Protein ligand-binding site comparison by a reduced vector representation derived from multidimensional scaling of generalized description of binding sites

Abstract

Proteins serve various functions in living cells. When they exert their functions, physical contact with other molecules occurs. A close connection therefore exists between their functions and structures. Therefore, comparison and classification about known and predicted protein structures provides important insight into the structural features of proteins, elucidating their functions and structures. Analyzing the mutual interactions between proteins and small molecules is important to predict the ligands which bind to parts of putative ligand binding sites. Such analysis demands a fast and efficient method for comparing ligand binding sites because of the recent increase of protein structure information. A method has been developed for representing a ligand binding site with one reduced vector for binding site comparison. Using our method, one can calculate the similarity between ligand binding sites merely by calculating the inner product of 11-dimensional vectors. The method explained herein shows higher performance of the similarity between binding sites than metrics used in existing alignment-free methods. It also shows performance that is comparable to accurate methods developed recently, which employ solving the optimization problem: APoc. Moreover, these study results suggest that this new method can provide similarities faster than our previous method.