Estimating system parameters for solvent–water and plant cuticle–water using quantum chemically estimated Abraham solute parameters. Issue 5 (18th April 2018) - Liang, Yuzhen; Torralba-Sanchez, Tifany L.; Di Toro, Dominic M.
Abstract : Finding the best solute parameter set for new systems whose system parameters need to be developed from experimental data. Abstract : Polyparameter Linear Free Energy Relationships (pp-LFERs) using Abraham system parameters have many useful applications. However, developing the Abraham system parameters depends on the availability and quality of the Abraham solute parameters. Using Quantum Chemically estimated Abraham solute Parameters (QCAP) is shown to produce pp-LFERs that have lower root mean square errors (RMSEs) of predictions for solvent–water partition coefficients than parameters that are estimated using other presently available methods. pp-LFERs system parameters are estimated for solvent–water, plant cuticle–water systems, and for novel compounds using QCAP solute parameters and experimental partition coefficients. Refitting the system parameter improves the calculation accuracy and eliminates the bias. Refitted models for solvent–water partition coefficients using QCAP solute parameters give better results (RMSE = 0.278 to 0.506 log units for 24 systems) than those based on ABSOLV (0.326 to 0.618) and QSPR (0.294 to 0.700) solute parameters. For munition constituents and munition-like compounds not included in the calibration of the refitted model, QCAP solute parameters produce pp-LFER models with much lower RMSEs for solvent–water partition coefficients (RMSE = 0.734 and 0.664 for original and refitted model, respectively) than ABSOLV (4.46 and 5.98) and QSPR (2.838 and 2.723). Refitting plant cuticle–water pp-LFER including munition constituents using QCAP solute parameters also results in lower RMSE (RMSE = 0.386) than that using ABSOLV (0.778) and QSPR (0.512) solute parameters. Therefore, for fitting a model in situations for which experimental data exist and system parameters can be re-estimated, or for which system parameters do not exist and need to be developed, QCAP is the quantum chemical method of choice.