QMProt: A Comprehensive Dataset of Quantum Properties for Proteins

We introduce Quantum Mechanics for Proteins (QMProt), a dataset developed to support quantum computing applications in protein research. QMProt contains precise quantum-mechanical and physicochemical data, enabling the accurate characterization of biomolecules and supporting advanced computational methods like molecular fragmentation and reassembly. The dataset includes 45 molecules covering all 20 essential human amino acids and their core structural elements: amino terminal groups, carboxyl terminal groups, alpha carbons, and unique side chains. QMProt primarily features organic molecules with up to 15 non-hydrogen atoms (C, N, O, S), offering comprehensive molecular Hamiltonians, ground state energies, and detailed physicochemical properties to enhance reproducibility and advance quantum simulations in molecular biology, biochemistry, and drug discovery.

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Publication Details

Journal
Electronics
Published
2025-07-14
DOI
https://doi.org/10.3390/electronics14142825
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.00
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article

QMProt: A Comprehensive Dataset of Quantum Properties for Proteins

Parfait Atchade-Adelomou, Laia Coronas Sala
Electronics
Machine Learning in Materials Science
article

QMProt: A Comprehensive Dataset of Quantum Properties for Proteins

Parfait Atchade-Adelomou, Laia Coronas Sala
article en

Abstract

We introduce Quantum Mechanics for Proteins (QMProt), a dataset developed to support quantum computing applications in protein research. QMProt contains precise quantum-mechanical and physicochemical data, enabling the accurate characterization of biomolecules and supporting advanced computational methods like molecular fragmentation and reassembly. The dataset includes 45 molecules covering all 20 essential human amino acids and their core structural elements: amino terminal groups, carboxyl terminal groups, alpha carbons, and unique side chains. QMProt primarily features organic molecules with up to 15 non-hydrogen atoms (C, N, O, S), offering comprehensive molecular Hamiltonians, ground state energies, and detailed physicochemical properties to enhance reproducibility and advance quantum simulations in molecular biology, biochemistry, and drug discovery.

ElectronicsVol. 14(14)
Lighthouse Guild (US), IIT@MIT (US)
Openalex Percentile: Top 88%
Machine Learning in Materials Science
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QMProt: A Comprehensive Dataset of Quantum Properties for Proteins — Parfait Atchade-Adelomou, Laia Coronas Sala · Electronics (2025) | TGRS Research Map | TGRS