Synkit

SynKit

Graph-based Python toolkit for reaction informatics: ITS graph construction, canonicalization, AAM validation, DPO rule extraction, CRN analysis, and synthesis planning.

Paper: doi:10.1021/acs.jcim.5c02123 | JCIM 2025

When to Use This Skill

• Converting reaction SMILES → ITS graphs (NetworkX) → DPO rules (GML)
• Validating or comparing atom-to-atom mappings (AAMValidator)
• Canonicalizing reaction SMILES (CanonRSMI) or ITS graphs (GraphCanonicaliser)
• Clustering reactions by structural similarity (WL graph hash)
• Extracting and composing reaction rules (DPO formalism)
• Analyzing chemical reaction networks (Feinberg deficiency theory, Petri nets)
• Detecting autocatalysis, siphons, traps in reaction networks
• Planning synthetic routes via rule composition (SynReactor)
• Building reaction databases or curating USPTO/ChEMBL reaction data

Core Concept: ITS Graph

The Imaginary Transition State (ITS) graph merges reactant and product graphs into a single labeled multigraph:

• Nodes: atoms with attributes (symbol, charge, radical, hybridization, H count)
• Edges: bonds with attributes (bond type, change flag: formed / broken / unchanged)

ITS ≡ CGR (Condensed Graph of Reaction) — same structure, different naming tradition.

Quick Start

from synkit.IO import load_reaction_smiles
from synkit.Graph import ITSConstruction
from synkit.Chem import CanonRSMI, AAMValidator

# 1. Parse reaction SMILES → ITS graph (NetworkX)
rxn_smiles = "[CH3:1][OH:2].[Na:3][H:4]>>[CH3:1][O:2][Na:3].[H:4][H:5]"
its = ITSConstruction.from_reaction_smiles(rxn_smiles)

# 2. Canonicalize the reaction SMILES
canon = CanonRSMI(rxn_smiles).canonicalize()

# 3. Validate atom-atom mapping
valid = AAMValidator(rxn_smiles).is_valid()

Router — What to Read

Key Submodules

Conversion Pipeline

Reaction SMILES (atom-mapped)
    │
    ▼ IO / Graph.ITSConstruction
ITS Graph (NetworkX)         ← cluster, hash, validate
    │
    ▼ Graph.GraphCanonicaliser
Canonical ITS Graph          ← canonical form independent of atom ordering
    │
    ▼ Rule module
DPO Rule (GML format)        ← compose, apply, store

All conversions are lossless for balanced, atom-mapped reactions. Caveats: stereochemistry is omitted; explicit H at reaction centers required for GML → SMILES reversion.

Installation

pip install synkit          # core (RDKit + NetworkX)
pip install synkit[all]     # full (+ transformers for RXNMapper)
# Python ≥ 3.11 required

Related Skills

• rdkit — molecule preprocessing before SynKit ingestion
• torchdrug — retrosynthesis with GNNs (complementary ML approach)
• deepchem — molecular ML when rule-based approach insufficient