We discuss a discretization-based solution approach for a classic problem in global 1 optimization, namely the distance geometry problem (DGP). We focus our attention on a par-1 2 ticular class of the DGP which is concerned with the identification of the conformation of 3 biological molecules. Among the many relevant ideas for the discretization of the DGP in 4 the literature, we identify the most promising ones and address their inherent limitations 5 to application to this class of problems. The result is an improved method for estimating 2 6 3D structures of small proteins based only on the knowledge of some distance restraints 7 between pairs of atoms. We present computational results showcasing the usefulness of the 8 new proposed approach. Proteins act on living cells according to their geometric and chem-9 ical properties: finding protein conformations can be very useful within the pharmaceutical 10 industry in order to synthesize new drugs.