Searching low-energy conformers of neutral and protonated di-, tri-, and tetra-glycine with first-principle accuracy assisted by the use of neural network potentials

Application of neural network potentials accelerate the discovery of low-energy conformers of peptides to understand how the interplay of different interactions lead to their three-dimensional structures.