Empirical Modification of Force Fields for the Development of Peptide-Based Gas Sensors

Molecular dynamics models combined with computational approaches can be used as advanced screening techniques for finding highly efficient material-molecule interactions based on binding affinity, including in the development of gas sensors. However, most models are originally designed for liquid phase interactions, which do not align with gas sensing conditions, resulting in lower-than-expected performance. This study introduces an empirical modification method to adjust peptide interaction models for a gas phase, aiming to better accommodate the interaction between pentapeptides and target gas molecules. By adapting the weights of terms in the Gibbs free energy equation given in an empirical force field model, we demonstrate a significant increase in the absolute value of coefficient of determination (R02) , from an average of 0.05 with conventional liquid phase models to 0.90 with proposed gas phase models. An empirical modification technique for gas phase interactions markedly enhances the prediction accuracy of models, facilitating the effective development of peptide-based gas sensors.