LCMD[db]: The Unified Chemical Data Hosting and Analysis Platform
4 affiliations
- 1Laboratory for Computational Molecular Design, Institute of Chemical Sciences and Engineering
- 2École Polytechnique Fédérale de Lausanne (EPFL)
- 3National Centre for Computational Design and Discovery of Novel Materials (MARVEL)
- 4National Centre for Competence in Research-Catalysis (NCCR-Catalysis)
Abstract
Chemical datasets used in computational chemistry are often distributed across separate repositories, stored in dataset-specific formats, and accompanied by heterogeneous metadata, property definitions, and structure representations. This fragmentation increases the manual preprocessing required to reuse datasets for molecular property prediction, reaction modeling, benchmarking, and machine-learning workflows. Here, we present LCMD-db, a chemical data hosting and analysis platform for organizing molecular, fragment, and reaction datasets within a common framework. LCMD-db represents data as datasets and self-consistent subsets, with explicit metadata, property definitions, structure mappings, and standardized ingestion pipelines. The platform supports molecular structures, fragments, equilibrium geometries, transition states, reaction participants, and computed properties linked to SMILES strings, molecular graphs, and three-dimensional structure files. For reaction datasets, LCMD-db stores molecular participants together with their chemical roles and reaction-coordinate relationships, allowing intermediates, transition states, reactants, products, catalysts, and other species to be treated as connected chemical entities rather than isolated files. The platform provides interactive visualization, property inspection, filtering, export of selected entries, and Python-native access to structured molecular and reaction objects. We demonstrate LCMD-db using in-house and external datasets spanning small organic molecules, transition-metal complexes, molecular fragments, and reaction datasets with thermodynamic or kinetic annotations. LCMD-db connects data hosting with analysis and modeling workflows by providing structured, searchable, and directly loadable chemical datasets.
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BibTeX
@misc{graux2026lcmddb,
title = {{LCMD[db]: The Unified Chemical Data Hosting and Analysis Platform}},
author = {Romain Graux and Juliette Veronique Schleicher and Thanapat Worakul and Yannick Calvino Alonso and Clémence Corminboeuf},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008334/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008334/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - LCMD[db]: The Unified Chemical Data Hosting and Analysis Platform
AU - Romain Graux
AU - Juliette Veronique Schleicher
AU - Thanapat Worakul
AU - Yannick Calvino Alonso
AU - Clémence Corminboeuf
PY - 2026
DA - 2026/09/04
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008334/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008334/v1
AB - Chemical datasets used in computational chemistry are often distributed across separate repositories, stored in dataset-specific formats, and accompanied by heterogeneous metadata, property definitions, and structure representations. This fragmentation increases the manual preprocessing required to reuse datasets for molecular property prediction, reaction modeling, benchmarking, and machine-learning workflows. Here, we present LCMD-db, a chemical data hosting and analysis platform for organizing molecular, fragment, and reaction datasets within a common framework. LCMD-db represents data as datasets and self-consistent subsets, with explicit metadata, property definitions, structure mappings, and standardized ingestion pipelines. The platform supports molecular structures, fragments, equilibrium geometries, transition states, reaction participants, and computed properties linked to SMILES strings, molecular graphs, and three-dimensional structure files. For reaction datasets, LCMD-db stores molecular participants together with their chemical roles and reaction-coordinate relationships, allowing intermediates, transition states, reactants, products, catalysts, and other species to be treated as connected chemical entities rather than isolated files. The platform provides interactive visualization, property inspection, filtering, export of selected entries, and Python-native access to structured molecular and reaction objects. We demonstrate LCMD-db using in-house and external datasets spanning small organic molecules, transition-metal complexes, molecular fragments, and reaction datasets with thermodynamic or kinetic annotations. LCMD-db connects data hosting with analysis and modeling workflows by providing structured, searchable, and directly loadable chemical datasets.
ER -