The problem of finding the global minimum of molecular potential energy function is very  challenging for algorithms which attempt to determine global optimal solution. The principal difficulty  in minimizing the molecular potential energy function is that the number of local minima increases  exponentially with the size of the molecule. The global minimum of the potential energy of a molecule  corresponds to its most stable conformation, which dictates the majority of its properties. In this paper  the efficiency of four newly developed real coded genetic algorithms is tested on the molecular potential  energy function and their supremacy is established over other existing algorithms. The minimization of  the function is performed on an independent set of internal coordinates involving only torsion angles.  Computational results with up to 100 degrees of freedom are presented