A strategy for finding classes of minima on a hypersurface: implications for approaches to the protein folding problem

Abstract

Locating the native structure of a given protein is a task made difficult by the complexity of the potential energy hypersurface and by the huge number of local minima it contains. We have explored a strategy (the "antlion" method) for hypersurface modification that suppresses all minima but that of the native structure. Transferrable penalty functions with general applicability for modifying a hypersurface to retain the desired minimum are identified, and two blocked oligopeptides (alanine dipeptide and tetrapeptide) are used for specific numerical illustration of the dramatic simplification that ensues. In addition, an intermediary role for neural networks to manage some aspects of the antlion strategy applied to large polypeptides and proteins is introduced.