Literature DB >> 17051339

Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors.

Ernesto Estrada1, Gerardo A Díaz, Eduardo J Delgado.   

Abstract

Quantitative structure-property relationship (QSPR) models are developed to predict the logarithm of infinite dilution activity coefficient of hydrocarbons, oxygen containing organic compounds and halogenated hydrocarbons in water at 298.15 K. The description of the molecular structure in terms of quantum-connectivity descriptors allows to obtain more simple QSPR models because of the quantum-chemical and topological information coded in this type of descriptors. The models developed in this paper have fewer descriptors and better statistics than other models reported in literature. The current models allow a more transparent physical interpretation of the phenomenon in terms of intermolecular interactions which occur in solution and which explain the respective deviations from ideality.

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Year:  2006        PMID: 17051339     DOI: 10.1007/s10822-006-9079-6

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  5 in total

1.  3D connectivity indices in QSPR/QSAR studies.

Authors:  E Estrada; E Molina
Journal:  J Chem Inf Comput Sci       Date:  2001 May-Jun

2.  Prediction of infinite dilution activity coefficients of chlorinated organic compounds in aqueous solution from quantum-chemical descriptors.

Authors:  Eduardo J. Delgado; Joel B. Alderete
Journal:  J Comput Chem       Date:  2001-11-30       Impact factor: 3.376

3.  The problem of overfitting.

Authors:  Douglas M Hawkins
Journal:  J Chem Inf Comput Sci       Date:  2004 Jan-Feb

4.  Quantum-connectivity descriptors in modeling solubility of environmentally important organic compounds.

Authors:  Ernesto Estrada; Eduardo J Delgado; Joel B Alderete; Gonzalo A Jaña
Journal:  J Comput Chem       Date:  2004-11-15       Impact factor: 3.376

5.  The prediction of human oral absorption for diffusion rate-limited drugs based on heuristic method and support vector machine.

Authors:  H X Liu; R J Hu; R S Zhang; X J Yao; M C Liu; Z D Hu; B T Fan
Journal:  J Comput Aided Mol Des       Date:  2005-01       Impact factor: 3.686

  5 in total

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