Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulations

Molecular dynamics simulations is a valuable tool to study protein unfolding in silico . Analyzing the relative spatial position of the residues during the simulation may indicate which residues are essential in determining the protein structure. We present a method, inspired by a popular data mining technique called Frequent Itemset Mining, that clusters sets of amino acid residues with a synchronized trajectory during the unfolding process. The proposed approach has several advantages over traditional hierarchical clustering.