Isomers and Energy Landscapes of Perchlorate-Water Clusters and a Comparison to Pure Water and Sulfate-Water Clusters.

Hydrated ions are crucially important in a wide array of environments, from biology to the atmosphere, and the presence and concentration of ions in a system can drastically alter its behavior. One way in which ions can affect systems is in their interactions with proteins. The Hofmeister series ranks ions by their ability to salt-out proteins, with kosmotropes, such as sulfate, increasing their stability and chaotropes, such as perchlorate, decreasing their stability. We study hydrated perchlorate clusters as they are strongly chaotropic and thus exhibit different properties than sulfate. In this study we simulate small hydrated perchlorate clusters using a basin-hopping geometry optimization search with empirical potentials. We compare topological features of these clusters to data from both computational and experimental studies of hydrated sulfate ions and draw some conclusions about ion effects in the Hofmeister series. We observe a patterning conferred to the water molecules within the cluster by the presence of the perchlorate ion and compare the magnitude of this effect to that observed in previous studies involving sulfate. We also investigate the influence of the overall ionic charge on the low-energy structures adopted by these clusters.

Structures and Energy Landscapes of Hydrated Sulfate Clusters.

The sulfate ion is the most kosmotropic member of the Hofmeister series, but the chemical origins of this effect are unclear. We present a global optimization and energy landscape mapping study of microhydrated sulfate ions, SO4(2-)(H2O)n, in the size range 3 ≤ n ≤ 50. The clusters are modeled using a rigid-body empirical potential and optimized using basin-hopping Monte Carlo in conjunction with a move set including cycle inversions to explore hydrogen bond topologies. For clusters containing a few water molecules (n ≤ 6) we are able to reproduce ab initio global minima, either as global minima of the empirical potential, or as low-energy isomers. This result justifies applications to larger systems. Experimental studies have shown that dangling hydroxyl groups are present on the surfaces of pure water clusters, but absent in hydrated sulfate clusters up to n ≈ 43. Our global optimization results agree with this observation, with dangling hydroxyl groups absent from the low-lying minima of small clusters, but competitive in larger clusters.

Visualizing energy landscapes with metric disconnectivity graphs.

The visualization of multidimensional energy landscapes is important, providing insight into the kinetics and thermodynamics of a system, as well the range of structures a system can adopt. It is, however, highly nontrivial, with the number of dimensions required for a faithful reproduction of the landscape far higher than can be represented in two or three dimensions. Metric disconnectivity graphs provide a possible solution, incorporating the landscape connectivity information present in disconnectivity graphs with structural information in the form of a metric. In this study, we present a new software package, PyConnect, which is capable of producing both disconnectivity graphs and metric disconnectivity graphs in two or three dimensions. We present as a test case the analysis of the 69-bead BLN coarse-grained model protein and show that, by choosing appropriate order parameters, metric disconnectivity graphs can resolve correlations between structural features on the energy landscape with the landscapes energetic and kinetic properties.