Prediction and Validation of a Protein’s Free Energy Surface Using Hydrogen Exchange and (Importantly) Its Denaturant Dependence
Xiangda Peng, Michael C. Baxa, Nabil F. Faruk, Joseph R. Sachleben, Sebastian Pintscher, Isabelle A. Gagnon, Scott Houliston, C.H. Arrowsmith, Karl F. Freed, Sugyan M. Dixit, Tobin R. Sosnick
Abstract
's accuracy is considerably improved upon modifying the energy function using a new machine-learning procedure that trains for proper protein behavior including realistic denatured states in addition to stable native states. The resulting increase in cooperativity is critical for replicating the HDX data and protein stability, indicating that we have properly encoded the underlying physiochemical interactions into an MD package. We did observe some mismatch, however, underscoring the ongoing challenges faced by simulations in calculating accurate FESs. Nevertheless, our ensembles can identify the properties of the fluctuations that lead to HDX, whether they be small-, medium-, or large-scale openings, and can speak to the breadth of the native ensemble that has been a matter of debate.