New solubility models based on descriptors derived from the detour matrix

New molecular descriptors were derived from already-known descriptors obtained from the Detour Matrix (also known as Maximal Topological Distance Matrix or Maximum Path Matrix) and applied to the prediction of aqueous solubility of 46 structurally heterogeneous compounds, constructing one-variable m...

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Autores principales: Talevi, Alan, Castro, Eduardo Alberto, Bruno Blanch, Luis Enrique
Formato: Articulo
Lenguaje:Inglés
Publicado: 2006
Materias:
Química
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/164781
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SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-164781
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spelling I19-R120-10915-1647812024-04-13T04:38:32Z http://sedici.unlp.edu.ar/handle/10915/164781 New solubility models based on descriptors derived from the detour matrix Talevi, Alan Castro, Eduardo Alberto Bruno Blanch, Luis Enrique 2006 2024-04-12T16:53:50Z en Química New molecular descriptors were derived from already-known descriptors obtained from the Detour Matrix (also known as Maximal Topological Distance Matrix or Maximum Path Matrix) and applied to the prediction of aqueous solubility of 46 structurally heterogeneous compounds, constructing one-variable models through linear regression. The correlation coefficients between these descriptors and the experimental values of solubility were compared to those obtained with more than 1,600 widely-used descriptors included in commercial software Dragon, confirming the very good performance of the proposed descriptors. The best-performance descriptors were then applied, in combination with Dragon’s descriptors, to generate two five-variable models for the estimation of solubility. The F-Statistical and the p-value for this models confirmed high statistical significance. We also present the distribution of molecular weights, solubility values, number of H donors, number of H acceptors and number of heteroatoms for the 46 compounds employed, which show molecular diversity. The results indicate that the proposed descriptors can be applied in QSAR and QSPR studies. Nuevos descriptores moleculares fueron derivados de descriptores ya conocidos obtenidos a partir de la Matriz Detour (también conocida como Matriz de Distancias Topológicas Máximas o Matriz de Máximos Recorridos) y aplicados a la predicción de la solubilidad acuosa de 46 compuestos estructuralmente heterogéneos, construyendo modelos de una variable mediante regresión lineal. Los coeficientes de correlación entre estos descriptores y los valores de solubilidad experimental fueron comparados con aquellos obtenidos con más de 1600 descriptores de uso extendido incluidos en el software comercial Dragon, confirmando el muy buen desempeño de los descriptores propuestos. Estos descriptores fueron aplicados, en combinación con descriptores del software comercial, para generar modelos de cinco variables para estimar la solubilidad acuosa. El estadístico F y el valor p de estos modelos confirmaron alta significancia estadística. Se presenta asimismo la distribución de pesos moleculares, valores de solubilidad, número de donores de H, número de aceptores de H y número de heteroátomos para los 46 compuestos empleados, lo cual demuestra la diversidad molecular de los mismos. Los resultados indican que los descriptores propuestos pueden ser aplicados en estudios QSAR y QSPR. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas Articulo Articulo http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf 129-141
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Química
spellingShingle Química
Talevi, Alan
Castro, Eduardo Alberto
Bruno Blanch, Luis Enrique
New solubility models based on descriptors derived from the detour matrix
topic_facet Química
description New molecular descriptors were derived from already-known descriptors obtained from the Detour Matrix (also known as Maximal Topological Distance Matrix or Maximum Path Matrix) and applied to the prediction of aqueous solubility of 46 structurally heterogeneous compounds, constructing one-variable models through linear regression. The correlation coefficients between these descriptors and the experimental values of solubility were compared to those obtained with more than 1,600 widely-used descriptors included in commercial software Dragon, confirming the very good performance of the proposed descriptors. The best-performance descriptors were then applied, in combination with Dragon’s descriptors, to generate two five-variable models for the estimation of solubility. The F-Statistical and the p-value for this models confirmed high statistical significance. We also present the distribution of molecular weights, solubility values, number of H donors, number of H acceptors and number of heteroatoms for the 46 compounds employed, which show molecular diversity. The results indicate that the proposed descriptors can be applied in QSAR and QSPR studies.
format Articulo
Articulo
author Talevi, Alan
Castro, Eduardo Alberto
Bruno Blanch, Luis Enrique
author_facet Talevi, Alan
Castro, Eduardo Alberto
Bruno Blanch, Luis Enrique
author_sort Talevi, Alan
title New solubility models based on descriptors derived from the detour matrix
title_short New solubility models based on descriptors derived from the detour matrix
title_full New solubility models based on descriptors derived from the detour matrix
title_fullStr New solubility models based on descriptors derived from the detour matrix
title_full_unstemmed New solubility models based on descriptors derived from the detour matrix
title_sort new solubility models based on descriptors derived from the detour matrix
publishDate 2006
url http://sedici.unlp.edu.ar/handle/10915/164781
work_keys_str_mv AT talevialan newsolubilitymodelsbasedondescriptorsderivedfromthedetourmatrix
AT castroeduardoalberto newsolubilitymodelsbasedondescriptorsderivedfromthedetourmatrix
AT brunoblanchluisenrique newsolubilitymodelsbasedondescriptorsderivedfromthedetourmatrix
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