ATP7B is a copper-transporting ATPase that plays a key role in the regulation of copper homeostasis. Mutations in the ATP7B gene are causative for Wilson's disease, and recent reports have suggested that genetic variants are associated with susceptibility to Alzheimer's disease. Unfortunately, it is difficult to profile experimentally novel genetic variants in the ATP7B gene, because the human protein X-ray structure is not yet entirely understood. In order to investigate ATP7B non-synonymous substitutions, we used an in silico amino acid sequence-based approach. Specifically, we analyzed 337 ATP7B non-synonymous substitutions, which included Wilson's disease-causing mutations (DVs) and non Wilson's disease-causing variants (NDVs), with an algorithm that estimated a combined probability (cPdel) of an amino acidic change to be deleterious for the protein function. This approach appeared to reliably indentify the probability of DVs and NDVs to be deleterious and to profile still unknown gene variants. Specifically, after analyzing ATP7B protein domains with the cPdel method, we found results in line with the predicted-modeled domains and some new suggestions. In conclusion, a functional survey of amino acid changes in the ATP7B protein is provided herein, and we suggest that this bioinformatic method can furnish information about novel ATP7B mutations. Furthermore, the same approach can be applied to other uncharacterized proteins.