REDUCED PROTEIN MODELS AND THEIR APPLICATION TO THE PROTEIN-FOLDING PROBLEM

One of the most important unsolved problems of computational biology i s prediction of the three-dimensional structure of a protein from its amino acid sequence. In practice, the solution to the protein folding problem demands that two interrelated problems be simultaneously addre ssed. Potentials that recognize the native state from the myriad of mi sfolded conformations are required, and the multiple minima conformati onal search problem must be solved. A means of partly surmounting both problems is to use reduced protein models and knowledge-based potenti als. Such models have been employed to elucidate a number of general f eatures of protein folding, including the nature of the energy landsca pe, the factors responsible for the uniqueness of the native state and the origin of the two-state thermodynamic behavior of globular protei ns. Reduced models have also been used to predict protein tertiary and quaternary structure. When combined with a limited amount of experime ntal information about secondary and tertiary structure, molecules of substantial complexity can be assembled. If predicted secondary struct ure and tertiary restraints are employed, low resolution models of sin gle domain proteins can be successfully predicted. Thus, simplified pr otein models have played an important role in furthering the understan ding of the physical properties of proteins.