One of the grand challenges in computational biology is the prediction of the three-dimensional structure of a protein, which determines its function, from its chemical makeup alone. A protein's primary structure, i. e., its amino acid sequence, is directly encoded in its DNA sequence,which is a purely one-dimensional structure that does not directly encode a three-dimensional shape. It is commonly believed that the native shape of a protein is the one corresponding to the global minimum of its internal energy; thus, the protein folding problem has been treated as an optimization problem in recent years. It is important to start solving any optimization problem from a good set of initial configurations that allow the optimization code to, ideally, search the complete optimization space for a global minimum. Our work focuses on providing an interactive, visual tool to rapidly create many initial configurations for a given amino acid sequence, which are then used as input for an optimization algorithm.
