Leveraging Molecular Mechanics With the uESE Continuum Solvation Model for Efficient Solvation Free Energy Prediction : Impact of Conformation and Extensive Validation
© 2025 The Author(s). Journal of Computational Chemistry published by Wiley Periodicals LLC.
| Veröffentlicht in: | Journal of computational chemistry. - 1984. - 46(2025), 28 vom: 30. Okt., Seite e70252 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2025
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| Zugriff auf das übergeordnete Werk: | Journal of computational chemistry |
| Schlagworte: | Journal Article conformation continuum solvation model electronic structure calculations molecular mechanics solvation free energy |
| Zusammenfassung: | © 2025 The Author(s). Journal of Computational Chemistry published by Wiley Periodicals LLC. The solvation free energy is a fundamental property of a solute directly related to solubility, which in turn is critical for processes ranging from pharmaceutical to materials manufacturing. We seek to develop efficient strategies to predict the solvation free energy, knowing only molecular structure, using electronic structure calculations with the uESE continuum solvation model. Benchmarking on the Minnesota Solvation Database, single conformations generated using the molecular mechanics force field MMFF94 yielded predictive accuracy comparable to reference gas-phase optimized geometries obtained with electronic structure calculations. Surprisingly, exploring multiple conformations did not consistently improve predictions, suggesting uESE performs well with a single representative input. Evaluation on the independent dGsolvDB1 dataset demonstrated reasonable predictive ability with single molecular mechanics-generated conformations and some generalizability to novel chemical space. Our findings indicate that combining fast molecular mechanics-based structure generation with uESE offers a promising approach for efficient and reasonably accurate solvation free energy predictions, with accuracy comparable to or exceeding that of far more computationally intensive methods like explicit solvent molecular dynamics, supporting its utility in high-throughput screening and machine learning for solubility prediction |
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| Beschreibung: | Date Revised 22.10.2025 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1096-987X |
| DOI: | 10.1002/jcc.70252 |