7 research outputs found
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
Isomers and Energy Landscapes of PerchlorateâWater Clusters and a Comparison to Pure Water and SulfateâWater 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, SO<sub>4</sub><sup>2â</sup>(H<sub>2</sub>O)<sub><i>n</i></sub>, in the size range 3 †<i>n</i> †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 (<i>n</i> †6) we are able to reproduce <i>ab initio</i> 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 <i>n</i> â 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