Predicting Mutational Effects on Ca-Activated Chloride Conduction of TMEM16A Based on a Simulation Study.

The dysfunction and defects of ion channels are associated with many human diseases, especially for loss-of-function mutations in ion channels such as cystic fibrosis transmembrane conductance regulator mutations in cystic fibrosis. Understanding ion channels is of great current importance for both medical and fundamental purposes. Such an understanding should include the ability to predict mutational effects and describe functional and mechanistic effects. In this work, we introduce an approach to predict mutational effects based on kinetic information (including reaction barriers and transition state locations) obtained by studying the working mechanism of target proteins. Specifically, we take the Ca-activated chloride channel TMEM16A as an example and utilize the computational biology model to predict the mutational effects of key residues. Encouragingly, we verified our predictions through electrophysiological experiments, demonstrating a 94% prediction accuracy regarding mutational directions. The mutational strength assessed by Pearson's correlation coefficient is -0.80 between our calculations and the experimental results. These findings suggest that the proposed methodology is reliable and can provide valuable guidance for revealing functional mechanisms and identifying key residues of the TMEM16A channel. The proposed approach can be extended to a broad scope of biophysical systems.