results": 10, "max_depth": 5 } ) results = response.json() for i, result in enumerate(results.get("precursors", [])[:5]): print(f"Route {i+1}:") print(f" Precursors: {result['smiles']}") print(f" Template: {result.get('template', 'N/A')}") print(f" Score: {result.get('score', 'N/A')}") ``` ### Using IBM RXN for Chemistry ```python # IBM RXN API from rxn4chemistry import RXN4ChemistryWrapper api_key = os.environ["RXN4CHEM_API_KEY"] rxn = RXN4ChemistryWrapper(api_key=api_key) rxn.create_project("retrosynthesis_example") # Predict retrosynthesis response = rxn.predict_automatic_retrosynthesis( product="CC(=O)Oc1ccccc1C(=O)O", # Aspirin max_steps=3 ) # Get results results = rxn.get_predict_automatic_retrosynthesis_results(response["prediction_id"]) for route in results.get("retrosynthetic_paths", []): print(f"Route confidence: {route.get('confidence', 'N/A')}") for step in route.get("steps", []): print(f" Reaction: {step.get('reaction_smiles', 'N/A')}") ``` ### Using AiZynthFinder (Open Source) ```python from aizynthfinder.aizynthfinder import AiZynthFinder # Configure the finder finder = AiZynthFinder() finder.stock.load("zinc_stock.hdf5") # Commercial building blocks finder.expansion_policy.load("expansion_policy_model.onnx") # Retro model # Set target finder.target_smiles = "CC(=O)Oc1ccccc1C(=O)O" # Aspirin # Run tree search finder.config.search.time_limit = 120 # seconds finder.config.search.iteration_limit = 500 finder.tree_search() # Extract and analyze routes finder.build_routes() for i, route in enumerate(finder.routes): print(f"Route {i+1} (score: {route.score:.3f}):") print(f" Steps: {len(route.reactions)}") for rxn in route.reactions: print(f" {rxn}") ``` ## SMILES Notation for Chemistry SMILES (Simplified Molecular Input Line Entry System) is the standard text representation: ``` # Common SMILES patterns Water: O Ethanol: CCO Benzene: c1ccccc1 Aspirin: CC(=O)Oc1ccccc1C(=O)O Caffeine: Cn1c(=O)c2c(ncn2C)n(C)c1=O Ibuprofen: CC(C)Cc1ccc(cc1)C(C)C(=O)O # SMILES rules # Atoms: C, N, O, S, P, F, Cl, Br, I # Bonds: - (single, implicit), = (double), # (triple) # Branches: () for branching # Rings: numbers for ring closure (c1ccccc1 = benzene) # Aromatic: lowercase letters # Stereochemistry: / \ for E/Z, @ @@ for R/S ``` ## Reaction Databases | Database | Coverage | Features | Access | |----------|----------|----------|--------| | Reaxys | 130M+ reactions | Experimental conditions, yields | Subscription | | SciFinder / CAS | 160M+ reactions | Commercial availability, safety data | Subscription | | USPTO | 3.7M reactions | US patent reactions | Free (open data) | | Open Reaction Database (ORD) | Growing | Structured reaction data, conditions | Free | | RMG (Reaction Mechanism Generator) | Kinetics | Automated mechanism generation | Free (MIT) | ## Best Practices for Route Planning 1. **Start simple**: Begin with the most obvious disconnections before trying exotic transforms. 2. **Consider availability**: Check if precursors are commercially available (Sigma-Aldrich, TCI, Alfa Aesar). 3. **Minimize steps**: Convergent synthesis (combining two complex halves) is generally preferred over linear synthesis. 4. **Protect and deprotect wisely**: Minimize protecting group manipulations; each adds 2 steps (protection + deprotection). 5. **Check literature**: Search Reaxys or SciFinder for precedent before attempting novel transformations. 6. **Validate computationally**: Use forward reaction prediction to verify that proposed retrosynthetic steps are feasible. 7. **Consider scale**: Reactions that work at milligram scale may fail at gram scale. Check for scalability issues (exothermic reactions, heterogeneous mixing).