During the last decade, the concept of energy landscapes has emerged as a unifying theme in seemingly disparate disciplines, such as biomolecular folding and aggregation, self-assembly, and glassy dynamics, and have provided fundamental insight into the thermodynamics and kinetics of complex systems. For many practical applications, it is often sufficient to consider a coarse-grained description of the landscape, in terms of stationary points (energy minima and transition states). This coarse-graining eliminates the need for dynamical sampling, and stationary points on the underlying landscape can be located in a time-independent fashion, exploiting tools of geometry optimisation. This approach offers several key advantages over conventional rare event sampling techniques, particularly for complex landscapes featuring broken ergodicity, and characterised by multiple relaxation time scales. My talk will discuss the methodological aspects of the computational energy landscape framework, and highlight some recent applications to the study of biophysical problems of contemporary interest, such as RNA folding, conformational switching between alternative folds in DNA and peptides, and structural heterogeneity in intrinsically disordered proteins.
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