  De novo prediction of protein folding is an open scientific challenge. Many
folding models and force fields have been developed, yet all face difficulties
converging to native conformations. Hydrophobicity scales (HSs) play a crucial
role in such simulations as they define the energetic interactions between
protein residues, thus determining the energetically favorable conformation.
While many HSs have been developed over the years using various methods, it is
surprising that the scales show very weak consensus in their assignment of
hydrophobicity indexes to the various residues. In this work, several HSs are
systematically assessed via atomistic Monte Carlo simulation of folding of
small proteins, by converting the HSs of interest into residue-residue contact
energy matrices. HSs that poorly preserve native structures of proteins were
tuned by applying a linear transformation. Subsequently, folding simulations
were used to examine the ability of the HSs to correctly fold the proteins from
a random initial conformation. Root mean square deviation (RMSD) and energy of
the proteins during folding were sampled and used to define an ER-score, as the
correlation between the 2-dimensional energy-RMSD (ER) histogram with 50%
lowest energy conformations and the ER histogram with 50% lowest RMSD
conformations. Thus, we were able to compare the ability of the different HSs
to predict de novo protein folding quantitatively.
