Estimating residue evolutionary conservation by introducing von Neumann entropy and a novel gap-treating approach

Evolutionary conservation derived from a multiple sequence alignment is a powerful indicator of the functional significance of a residue, and it can help to predict active sites, ligand-binding sites, and protein interaction interfaces. The results of the existing algorithms in identifying the residue's conservation strongly depend on the sequence alignment, making the results highly variable. Here, by introducing the amino acid similarity matrix, we propose a novel gap-treating approach by combining the evolutionary information and von Neumann entropies to compute the residue conservation scores. It is indicated through a series of tested results that the new approach is quite encouraging and promising and may become a useful tool in complementing the existing methods.