The SAMPL9 host-guest blind challenge: an overview of binding free energy predictive accuracy.

ABSTRACT: We report the results of the SAMPL9 host-guest blind challenge for predicting binding free energies. The challenge focused on macrocycles from pillar[n]-arene and cyclodextrin host families, including WP6, and bCD and HbCD. A variety of methods were used by participants to submit binding free energy predictions. A machine learning approach based on molecular descriptors achieved the highest accuracy (RMSE of 2.04 kcal mol^-1) among the ranked methods in the WP6 dataset. Interestingly, predictions for WP6 obtained via docking tended to outperform all methods (RMSE of 1.70 kcal mol^-1), most of which are MD based and computationally more expensive. In general, methods applying force fields achieved better correlation with experiments for WP6 opposed to the m

SUBMITTER: Amezcua M 

PROVIDER: S-EPMC10954238 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature