Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds
We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538molecular descriptors derived with PaDEL...
Autores principales: | , , , |
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Formato: | Articulo |
Lenguaje: | Inglés |
Publicado: |
2016
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Materias: | |
Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/86908 |
Aporte de: |
id |
I19-R120-10915-86908 |
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record_format |
dspace |
institution |
Universidad Nacional de La Plata |
institution_str |
I-19 |
repository_str |
R-120 |
collection |
SEDICI (UNLP) |
language |
Inglés |
topic |
Química Correlation and logic software Estimation program interface suite software Pharmaceutical data exploration laboratory software Quantitative structure-property relationships Replacement method Soil sorption coefficient |
spellingShingle |
Química Correlation and logic software Estimation program interface suite software Pharmaceutical data exploration laboratory software Quantitative structure-property relationships Replacement method Soil sorption coefficient Aranda, José Francisco Garro Martinez, Juan C. Castro, Eduardo Alberto Duchowicz, Pablo Román Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
topic_facet |
Química Correlation and logic software Estimation program interface suite software Pharmaceutical data exploration laboratory software Quantitative structure-property relationships Replacement method Soil sorption coefficient |
description |
We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly well with a previously reported one that uses Dragon descriptors. |
format |
Articulo Articulo |
author |
Aranda, José Francisco Garro Martinez, Juan C. Castro, Eduardo Alberto Duchowicz, Pablo Román |
author_facet |
Aranda, José Francisco Garro Martinez, Juan C. Castro, Eduardo Alberto Duchowicz, Pablo Román |
author_sort |
Aranda, José Francisco |
title |
Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
title_short |
Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
title_full |
Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
title_fullStr |
Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
title_full_unstemmed |
Conformation-independent QSPR approach for the soil sorption coefficient of heterogeneous compounds |
title_sort |
conformation-independent qspr approach for the soil sorption coefficient of heterogeneous compounds |
publishDate |
2016 |
url |
http://sedici.unlp.edu.ar/handle/10915/86908 |
work_keys_str_mv |
AT arandajosefrancisco conformationindependentqsprapproachforthesoilsorptioncoefficientofheterogeneouscompounds AT garromartinezjuanc conformationindependentqsprapproachforthesoilsorptioncoefficientofheterogeneouscompounds AT castroeduardoalberto conformationindependentqsprapproachforthesoilsorptioncoefficientofheterogeneouscompounds AT duchowiczpabloroman conformationindependentqsprapproachforthesoilsorptioncoefficientofheterogeneouscompounds |
bdutipo_str |
Repositorios |
_version_ |
1764820489441640452 |