The continued concerted development of novel efficient algorithms and computer architectures has made it possible to perform quantum chemistry (QC) calculations on very big systems as highlighted recently in Ref. Unfortunately, the procedure of simply increasing the size of the system treated with quantum mechanics (QM) still suffers from relative high computational cost especially when studying bio-molecular systems, where effects of nuclear dynamics can play a crucial role. Usually such dynamics is handled by coupling the quantum mechanical method to e.g. molecular dynamics. In addition to this, problems with methods rooted in density functional theory (DFT) have been observed when increasing the size of the molecular system, 3 despite of DFT being the most used method for treating big molecular systems. Such problems usually show up in finite cluster representations of the system considered and leads, in the case of solute-solvent systems, to artificially edge effects. Hence, alternative methods to large cluster QM calculations seem to be well justified.