Recursive approaches to the statistical physics of lattice proteins

Introduces a class of recursively-based computational methods for studying the statistical physics of lattice polymer systems. The methods display certain novel aspects geared specifically towards the efficient analysis of lattice heteropolymer models at low temperatures. However, the general principles are in fact extremely general in scope, and can be applied also to problems at arbitrary temperatures, to homopolymers and RNA molecules, to sequence analysis issues such as inverse folding and sequence alignment, and to other discrete global optimization problems. Special importance is laid upon the need to measure in detail the structural characteristics of as large a number as possible of the low-energy states of heteropolymer models in order to understand their folding properties, as opposed to simply locating the slate of globally minimal energy (or locally minimal energy). In this way fundamental questions concerning the relevance of thermodynamic barriers in the models can be addressed.<>