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.

Combination of commercial QSPR (quantitative structure−property relationship) software with an evaluated database creates a powerful tool for development of thermophysical property correlations. By using data quality codes in the DIPPR relational database, a training set of property values within a desired accuracy level can be obtained for use in QSPR regression software. Moreover, additional database queries can be used to restrict the training set to specified families or functional groups and further refine the molecular descriptors that are used to correlate the property. This provides a good basis for rapid development of QSPR correlations of known uncertainty and chemical domain. This procedure is illustrated by its application to the extension of the Macleod−Sugden (Trans. Faraday Soc. 1923, 19, 38. Chem. Soc. 1924, 125, 32.) correlation for surface tension based upon the parachor. Quayle (Chem. Rev. 1953, 53, 439−591.) correlated the parachor in terms of additive atomic and structural increments but used a training set limited in temperature and scope. In this work, new molecular descriptors were selected consistent with the accuracy of the training set extracted from the DIPPR database, and their additive increments to the parachor were regressed from 8697 surface tension values of uncertainty less than 5% for 649 different compounds. This produced a correlation with an average absolute deviation (AAD) of 3.2%. This can be compared with an AAD of 6.9% using the Quayle descriptors for the same set.

Although polyethylene glycol (PEG) is commonly used to improve protein stability and therapeutic efficacy, the optimal location for attaching PEG onto proteins is not well understood. Here, we present a cell-free protein synthesis-based screening platform that facilitates site-specific PEGylation and efficient evaluation of PEG attachment efficiency, thermal stability, and activity for different variants of PEGylated T4 lysozyme, including a di-PEGylated variant. We also report developing a computationally efficient coarse-grain simulation model as a potential tool to narrow experimental screening candidates. We use this simulation method as a novel tool to evaluate the locational impact of PEGylation. Using this screen, we also evaluated the predictive impact of PEGylation site solvent accessibility, conjugation site structure, PEG size, and double PEGylation. Our findings indicate that PEGylation efficiency, protein stability, and protein activity varied considerably with PEGylation site, variations that were not well predicted by common PEGylation guidelines. Overall our results suggest current guidelines are insufficiently predictive, highlighting the need for experimental and simulation screening systems such as the one presented here.

The interaction of proteins with surfaces is important in numerous applications in many fields-such as biotechnology, proteomics, sensors, and medicine--but fundamental understanding of how protein stability and structure are affected by surfaces remains incomplete. Over the last several years, molecular simulation using coarse grain models has yielded significant insights, but the formalisms used to represent the surface interactions have been rudimentary. We present a new model for protein surface interactions that incorporates the chemical specificity of both the surface and the residues comprising the protein in the context of a one-bead-per-residue, coarse grain approach that maintains computational efficiency. The model is parameterized against experimental adsorption energies for multiple model peptides on different types of surfaces. The validity of the model is established by its ability to quantitatively and qualitatively predict the free energy of adsorption and structural changes for multiple biologically-relevant proteins on different surfaces. The validation, done with proteins not used in parameterization, shows that the model produces remarkable agreement between simulation and experiment.

The interaction of proteins with surfaces regulates numerous processes in nature, science, and technology. In many applications, it is desirable to place proteins on surfaces in an active state, and tethering represents one manner in which to accomplish this. However, a clear understanding of how tether placement and design affects protein activity is lacking. Available theoretical models predict that proteins will be stabilized when tethered to substrates. Such models suggest that the surface reduces the number of states accessible to the unfolded state of the protein, thereby reducing the entropic cost of folding on the surface compared to the bulk case. Recent studies, however, have shown that this stabilization is not always seen. The purpose of this article is to determine the validity of the theory with a thorough thermodynamic analysis of the folding of peptides attached to surfaces. Configuration-temperature-density-of-states Monte Carlo simulations are used to examine the behavior of four different peptides of different secondary and tertiary structure. It is found that the surface does reduce the entropic cost of folding for tethered peptides, as the theory suggests. This effect, however, does not always translate into improved stability because the surface may also have a destabilizing enthalpic effect. The theory neglects this effect and assumes that the enthalpy of folding is the same on and off the surface. Both the enthalpic and entropic contributions to the stability are found to be topology- and tether-placement-specific; we show that stability cannot be predicted a priori. A detailed analysis of the folding of protein A shows how the same protein can be both stabilized and destabilized on a surface depending upon how the tethering enhances or hinders the ability of the peptide to form correct tertiary structures.