TY - JOUR
AU - 
AB - pubs.acs.org/JCTC Article Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA Jan Neumann and Nadine Schwierz* Cite This: J. Chem. Theory Comput. 2022, 18, 1202−1212 Read Online Metrics & More Article Recommendations * sı Supporting Information ACCESS ABSTRACT: Magnesium is an indispensable cofactor in countless vital processes. In order to understand its functional role, the characterization of the binding pathways to biomolecules such as RNA is crucial. Despite the importance, a molecular description is still lacking since the transition from the water-mediated outer-sphere to the direct inner- sphere coordination is on the millisecond time scale and therefore out of reach for conventional simulation techniques. To fill this gap, we use transition path sampling to resolve the binding pathways and to elucidate the role of the solvent in the binding process. The results reveal that the molecular void provoked by the leaving phosphate oxygen of the RNA is immediately filled by an entering water molecule. In addition, water molecules from the first and second hydration shell couple to the concerted exchange. To capture the intimate solute−solvent coupling, we perform a committor analysis as the basis for a machine learning algorithm that derives the optimal deep learning model from thousands 
TI - Artificial Intelligence Resolves Kinetic Pathways of Magnesium Binding to RNA
DO - 10.1101/2021.07.25.453696
DA - 2021-07-26
UR - https://www.deepdyve.com/lp/unpaywall/artificial-intelligence-resolves-kinetic-pathways-of-magnesium-binding-p0EZBhPX1I
DP - DeepDyve
ER -