Reaction Center Identification

A core computational method involves calculating the difference in bond orders between products and reactants for every mapped atom pair. Bonds that change order (e.g., from single to double) or are created/destroyed are flagged as part of the reaction center. This approach treats the reaction as a graph edit distance problem, where the minimal set of edge and node modifications defines the transformation core.

Definitions vary between a core reaction center and an extended reaction center:

• Core: Only atoms directly changing connectivity or bond order.
• Extended: Includes atoms within one bond distance of the core, capturing neighboring group effects. Template extraction algorithms often use the extended definition to ensure extracted reaction rules retain sufficient chemical context for valid retrosynthetic application.

In semi-template retrosynthesis, reaction center identification serves as the critical first stage. A graph neural network first predicts which bond in the target molecule is most likely to be the reaction center. Once identified, a template-free generative module completes the synthon by adding appropriate leaving groups or fragments. This decoupling allows the model to leverage template-based precision for site selection while maintaining generative flexibility for synthon completion.

Modern identification models use message-passing neural networks (MPNNs) operating on molecular graphs. Each atom node receives a learned embedding, and edges representing bonds are scored for their likelihood of being part of the reaction center. Directed MPNNs propagate information along bond directions to distinguish between bond formation and cleavage, enabling the model to predict not just where but how the connectivity changes.

The quality of reaction center identification is often validated through round-trip accuracy. The identified center is used to generate synthons, which are then fed into a forward reaction predictor. If the forward model reconstructs the original product, the identified center is considered chemically valid. This metric ensures that the identified atoms and bonds are not just statistically likely but mechanistically consistent with known reactivity.

The foundational preprocessing step that establishes a one-to-one correspondence between atoms in reactants and products. Accurate atom mapping is a prerequisite for reaction center identification, as it explicitly tracks which atoms undergo bond changes.

• Enables extraction of the reaction center by comparing mapped graphs
• Critical for creating high-quality training data from reaction databases
• Manual curation remains the gold standard for benchmark datasets

A strategy that applies a pre-defined library of reaction rules to predict disconnections. Each rule encodes a specific reaction center pattern and its corresponding precursor substructures.

• Reaction centers are the keys used to index the template library
• Subgraph isomorphism algorithms match target substructures to template reaction centers
• Limited by template coverage; cannot predict novel reaction types outside the rule set

A fixed-length vector representation encoding the structural transformation occurring at the reaction center. These fingerprints capture the difference between reactant and product atom environments.

• Used for reaction classification and similarity searching
• Enables clustering of reactions by transformation type
• Common implementations include DRFP (differential reaction fingerprint) and rxnfp based on BERT encoders

A hybrid approach that first identifies a reaction center using a template-based method, then completes the synthon generation using a template-free generative model.

• Decouples the two sub-problems: where to cut and what to add
• Leverages the precision of templates for center identification
• Uses generative models to propose leaving groups and complete synthons

The computational step that converts a disconnected bond into valid, synthetically equivalent molecular fragments with appropriate leaving groups. This step immediately follows reaction center identification.

• Transforms identified bond disconnections into chemically valid precursor molecules
• Requires knowledge of functional group interconversions and protecting group logic
• Often implemented as a sequence-to-sequence translation task using SMILES

A validation metric that measures the consistency of a retrosynthesis model. After predicting precursors, a forward reaction model predicts the product; if it matches the original target, the round-trip succeeds.

• Indirectly validates that the reaction center was correctly identified and reversed
• A high round-trip score indicates both retrosynthetic and forward models are well-calibrated
• Penalizes chemically implausible disconnections that cannot be recombined