How Does the Quality of Phospholipidosis Data Influence the Predictivity of Structural Alerts? was written by Przybylak, Katarzyna R.;Alzahrani, Abdullah Rzgallah;Cronin, Mark T. D.. And the article was included in Journal of Chemical Information and Modeling in 2014.COA of Formula: C10H22O3 This article mentions the following:
The ability of drugs to induce phospholipidosis (PLD) is linked directly to their mol. substructures: hydrophobic, cyclic moieties with hydrophilic, peripheral amine groups. These structural properties can be captured and coded into SMILES arbitrary target specification (SMARTS) patterns. Such structural alerts, which are capable of identifying potential PLD inducers, should ideally be developed on a relatively large but reliable data set. We had previously developed a model based on SMARTS patterns consisting of 32 structural fragments using information from 450 chems. In the present study, addnl. PLD structural alerts have been developed based on a newer and larger data set combining two data sets published recently by the United States Food and Drug Administration (US FDA). To assess the predictive performance of the updated SMARTS model, two publicly available data sets were considered. These data sets were constructed using different criteria and hence represent different standards for overall quality. In the first data set high quality was assured as all neg. chems. were confirmed by the gold standard method for the detection of PLD-transmission electron microscopy (EM). The second data set was constructed from seven previously published data sets and then curated by removing compounds where conflicting results were found for PLD activity. Evaluation of the updated SMARTS model showed a strong, pos. correlation between predictive performance of the alerts and the quality of the data set used for the assessment. The results of this study confirm the importance of using high quality data for modeling and evaluation, especially in the case of PLD, where species, tissue, and dose dependence of results are addnl. confounding factors. In the experiment, the researchers used many compounds, for example, rel-(1s,4s)-4-(2-Hydroxypropan-2-yl)-1-methylcyclohexanol hydrate (cas: 2451-01-6COA of Formula: C10H22O3).
rel-(1s,4s)-4-(2-Hydroxypropan-2-yl)-1-methylcyclohexanol hydrate (cas: 2451-01-6) belongs to alcohols. Alcohols are weak acids. The most acidic simple alcohols (methanol and ethanol) are about as acidic as water, and most other alcohols are somewhat less acidic. A multistep synthesis may use Grignard-like reactions to form an alcohol with the desired carbon structure, followed by reactions to convert the hydroxyl group of the alcohol to the desired functionality.COA of Formula: C10H22O3
Referemce:
Alcohol – Wikipedia,
Alcohols – Chemistry LibreTexts