We consider the Molecular Distance Geometry Problem (MDGP) that arises in nuclear magnetic resonance spectroscopy analysis, which provides a set of inter-atomic distances for certain pairs of atoms of a given protein. Considering this set of distances, the MDGP consists in finding an embedding in $R^3$ of the molecule atoms. We propose and discuss three different approaches to the MDGP based on a discretization of the solution space. Two of them use integer programming approaches and the third is a constraint programming approach. We compare the three approaches for a set of small size instances. Furthermore we discuss how such approaches can be used to improve branch and prune schemes to solve the MDGP.