Understanding the behavior of DNA at the molecular level is of considerable fundamental and engineering importance. While adequate representations of DNA exist at the atomic and continuum level, there is a relative lack of models capable of describing the behavior of DNA at mesoscopic length scales. We present a mesoscale model of DNA that reduces the complexity of a nucleotide to three interactions sites, one each for the phosphate, sugar, and base, thereby rendering the investigation of DNA up to a few microns in length computationally tractable. The charges on these sites are considered explicitly. The model is parametrized using thermal denaturation experimental data at a fixed salt concentration. The validity of the model is established by its ability to predict several aspects of DNA behavior, including salt-dependent melting, bubble formation and rehybridization, and the mechanical properties of the molecule as a function of salt concentration.

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.

Commercialization of protein-based therapeutics is a challenging task in part due to the difficulties in maintaining protein solutions safe and efficacious throughout the drug product development process, storage, transportation and patient administration. Bulk drug substance goes through a series of formulation, fill and finish operations to provide the final dosage form in the desired formulation and container or delivery device. Different process parameters during each of these operations can affect the purity, activity and efficacy of the final product. Common protein degradation pathways and the various physical and chemical factors that can induce such reactions have been extensively studied for years. This review presents an overview of the various formulation-fill-finish operations with a focus on processing steps and conditions that can impact product quality. Various manufacturing operations including bulk freeze-thaw, formulation, filtration, filling, lyophilization, inspection, labeling, packaging, storage, transport and delivery have been reviewed. The article highlights our present day understanding of protein instability issues during biopharmaceutical manufacturing and provides guidance on process considerations that can help alleviate these concerns.

A Monte Carlo algorithm that performs a random walk in energy space has been used to study random coil-helix and random coil-beta sheet transitions in model proteins. This method permits estimation of the density of states of a protein via a random walk on the energy surface, thereby allowing the system to escape from local free-energy minima with relative ease. A cubic lattice model and a knowledge based force field are employed for these simulations. It is shown that, for a given amino acid sequence, the method is able to fold long polypeptides reproducibly. Its results compare favorably with those of annealing and parallel tempering simulations, which have been used before in the same context. This method is used to examine the effect of amino acid sequence and chain length on the folding of several designer polypeptides.

The effects of chaperonin-like cage-induced confinement on protein stability have been studied for molecules of varying sizes and topologies. Minimalist models based on Gō-like interactions are employed for the proteins, and density-of-states-based Monte Carlo simulations are performed to accurately characterize the thermodynamic transitions. This method permits efficient sampling of conformational space and yields precise estimates of free energy and entropic changes associated with protein folding. We find that confinement-driven stabilization is not only dependent on protein size and cage radius, but also on the specific topology. The choice of the confining potential is also shown to have an effect on the observed stabilization and the scaling behavior of the stabilization with respect to the cage size.