Density-based classification of protein structures using iterative TM-score

Finding similarity between a pair of protein structures is one of the fundamental tasks in many areas of bioinformatical research such as protein structure prediction, function mapping, etc. We propose a method for finding pairing of amino acids based on densities of the structures and we also propose a modification to the original TM-score rotation algorithm that assess similarity score to this alignment. Proposed modification is faster than TM and comparably robust according to non-optimal parts in the alignment. We measure the qualities of the algorithm in terms of SCOP classification accuracy. Regarding the accuracy, our solution outperforms the contemporary solutions at two out of three tested levels of the SCOP hierarchy.