Reaction Enumeration

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha c8c1fc3a2b13 · 19 Oct 2026Report an issue or request a re-scan

• PublisherGPTomics GitHub organizationOwner of the repository this skill is read from
• Source folderGPTomics/bioSkills/chemoinformatics/reaction-enumerationThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdictc8c1fc3a2b13A new audit runs when the source changes
• Repository statusArchivedLast push 65 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product validation, RECAP/BRICS…

---
name: bio-reaction-enumeration
description: Enumerates virtual chemical libraries via reaction SMARTS transformations using RDKit and reaction templates, with explicit handling of atom mapping, RDChiral template extraction, product validation, RECAP/BRICS fragmentation, R-group decomposition, matched molecular pair analysis (MMPA), and Free-Wilson analysis. Use when generating combinatorial libraries from building blocks, enumerating analog series, deriving structure-activity rules, or extracting transformations from reaction data.
tool_type: python
primary_tool: RDKit
---

## Version Compatibility

Reference examples tested with: RDKit 2024.09+, RDChiral 1.1+, mmpdb 3.1+, scikit-learn 1.4+, numpy 1.26+.

Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed
package and adapt the example to match the actual API rather than retrying.

# Reaction Enumeration

Generate virtual libraries by applying reaction SMARTS to building blocks, enumerate analog series via matched molecular pairs, decompose into R-groups for SAR modeling, or extract transformations from reaction data. Reaction enumeration sits at the intersection of medicinal chemistry, lead optimization, and de novo design; DOGS is one published example of reaction-driven de novo design (Hartenfeller et al. 2012). The two key operations are **transform** (apply known reactions to make new compounds) and **mine** (extract rules from observed analog series). RDKit's reaction SMARTS handles the former; mmpdb / Free-Wilson handle analog-series analysis, while mapped-reaction template extraction requires separate tooling such as RDChiral.

For retrosynthetic planning (target-to-starting-material decomposition), see `chemoinformatics/retrosynthesis`. For ML-driven design, see `chemoinformatics/generative-design`. For scaffold-based design, see `chemoinformatics/scaffold-analysis`.

## Operation Taxonomy

| Operation | Goal | Tool | Fails when |
|-----------|------|------|------------|
| Forward enumeration | Apply reaction to building blocks -> products | RDKit `ReactionFromSmarts` + `RunReactants` | Wrong atom mapping; missing connectivity |
| Reverse enumeration (retrosynthesis) | Product -> starting materials | AiZynthFinder, Chemformer | See retrosynthesis skill |
| Template mining | Reaction database -> reaction SMARTS templates | RXNMapper + RDChiral | Atom mapping ambiguous; mechanism unclear |
| RECAP fragmentation | Molecule -> retro-synthetic fragments | RDKit `Chem.Recap` | Inflexible bond rules |
| BRICS fragmentation | Molecule -> retro-synthetic fragments | RDKit `BRICS` module | Many false fragments |
| R-group decomposition | Set of mols + scaffold -> R-group table | RDKit `Chem.rdRGroupDecomposition` | Multiple scaffolds; ambiguous attachment |
| Matched Molecular Pairs (MMPA) | Set of mols -> transformation rules | mmpdb | Sparse or context-confounded matched pairs |
| Free-Wilson | Compounds + activities -> additive R-group contributions | scikit-learn linear regression | Strict additivity assumption |

## Reaction SMARTS Basics

A reaction SMARTS is `reactants >> products` with atom maps `[atom:idx]` tracking atoms through the transformation:

```python
from rdkit import Chem
from rdkit.Chem import AllChem

amide = AllChem.ReactionFromSmarts(
    '[C:1](=[O:2])O.[N:3]>>[C:1](=[O:2])[N:3]'
)

errors = amide.Validate()
print(errors)
```

**Atom mapping rules:**
- Atoms with the same map index `[C:1]` in both reactant and product are tracked
- Maps must be unique within each reactant/product
- Atoms present in a reactant template but absent from the product template are removed; atoms present only in the product template are created
- Atoms outside the matched reaction-center template are generally carried through with their reactant molecule
- Bond orders may change; map index preserves identity

**Common error:** Missing or inconsistent maps for atoms intended to survive within the reaction center can delete atoms, create duplicates, or obscure which reactant atom a product atom represents. Mapping alone does not define the transformation; the reactant and product templates do.

## Common Reaction Templates

```python
REACTIONS = {
    'amide_coupling': '[C:1](=[O:2])O.[N:3]>>[C:1](=[O:2])[N:3]',
    'reductive_amination': '[C:1](=O).[NH2:2]>>[CH:1][NH:2]',
    'suzuki': '[c:1][Br].[c:2][B](O)O>>[c:1][c:2]',
    'buchwald_hartwig': '[c:1][Br].[NH:2]>>[c:1][N:2]',
    'sn2_substitution': '[CH:1][Br].[N:2]>>[CH:1][N:2]',
    'sonogashira': '[c:1][Br].[CH:2]#[C:3]>>[c:1][C:2]#[C:3]',
    'click_chemistry': '[N-:1]=[N+:2]=[N:3][CH2:4].[CH:5]#[C:6]>>[N:3]1[N:2]=[N:1][C:6]=[C:5]1[CH2:4]',
    'esterification': '[C:1](=[O:2])O.[OH:3][C:4]>>[C:1](=[O:2])[O:3][C:4]',
    'urea_formation': '[N:1]=C=O.[NH:2]>>[N:1]C(=O)[N:2]',
    'sulfonamide': '[S:1](=O)(=O)Cl.[NH:2]>>[S:1](=O)(=O)[N:2]',
}
```

These are illustrative templates; real reactions need stereo, protecting-group, and chemoselectivity considerations. For production library enumeration, use a separately curated and validated template collection, such as a vendor catalog. RXNMapper maps atoms in reaction records; it does not by itself supply or validate reaction templates.

## Combinatorial Library Enumeration

**Goal:** Generate every (R1, R2, ..., Rn) product combination from sets of building blocks.

**Approach:** Cartesian product of reactant lists; apply reaction SMARTS; sanitize + deduplicate.

```python
from itertools import product
from rdkit import Chem
from rdkit.Chem import AllChem, Descriptors

def enumerate_library(rxn_smarts, reactant_lists, mw_max=600):
    rxn = AllChem.ReactionFromSmarts(rxn_smarts)
    num_warnings, num_errors = rxn.Validate()
    if num_errors:
        raise ValueError(f'Invalid reaction: {rxn_smarts}')

    seen = set()
    products = []
    for

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

pip install rdkit

git clone https://github.com/GPTomics/bioSkills
git -C bioSkills checkout c8c1fc3a2b13

Works in

1. 2026-10-19
   ✓SAFE B 89 / 100

   first audit · source c8c1fc3a2b13

Questions about Reaction Enumeration

• github.com/GPTomics/bioSkills/tree/main/chemoinformatics/reactio — the audited source at commit c8c1fc3a2b13 and every finding aboveObserved · 19 Oct 2026

Spotted something wrong? Report a correction · Methodology