We have studied the efficiency of parallel tempering simulations for a variety of systems including a coarse-grained protein, an atomistic model polypeptide, and the Lennard-Jones fluid. A scheme is proposed for the optimal allocation of temperatures in these simulations. The method is compared to the existing empirical approaches used for this purpose. Accuracy associated with the computed thermodynamic quantities such as specific heat is also computed and their dependence on the trial-exchange acceptance rate is reported.

Amyloid deposits of amylin in the pancreas are an important characteristic feature found in patients with Type-2 diabetes. The aggregate has been considered important in the disease pathology and has been studied extensively. However, the secondary structures of the individual peptide have not been clearly identified. In this work, we present detailed solution structures of rat amylin using a combination of Monte Carlo and molecular dynamics simulations. A new Monte Carlo method is presented to determine the free energy of distinct biomolecular conformations. Both folded and random-coil conformations of rat amylin are observed in water and their relative stability is examined in detail. The former contains an alpha-helical segment comprised of residues 7-17. We find that at room temperature the folded structure is more stable, whereas at higher temperatures the random-coil structure predominates. From the configurations and weights we calculate the alpha-carbon NMR chemical shifts, with results that are in reasonable agreement with experiments of others. We also calculate the infrared spectrum in the amide I stretch regime, and the results are in fair agreement with the experimental line shape presented herein.

One of the central problems in statistical mechanics is that of finding the density of states of a system. Knowledge of the density of states of a system is equivalent to knowledge of its fundamental equation, from which all thermodynamic quantities can be obtained. Over the past several years molecular simulations have made considerable strides in their ability to determine the density of states of complex fluids and materials. In this review we discuss some of the more promising approaches proposed in the recent literature along with their advantages and limitations.

A Monte Carlo simulation method is presented for simulation of phase transitions, with emphasis on the study of crystallization. The method relies on a random walk in order parameter ⌽͑q N ͒ space to calculate a free energy profile between the two coexisting phases. The energy and volume data generated over the course of the simulation are subsequently reweighed to identify the precise conditions for phase coexistence. The usefulness of the method is demonstrated in the context of crystallization of a purely repulsive Lennard-Jones system. A systematic analysis of precritical and critical nuclei as a function of supercooling reveals a gradual change from a bcc to a fcc structure inside the crystalline nucleus as it grows at large degrees of supercooling. The method is generally applicable and is expected to find applications in systems for which two or more coexisting phases can be distinguished through one or more order parameters.

The translocation of large DNA molecules through narrow pores has been examined in the context of multiscale simulations that include a full coupling of fluctuating hydrodynamic interactions, boundary effects, and molecular conformation. The actual rate constants for this process are determined for the first time, and it is shown that hydrodynamic interactions can lead to translocation rates that vary by multiple orders of magnitude when molecular weights are only changed by a factor of 10, in stark contrast to predictions from widely used free draining calculations.