Energy landscapes and global thermodynamics for alanine peptides

We compare different approaches for computing the thermodynamics of biomolecular systems. Techniques based on parallel replicas evolving via molecular dynamics or Monte Carlo simulations produce overlapping histograms for the densities of states. In contrast, energy landscape methods employ a superposition partition function constructed from local minima of the potential energy surface. The latter approach is particularly powerful for systems exhibiting broken ergodicity, and it is usually implemented using a harmonic normal mode approximation, which has not been extensively tested for biomolecules. The present contribution compares these alternative approaches for small alanine peptides modelled using the CHARMM and AMBER force fields. Densities of states produced from canonical sampling using multiple temperature replicas provide accurate reference data to evaluate the effect of the harmonic normal mode approximation in the superposition calculations. This benchmarking lays foundations for the application of energy landscape methods to larger biomolecules. It will also provide well characterised model systems for developing enhanced sampling methods, and for the treatment of anharmonicity corresponding to individual local minima.