Literature DB >> 11410048

Quantitative structure-property relationships (QSPRs) for the estimation of vapor pressure: a hierarchical approach using mathematical structural descriptors.

S C Basak1, D Mills.   

Abstract

A set of 379 molecular descriptors was calculated for use in hierarchical quantitative structure-property relationship (QSPR) modeling of vapor pressure for a structurally diverse database consisting of 469 chemicals. The hierarchical approach utilizes topostructural, topochemical, geometrical, and quantum chemical descriptors in a stepwise fashion to develop QSPR models. In this way, the relative roles of the various levels of descriptors can be examined. The results show that the easily calculated topological descriptors explain the majority of the variance and that the addition of geometrical and quantum chemical descriptors does not result in a significantly improved model.

Year:  2001        PMID: 11410048     DOI: 10.1021/ci000165r

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  2 in total

1.  Topochemical models for the prediction of voltage-gated sodium channel binding activity of hydantoins and related non-hydantoins.

Authors:  Meenal Gupta; Anil Kumar Madan
Journal:  J Mol Model       Date:  2006-09-07       Impact factor: 1.810

2.  Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data.

Authors:  Alexios Koutsoukas; Keith J Monaghan; Xiaoli Li; Jun Huan
Journal:  J Cheminform       Date:  2017-06-28       Impact factor: 5.514

  2 in total

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