Folding free energy function selects native-like protein sequences in the core but not on the surface.

An automatic protein design procedure is used to select amino acid sequences that optimize the folding free energy function for a given protein. The only information used in designing the sequences is a set of known backbone structures for each protein, a rotamer library, and a well established classical empirical force field, which relies on basic physical chemical principles that underlie molecular interactions and protein stability, and has not been adjusted to yield native-like sequences. Applying the procedure to 7 different known protein folds, representing a total of 45 different native protein structures, yields ensembles of designed sequences displaying remarkable similarity to their natural counterparts in the protein core, but which are distinctly non-native on the protein surface. We show that natural and designed sequences for a given fold score significantly higher than random sequences against profiles derived from both, designed and natural sequence ensembles. Furthermore, we find that designed sequence profiles can be used to retrieve the native sequences for many of the analyzed proteins using standard PSI-BLAST searches in sequence databases. These findings may have important implications for our understanding the selection pressures operating on natural protein sequences and hold promise for improving fold recognition.