SAMPL7 physical property prediction from EC-RISM theory

Inspired by the successful application of the embedded cluster reference interaction site model (EC-RISM), a combination of quantum–mechanical calculations with three-dimensional RISM theory to predict Gibbs energies of species in solution within the SAMPL6.1 (acidity constants, p K a ) and SAMPL6.2 (octanol–water partition coefficients, log P ) the methodology was applied to the recent SAMPL7 physical property challenge on aqueous p K a and octanol–water log P values. Not part of the challenge but provided by the organizers, we also computed distribution coefficients log D 7.4 from predicted p K a and log P data. While macroscopic p K a predictions compared very favorably with experimental data (root mean square error, RMSE 0.72 p K units), the performance of the log P model (RMSE 1.84) fell behind expectations from the SAMPL6.2 challenge, leading to reasonable log D 7.4 predictions (RMSE 1.69) from combining the independent calculations. In the post-submission phase, conformations generated by different methodology yielded results that did not significantly improve the original predictions. While overall satisfactory compared to previous log D challenges, the predicted data suggest that further effort is needed for optimizing the robustness of the partition coefficient model within EC-RISM calculations and for shaping the agreement between experimental conditions and the corresponding model description.