Recent studies suggest that the protein folding should be revised as the emergent property of a complex system and that the Nature allows only a very limited number of folds that seem to be strongly influenced by geometrical properties. In this work we explore the principles underlying this new view and show how helical protein conformations can be obtained starting from simple considerations. To this aim, we generate a large data set of C-alpha traces made of about 65-70 C-alpha nodes, by computationally solving a model that takes into account only topological features of the all-alpha proteins; then, we build corresponding full-atom structures, by using the sequences of crystallographic structures of 4 small, globular all-alpha proteins from PDB, and analyze them in terms of structural and energetic properties. We demonstrate that our computational approach can capture the native topology by obtaining four poorly-populated sets of structures that are reasonably similar to the conformational states typical of the experimental PDB structures. The most noticeable results also show that the proposed approach generates backbone folds without the influence of the side chains and the protein sequence selects its fold from a limited number of total folds. The method may also offer a means towards the exploration of the landscape of protein conformations, including known states such as the the molten globule, as well as low-populated states not evincible by experimental techniques.