limits with modeling data and modeling data with limits

Clicks: 253
ID: 194366
2006
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Ranked #159 of 292 articles by views in Proceedings of the National Academy of Sciences of the United States of America

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Abstract
Modeling of the solubility of amino acids and purine and pyrimidine bases with a set of sixteen molecular descriptors has been thoroughly analyzed to detect and understand the reasons for anomalies in the description of this property for these two classes of compounds. Unsatisfactory modeling can be ascribed to incomplete collateral data, i.e, to the fact that there is insufficient data known about the behavior of these compounds in solution. This is usually because intermolecular forces cannot be modeled. The anomalous modeling can be detected from the rather large values of the standard deviation of the estimates of the whole set of compounds, and from the unsatisfactory modeling of some of the subsets of these compounds. Thus the detected abnormalities can be used (i) to get an idea about weak intermolecular interactions such as hydration, self-association, the hydrogen-bond phenomena in solution, and (ii) to reshape the molecular descriptors with the introduction of parameters that allow better modeling. This last procedure should be used with care, bearing in mind that the solubility phenomena is rather complex.
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pogliani2006datalimits Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lionello Pogliani
Journal Proceedings of the National Academy of Sciences of the United States of America
Year 2006
DOI
10.2481/dsj.1.203
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