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The charge transfer and polarization effects are important components in themolecular mechanism description of bio-molecules. Classical force field withfixed point charge cannot take into the account of the non-negligiblecorrelation between atomic charge and structure changes. In this work, highthroughput ab initio calculations for the pentapeptide Met-enkephalin (MetEnk)reveal that geometric dependent charge transfer among residues is significantamong tens of thousands of conformations. And we suggest a data driven modelwith machine learning algorithms to solve the geometric dependent chargefluctuations problem. This data driven model can directly provide ab initiolevel atomic charges of any structure for MetEnk, and avoids self-consistentiteration in polarizable force field. Molecular dynamics simulationsdemonstrated that the data driven model provides a possible choice to describethe explicit charge flux with minor modification of available classical forcefields. This work provides us an alternative molecular mechanism model forfuture dynamics simulation of oligopeptides.

Charge Transfer in Classical Molecular Dynamics Simulations of Met-enkephalin: Improving Traditional Force Field with Data Driven Models