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Helmkit: fast and robust conversion of HELM notation to atomistic representations for large-scale macromolecular
Ramon Adàlia1,2, Gemma Sanjuan3, Tomàs Margalef3
1Computer Architecture and Operating Systems, Universitat Autònoma de Barcelona, Carrer de les Sitges, 08193, Cerdanyola del Vallès, Barcelona, Spain. Ramon.Adalia@autonoma.cat.
Journal of Cheminformatics
|May 29, 2026
Summary
We developed helmkit, a Python library for fast and accurate conversion of Hierarchical Editing Language for Macromolecules (HELM) strings to molecular models. This tool supports diverse biomolecules and enhances computational drug discovery workflows.
Area of Science:
- Computational chemistry
- Cheminformatics
- Biomolecular modeling
Background:
- The Hierarchical Editing Language for Macromolecules (HELM) is crucial for representing complex biomolecules.
- Existing HELM-to-atomistic model conversion tools face limitations in speed, scope, and robustness.
- Efficient processing of HELM notations is vital for large-scale computational studies.
Purpose of the Study:
- To introduce helmkit, an open-source Python library for high-throughput conversion of HELM strings to RDKit molecular objects.
- To provide a robust and efficient solution for analyzing diverse macromolecular structures.
- To overcome the limitations of existing tools in speed, scope, and accuracy.
Main Methods:
- Developed helmkit, a Python library with minimal dependencies and built-in parallelization.
- Implemented support for peptides, nucleic acids, chemical linkers, and hybrid molecules.
- Enabled native handling of inline monomers, special characters, and automatic inference of missing attachment points.
Main Results:
- Achieved processing speeds of up to 5,000 HELM entities per second.
- Demonstrated near-perfect accuracy on large datasets (PubChem, CycPeptMPDB), successfully parsing challenging structures.
- Validated helmkit's robustness against real-world HELM variants, including error correction and R-group inference.
Conclusions:
- helmkit offers a fast, accurate, and scalable solution for converting HELM notations to atomistic models.
- The library significantly advances computational workflows in drug discovery, virtual screening, and biomolecular engineering.
- helmkit addresses a practical limitation in cheminformatics, facilitating efficient analysis of complex biomolecules.
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