Genomics projects have elucidated several genes that encode protein sequences. Subsequently, the advent of the proteomics age has enabled the synthesis and 3D structure determination for these protein sequences. Some of these proteins incorporate metal atoms but it is often not known whether they are metal-binding proteins and the nature of the biological activity is not understood. Consequently, the development of methods to predict metal-mediated biological activity of proteins from the 3D structure of metal-unbound proteins is a goal of major importance. More specifically, the amino terminal Cu(II)- and Ni(II)-binding (ATCUN) motif is a small metal-binding site found in the N-terminus of many naturally occurring proteins. The ATCUN motif participates in DNA cleavage and has anti-tumor activity. In this study, we calculated average 3D electrostatic potentials (xi(k)) for 265 different proteins including 133 potential ATCUN anti-tumor proteins. We also calculated xi(k) values for the total protein or for the following specific protein regions: the core, inner, middle, and outer orbits. A linear discriminant analysis model was subsequently developed to assign proteins into two groups called ATCUN DNA-cleavage proteins and non-active proteins. The best model found was: ATCUN=1.15.xi(1)(inner)+2.18.xi(5)(middle)+27.57.xi(0)(outer)-27.57.xi(0)(total)+0.09. The model correctly classified 182 out of 197 (91.4%) and 61 out of 66 (92.4%) proteins in training and external predicting series', respectively. Finally, desirability analysis was used to predict the values for the electrostatic potential in one single region and the combined values in two regions that are desirable for ATCUN-like proteins. To the best of our knowledge, the present work is the first study in which desirability analysis has been used in protein quantitative-structure-activity-relationship (QSAR).