Embedded Neural Network Potentials
/Neural network potentials (NNPs) are neural networks that are trained using machine-learning to reproduce the potential energy of atomic coordinates. Neural network potentials, like the ANI-1ccX model, provide the same accuracy of high-level ab initio CCSD(T) calculations but at one billionth of the cost. We have developed to use a NNP to describe a component of the system but the rest of the system is described using a conventional of molecular mechanical model. We have implemented this through the QM/MM features of NAMD.
