Prepare release v.0.0.12

Changelog v0.0.12

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Highlights

New Features & Enhancements

AAM Inference

• Introduced AAM inference capabilities, allowing the generation of reaction SMILES with Atom-Atom Mapping (AAM) using rule-based transformations.
• AAM generation is now integrated with rule transformation to predict and apply atom mappings for reaction steps.

PartialAAM Expansion

• Enhanced PartialAAM expansion by refining the process of expanding partial Atom-Atom Mapped (AAM) reaction SMILES into full AAM RSMI (Reaction SMILES).
• Improved expansion algorithm efficiency and accuracy, with additional normalization to handle redundant hydrogen mappings, ensuring that mappings are retained only for hydrogens in the reaction center.

AAM Validator

• Added AAMValidator to verify the equivalence of AAMs between reaction steps.
• This tool compares atom mappings across multiple reaction steps, ensuring that the mappings remain consistent and accurate throughout the transformation process.

SynVis Enhancement

• Bug Fix: Fixed visualization issues in SynVis, ensuring correct coloring of bonds in ITS graphs.
  • Green now represents new bonds being formed.
  • Red indicates bonds that have been broken during the reaction.

Chemical Conversion Framework

• Introduced the chemical_conversion function to support format conversion between different chemical representations.
  • Now capable of converting between formats such as SMARTS, GML, and others, allowing users to seamlessly transform chemical data between multiple formats.

Multi-Step Reaction Framework (Prototype)

• Developed a prototype for a multi-step reaction framework that allows users to input an original reaction along with a list of reaction rules and their application order.
  • The framework generates the entire reaction sequence, step by step, with atom-atom mapping applied at each stage.

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Known Limitations

Time Processing for DG Transformation

• Current Bug: Time processing issues observed when transforming DG (Direct Graph) to SMILES with AAM.
  • The transformation process can experience delays, particularly when handling complex reactions with extensive atom mappings.

MØD and RDKit Compatibility Issues (Ongoing)

• Problem: Compatibility issues persist between MØD (conda version) and RDKit, resulting in Boost.Python.ArgumentError during RDKit operations.
• Workaround:
  • Add a workaround (using torch 2.0.1) before initializing MØD to mitigate compatibility issues.
  • For pytest, use a fixed test order to avoid conflicts during testing workflows.

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