Energy-entropy prediction of octanol-water logP of SAMPL7 N-acyl sulfonamide bioisosters.
AuthorsFalcioni, Fabio; email: email@example.com
Henchman, Richard H; orcid: 0000-0002-0461-6625; email: firstname.lastname@example.org
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AbstractPartition coefficients quantify a molecule's distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol-water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.
CitationJournal of computer-aided molecular design, volume 35, issue 7, page 831-840
DescriptionFrom Europe PMC via Jisc Publications Router
History: ppub 2021-07-01, epub 2021-07-10
Publication status: Published
Funder: Engineering and Physical Sciences Research Council; Grant(s): EP/L015218/1, EP/N025105/1
Funder: NIGMS NIH HHS; Grant(s): R01 GM124270