Prediction of hydration free energies for the SAMPL4 data set with the AMOEBA polarizable force field
- PMID: 24577872
- DOI: 10.1007/s10822-014-9733-3
Prediction of hydration free energies for the SAMPL4 data set with the AMOEBA polarizable force field
Abstract
Hydration free energy calculations are often used to validate molecular simulation methodologies and molecular mechanics force fields. We use the free-energy perturbation method together with the AMOEBA polarizable force field and the Poltype parametrization protocol to predict the hydration free energies of 52 molecules as part of the SAMPL4 blind challenge. For comparison, similar calculations are performed using the non-polarizable General Amber force field. Against our expectations, the latter force field gives the better results compared to experiment. One possible explanation is the sensitivity of the AMOEBA results to the conformation used for parametrization.
Similar articles
-
Extended solvent-contact model approach to SAMPL4 blind prediction challenge for hydration free energies.J Comput Aided Mol Des. 2014 Mar;28(3):175-86. doi: 10.1007/s10822-014-9729-z. Epub 2014 Feb 20. J Comput Aided Mol Des. 2014. PMID: 24554191
-
Predicting hydration free energies with chemical accuracy: the SAMPL4 challenge.J Comput Aided Mol Des. 2014 Mar;28(3):211-9. doi: 10.1007/s10822-014-9725-3. Epub 2014 Feb 19. J Comput Aided Mol Des. 2014. PMID: 24550133
-
Prediction of hydration free energies for the SAMPL4 diverse set of compounds using molecular dynamics simulations with the OPLS-AA force field.J Comput Aided Mol Des. 2014 Mar;28(3):265-76. doi: 10.1007/s10822-014-9727-1. Epub 2014 Feb 21. J Comput Aided Mol Des. 2014. PMID: 24557853
-
Blind prediction of solvation free energies from the SAMPL4 challenge.J Comput Aided Mol Des. 2014 Mar;28(3):135-50. doi: 10.1007/s10822-014-9718-2. Epub 2014 Mar 11. J Comput Aided Mol Des. 2014. PMID: 24615156 Free PMC article. Review.
-
Current Status of AMOEBA-IL: A Multipolar/Polarizable Force Field for Ionic Liquids.Int J Mol Sci. 2020 Jan 21;21(3):697. doi: 10.3390/ijms21030697. Int J Mol Sci. 2020. PMID: 31973103 Free PMC article. Review.
Cited by
-
Semiclassical Vibrational Spectroscopy of Biological Molecules Using Force Fields.J Chem Theory Comput. 2020 Jun 9;16(6):3476-3485. doi: 10.1021/acs.jctc.0c00127. Epub 2020 May 20. J Chem Theory Comput. 2020. PMID: 32374992 Free PMC article.
-
Physics-Based Solubility Prediction for Organic Molecules.Chem Rev. 2025 Aug 13;125(15):7057-7098. doi: 10.1021/acs.chemrev.4c00855. Epub 2025 Jul 29. Chem Rev. 2025. PMID: 40728940 Free PMC article. Review.
-
Using Deep Graph Neural Networks Improves Physics-Based Hydration Free Energy Predictions Even for Molecules Outside of the Training Set Distribution.J Phys Chem B. 2025 Jul 24;129(29):7483-7498. doi: 10.1021/acs.jpcb.5c02263. Epub 2025 Jul 11. J Phys Chem B. 2025. PMID: 40641374 Free PMC article.
-
Performance of the SMD and SM8 models for predicting solvation free energy of neutral solutes in methanol, dimethyl sulfoxide and acetonitrile.J Comput Aided Mol Des. 2015 Mar;29(3):217-24. doi: 10.1007/s10822-014-9814-3. Epub 2014 Nov 15. J Comput Aided Mol Des. 2015. PMID: 25398641
-
Force matching as a stepping stone to QM/MM CB[8] host/guest binding free energies: a SAMPL6 cautionary tale.J Comput Aided Mol Des. 2018 Oct;32(10):983-999. doi: 10.1007/s10822-018-0165-3. Epub 2018 Oct 1. J Comput Aided Mol Des. 2018. PMID: 30276502 Free PMC article.
References
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources