Rugged Free-Energy Landscapes – An Introduction

Abstract

Understanding the static and even more the dynamical behavior of complex physical systems is one of the most challenging problems of current research in physics, chemistry and biology. Paradigmatic examples of condensed matter physics are spin glasses and structural glasses. More recently, in life sciences, the rapid advances in computational biology have added the exploration of the properties of biologically relevant macromolecules to this list. Here, the most prominent example is protein folding, but also studies of protein aggregation and adsorption to soft or hard interfaces are of great medical and technological interest. While the physics concepts underlying the behavior of spin and structural glasses are still quite close, the basic principles governing the properties of biomolecules are in many respects quite diverse. Still, there are certain joint features in all these systems which make a common treatment quite promising for future scientific advances. The lectures in this volume are mainly centered around computational approaches. Due to the steadily increasing power of modern capability computers combined with significant algorithmic improvements over the past few years, computational physics/chemistry/biology is by now the third column of basic research tools in fundamental natural science besides the traditional analytical theory and experiments. This is nicely illustrated by the “Landau triangle” in Fig. 13.1 of Chap. 13. Among the most prominent joint key features of the three fields considered in this volume are rugged free-energy landscapes which generate metastability and are often responsible for very slow dynamics. In computer simulation studies, this is reflected by a slow time evolution of the systems which tend to get trapped in one of these multiple minima. It is a great challenge to develop new simulation algorithms that alleviate the resulting slowing down problem. Usually a quite specific knowledge of the considered system is necessary to develop ideas for improvements. Once discovered, however, it is often possible to transfer new methods also to the related fields. In the last couple of years, precisely this mechanism has been at work concerning the rugged free-energy