Markov state model of the two-state behaviour of water

Abstract

With the help of a Markov State Model (MSM), two-state behaviour is resolved for two computer models of water in a temperature range from 255 K to room temperature (295 K). The method is first validated for ST2 water, for which the so far strongest evidence for a liquid-liquid phase transition exists. In that case, the results from the MSM can be cross-checked against the radial distribution function g(5)(r) of the 5th-closest water molecule around a given reference water molecule. The latter is a commonly used local order parameter, which exhibits a bimodal distribution just above the liquidliquid critical point that represents the low-density form of the liquid (LDL) and the high density liquid. The correlation times and correlation lengths of the corresponding spatial domains are calculated and it is shown that they are connected via a simple diffusion model. Once the approach is established, TIP4P/2005 will be considered, which is the much more realistic representation of real water. The MSM can resolve two-state behavior also in that case, albeit with significantly smaller correlation times and lengths. The population of LDL-like water increases with decreasing temperature, thereby explaining the density maximum at 4 degrees C along the lines of the two-state model of water. Published by AIP Publishing. With the help of a Markov State Model (MSM), two-state behaviour is resolved for two computer models of water in a temperature range from 255 K to room temperature (295 K). The method is first validated for ST2 water, for which the so far strongest evidence for a liquid-liquid phase transition exists. In that case, the results from the MSM can be cross-checked against the radial distribution function g 5 (r) of the 5th-closest water molecule around a given reference water molecule. The latter is a commonly used local order parameter, which exhibits a bimodal distribution just above the liquid-liquid critical point that represents the low-density form of the liquid (LDL) and the high density liquid. The correlation times and correlation lengths of the corresponding spatial domains are calculated and it is shown that they are connected via a simple diffusion model. Once the approach is established, TIP4P/2005 will be considered, which is the much more realistic representation of real water. The MSM can resolve two-state behavior also in that case, albeit with significantly smaller correlation times and lengths. The population of LDL-like water increases with decreasing temperature, thereby explaining the density maximum at 4• C along the lines of the two-state model of water. Published by AIP Publishing. [http://dx

Supercooled and glassy water: Metastable liquid(s), amorphous solid(s), and a no-man’s land

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Solvation Layer of Antifreeze Proteins Analyzed with a Markov State Model

“…The Markov state model used to analyse of the protein solvation layer has been constructed in essentially the same way as in Ref. 62, where the two-state behaviour of bulk water has been investigated. In brief, the five closest water molecules around a given reference water molecule were selected.…”

“…In comparison to Ref. 62, the algorithm had to be adapted only to a minor extent for the purpose of the present study. That is, since the structures of the five closest water molecules around a given water molecule need to be analyzed with regard to the question whether it is HDL or LDL-like, it does not make sense to consider reference water molecules in the first solvation layer around the protein, since those necessarily will have a smaller coordination number.…”

Feature vector clustering molecular pairs in computer simulations

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“…Hamm studied the two-state water behavior, clustering microstates of waters via MSM. [44] Da et al studied the backtracking process of RNA Polymerase II by MSM, dividing MD samples into 800 states by k-centers clustering. [45] Zhao et al developed a parallel k-center clustering method and identified states of biomolecule.…”