Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds

The objective of the article was to perform a predictive analysis, based on quantitative structure-property relationships, of the dissociation constants (pKa) of different medicinal compounds (e.g., salicylic acid, salbutamol, lidocaine). Given the importance of this property in medicinal chemistry,...

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Autores principales:	Mercader, Andrew Gustavo, Goodarzi, Mohammad, Duchowicz, Pablo Román, Fernández, Francisco Marcelo, Castro, Eduardo Alberto
Formato:	Articulo
Lenguaje:	Inglés
Publicado:	2010
Materias:	Química Enhanced replacement method Pharmaceutical compounds pKa QSPR
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/82551
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-82551
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Química Enhanced replacement method Pharmaceutical compounds pKa QSPR
spellingShingle	Química Enhanced replacement method Pharmaceutical compounds pKa QSPR Mercader, Andrew Gustavo Goodarzi, Mohammad Duchowicz, Pablo Román Fernández, Francisco Marcelo Castro, Eduardo Alberto Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
topic_facet	Química Enhanced replacement method Pharmaceutical compounds pKa QSPR
description	The objective of the article was to perform a predictive analysis, based on quantitative structure-property relationships, of the dissociation constants (pKa) of different medicinal compounds (e.g., salicylic acid, salbutamol, lidocaine). Given the importance of this property in medicinal chemistry, it is of interest to develop theoretical methods for its prediction. The descriptors selection from a pool containing more than a thousand geometrical, topological, quantum-mechanical, and electronic types of descriptors was performed using the enhanced replacement method. Genetic algorithm and the replacement method (RM) techniques were used as reference points. A new methodology for the selection of the optimal number of descriptors to include in a model was presented and successfully used, showing that the best model should contain four descriptors. The best quantitative structure-property relationships linear model constructed using 62 molecular structures not previously used in this type of quantitative structure-property study showed good predictive attributes. The root mean squared error of the 26 molecules test set was 0.5600. The analysis of the quantitative structure-property relationships model suggests that the dissociation constants depend significantly on the number of acceptor atoms for H-bonds and on the number of carboxylic acids present in the molecules.
format	Articulo Articulo
author	Mercader, Andrew Gustavo Goodarzi, Mohammad Duchowicz, Pablo Román Fernández, Francisco Marcelo Castro, Eduardo Alberto
author_facet	Mercader, Andrew Gustavo Goodarzi, Mohammad Duchowicz, Pablo Román Fernández, Francisco Marcelo Castro, Eduardo Alberto
author_sort	Mercader, Andrew Gustavo
title	Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
title_short	Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
title_full	Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
title_fullStr	Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
title_full_unstemmed	Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds
title_sort	predictive qspr study of the dissociation constants of diverse pharmaceutical compounds
publishDate	2010
url	http://sedici.unlp.edu.ar/handle/10915/82551
work_keys_str_mv	AT mercaderandrewgustavo predictiveqsprstudyofthedissociationconstantsofdiversepharmaceuticalcompounds AT goodarzimohammad predictiveqsprstudyofthedissociationconstantsofdiversepharmaceuticalcompounds AT duchowiczpabloroman predictiveqsprstudyofthedissociationconstantsofdiversepharmaceuticalcompounds AT fernandezfranciscomarcelo predictiveqsprstudyofthedissociationconstantsofdiversepharmaceuticalcompounds AT castroeduardoalberto predictiveqsprstudyofthedissociationconstantsofdiversepharmaceuticalcompounds
bdutipo_str	Repositorios
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Predictive QSPR study of the dissociation constants of diverse pharmaceutical compounds

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