Literature DB >> 30219007

Improving solvation energy predictions using the SMD solvation method and semiempirical electronic structure methods.

Jimmy C Kromann1, Casper Steinmann2, Jan H Jensen1.   

Abstract

The PM6 implementation in the GAMESS program is extended to elements requiring d-integrals and interfaced with the conducter-like polarized continuum model of solvation, including gradients. The accuracy of aqueous solvation energies computed using AM1, PM3, PM6, and DFT tight binding (DFTB) and the Solvation Model Density (SMD) continuum solvation model is tested using the Minnesota Solvation Database data set. The errors in SMD solvation energies predicted using Neglect of Diatomic Differential Overlap (NDDO)-based methods are considerably larger than when using density functional theory (DFT) and HF, with root mean square error (RMSE) values of 3.4-5.9 (neutrals) and 6-15 kcal/mol (ions) compared to 2.4 and ∼5 kcal/mol for HF/6-31G(d). For the NDDO-based methods, the errors are especially large for cations and considerably higher than the corresponding conductor-like screening model results, which suggests that the NDDO/SMD results can be improved by re-parameterizing the SMD parameters focusing on ions. We found that the best results are obtained by changing only the radii for hydrogen, carbon, oxygen, nitrogen, and sulfur, and this leads to RMSE values for PM3 (neutrals: 2.8/ions: ∼5 kcal/mol), PM6 (4.7/∼5 kcal/mol), and DFTB (3.9/∼5 kcal/mol) that are more comparable to HF/6-31G(d) (2.4/∼5 kcal/mol). Although the radii are optimized to reproduce aqueous solvation energies, they also lead more accurate predictions for other polar solvents such as dimethyl sulfoxide, acetonitrile, and methanol, while the improvements for non-polar solvents are negligible.

Entities:  

Year:  2018        PMID: 30219007     DOI: 10.1063/1.5047273

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  9 in total

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Authors:  Muhammad Khalid; Muhammad Nadeem Arshad; Shahzad Murtaza; Iqra Shafiq; Muhammad Haroon; Abdullah M Asiri; Sara Figueirêdo de AlcântaraMorais; Ataualpa A C Braga
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Authors:  Peng Xu; Tosaporn Sattasathuchana; Emilie Guidez; Simon P Webb; Kilinoelani Montgomery; Hussna Yasini; Iara F M Pedreira; Mark S Gordon
Journal:  J Chem Phys       Date:  2021-03-14       Impact factor: 3.488

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Journal:  Molecules       Date:  2020-05-30       Impact factor: 4.411

9.  Delfos: deep learning model for prediction of solvation free energies in generic organic solvents.

Authors:  Hyuntae Lim; YounJoon Jung
Journal:  Chem Sci       Date:  2019-08-20       Impact factor: 9.825

  9 in total

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