Persistent Link:
http://hdl.handle.net/10150/193517
Title:
Prediction of aqueous solubility from SCRATCH
Author:
Jain, Parijat
Issue Date:
2008
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Several methods have been proposed for the prediction of aqueous solubility. This study proposes the SCRATCH model for the aqueous solubility estimation of a compound directly from its structure. The algorithm utilizes predicted melting points and predicted aqueous activity coefficients for the solubility estimation, reflecting the truly predictive nature of the model. It uses two additive, constitutive molecular descriptors (enthalpy of melting and aqueous activity coefficient) and two non-additive molecular descriptors (symmetry and flexibility). The melting point prediction is trained on over 2200 compounds whereas the aqueous activity coefficient is trained on about 1640 compounds, making the model very rigorous and robust. The model is validated using a 10-fold cross- validation.A comparison with the General Solubility Equation suggests that the SCRATCH predicted aqueous solubilities have a slightly more average absolute error. This could result due to the fact that SCRATCH uses two predicted parameters whereas the GSE utilizes only one predicted property. Although the GSE is simpler to use, the drawback of requiring an experimental melting point is overcome in SCRATCH which can predict the aqueous solubility of a compound just based on its structure and no experimental values.
Type:
text; Electronic Dissertation
Keywords:
Pharmaceutical Sciences
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Pharmaceutical Sciences; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Yalkowsky, Samuel H
Committee Chair:
Yalkowsky, Samuel H

Full metadata record

DC FieldValue Language
dc.language.isoENen_US
dc.titlePrediction of aqueous solubility from SCRATCHen_US
dc.creatorJain, Parijaten_US
dc.contributor.authorJain, Parijaten_US
dc.date.issued2008en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractSeveral methods have been proposed for the prediction of aqueous solubility. This study proposes the SCRATCH model for the aqueous solubility estimation of a compound directly from its structure. The algorithm utilizes predicted melting points and predicted aqueous activity coefficients for the solubility estimation, reflecting the truly predictive nature of the model. It uses two additive, constitutive molecular descriptors (enthalpy of melting and aqueous activity coefficient) and two non-additive molecular descriptors (symmetry and flexibility). The melting point prediction is trained on over 2200 compounds whereas the aqueous activity coefficient is trained on about 1640 compounds, making the model very rigorous and robust. The model is validated using a 10-fold cross- validation.A comparison with the General Solubility Equation suggests that the SCRATCH predicted aqueous solubilities have a slightly more average absolute error. This could result due to the fact that SCRATCH uses two predicted parameters whereas the GSE utilizes only one predicted property. Although the GSE is simpler to use, the drawback of requiring an experimental melting point is overcome in SCRATCH which can predict the aqueous solubility of a compound just based on its structure and no experimental values.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectPharmaceutical Sciencesen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplinePharmaceutical Sciencesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorYalkowsky, Samuel Hen_US
dc.contributor.chairYalkowsky, Samuel Hen_US
dc.contributor.committeememberMayersohn, Michaelen_US
dc.contributor.committeememberMyrdal, Paul Ben_US
dc.identifier.proquest10122en_US
dc.identifier.oclc659750662en_US
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