Van der Waals's energy models attraction and repulsion effects between pairs of atoms. This energy is used by ab initio methods to find the tertiary structure of a protein based only on its amino acid sequence and on a force field model. Several researches suggests Genetic Algorithms (GAs), are adequate for the development of ab initio approaches for protein structure prediction. A GA generates thousands of potential structures for a protein conformation, and evaluates the van der Waals' interaction in each generated structure. In practice, 99% of running time of the GA is used with the computation of van der Waals' energy. To compute the van der Waals energy for a given structure, we need to calculate effects of the interactions of all pairs of atoms in the structure. Using this cutoff, the complexity of the algorithm is O(n²) per conformation, where n is the number of atoms of the protein. For atoms separated by more than 8 Å the van der Waals effect is relatively weak. Thus, we apply a Cell-lists method to the van der Waals function reducing the complexity of algorithm to O(n). Furthermore, we applied parallel programming to the Cell-lists method using MPI, reducing significatively the running time. The combination of the Cell-lists and MPI techniques resulted in a speedup of 1000 for a protein with 147,900 atoms.