997 resultados para Vehicle dynamics


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Temocapril is a prodrug whose hydrolysis by carboxylesterase 1 (CES1) yields the active ACE inhibitor temocaprilat. This molecular-dynamics (MD) study uses a resolved structure of the human CES1 (hCES1) to investigate some mechanistic details of temocapril hydrolysis. The ionization constants of temocapril (pK1 and pK3) and temocaprilat (pK1, pK2, and pK3) were determined experimentally and computationally using commercial algorithms. The constants so obtained were in good agreement and revealed that temocapril exists mainly in three ionic forms (a cation, a zwitterion, and an anion), whereas temocaprilat exists in four major ionic forms (a cation, a zwitterion, an anion, and a dianion). All these ionic forms were used as ligands in 5-ns MS simulations. While the cationic and zwitterionic forms of temocapril were involved in an ion-pair bond with Glu255 suggestive of an inhibitor behavior, the anionic form remained in a productive interaction with the catalytic center. As for temocaprilat, its cation appeared trapped by Glu255, while its zwitterion and anion made a slow departure from the catalytic site and a partial egress from the protein. Only its dianion was effectively removed from the catalytic site and attracted to the protein surface by Lys residues. A detailed mechanism of product egress emerges from the simulations.

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We have developed a processing methodology that allows crosshole ERT (electrical resistivity tomography) monitoring data to be used to derive temporal fluctuations of groundwater electrical resistivity and thereby characterize the dynamics of groundwater in a gravel aquifer as it is infiltrated by river water. Temporal variations of the raw ERT apparent-resistivity data were mainly sensitive to the resistivity (salinity), temperature and height of the groundwater, with the relative contributions of these effects depending on the time and the electrode configuration. To resolve the changes in groundwater resistivity, we first expressed fluctuations of temperature-detrended apparent-resistivity data as linear superpositions of (i) time series of riverwater-resistivity variations convolved with suitable filter functions and (ii) linear and quadratic representations of river-water-height variations multiplied by appropriate sensitivity factors; river-water height was determined to be a reliable proxy for groundwater height. Individual filter functions and sensitivity factors were obtained for each electrode configuration via deconvolution using a one month calibration period and then the predicted contributions related to changes in water height were removed prior to inversion of the temperature-detrended apparent-resistivity data. Applications of the filter functions and sensitivity factors accurately predicted the apparent-resistivity variations (the correlation coefficient was 0.98). Furthermore, the filtered ERT monitoring data and resultant time-lapse resistivity models correlated closely with independently measured groundwater electrical resistivity monitoring data and only weakly with the groundwater-height fluctuations. The inversion results based on the filtered ERT data also showed significantly less inversion artefacts than the raw data inversions. We observed resistivity increases of up to 10% and the arrival time peaks in the time-lapse resistivity models matched those in the groundwater resistivity monitoring data.

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