DE-NOVO DESIGN OF THE HYDROPHOBIC CORE OF UBIQUITIN

We have previously reported the development and evaluation of a comput ational program to assist in the design of hydrophobic cores of protei ns. In an effort to investigate the role of core packing in protein st ructure, we have used this program, referred to as Repacking of Cores (ROC), to design several variants of the protein ubiquitin. Nine ubiqu itin variants containing from three to eight hydrophobic core mutation s were constructed, purified, and characterized in terms of their stab ility and their ability to adopt a uniquely folded native-like conform ation. In general, designed ubiquitin variants are more stable than co ntrol variants in which the hydrophobic core was chosen randomly. Howe ver, in contrast to previous results with 434 cro, all designs are des tabilized relative to the wild-type (WT) protein. This raises the poss ibility that beta-sheet structures have more stringent packing require ments than alpha-helical proteins. A more striking observation is that all variants, including random controls, adopt fairly well-defined co nformations, regardless of their stability. This result supports concl usions from the cro studies that non-core residues contribute signific antly to the conformational uniqueness of these proteins while core pa cking largely affects protein stability and has less impact on the nat ure or uniqueness of the fold. Concurrent with the above work, we used stability data on the nine ubiquitin variants to evaluate and improve the predictive ability of our core packing algorithm. Additional vers ions of the program were generated that differ in potential function p arameters and sampling of side chain conformers. Reasonable correlatio ns between experimental and predicted stabilities suggest the program will be useful in future studies to design variants with stabilities c loser to that of the native protein. Taken together, the present study provides further clarification of the role of specific packing intera ctions in protein structure and stability, and demonstrates the benefi t of using systematic computational methods to predict core packing ar rangements for the design of proteins.