Exploring the lower part of discrete polymer model energy landscapes

We present a generic, problem-independent algorithm for exploration of the low-energy portion of the energy landscape of discrete systems and apply it to the energy landscape of lattice proteins. Starting from a set of optimal and near-optimal conformations derived from a constraint-based search technique, we are able to selectively investigate the lower part of lattice protein energy landscapes in two and three dimensions. This novel approach allows, in contrast to exhaustive enumeration, for an efficient calculation of optimal and near-optimal structures below a given energy threshold and is only limited by the available amount of memory. A straightforward application of the algorithm is the calculation of barrier trees (representing the energy landscape), which then allows dynamics studies based on landscape theory.