Cargando…

Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives

An approach using multivariate adaptive regression splines (MARSplines) was applied for quantitative structure–activity relationship studies of the antitumor activity of anthrapyrazoles. At the first stage, the structures of anthrapyrazole derivatives were subjected to geometrical optimization by th...

Descripción completa

Detalles Bibliográficos
Autores principales: Gackowski, Marcin, Szewczyk-Golec, Karolina, Pluskota, Robert, Koba, Marcin, Mądra-Gackowska, Katarzyna, Woźniak, Alina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104800/
https://www.ncbi.nlm.nih.gov/pubmed/35563523
http://dx.doi.org/10.3390/ijms23095132
_version_ 1784707882904715264
author Gackowski, Marcin
Szewczyk-Golec, Karolina
Pluskota, Robert
Koba, Marcin
Mądra-Gackowska, Katarzyna
Woźniak, Alina
author_facet Gackowski, Marcin
Szewczyk-Golec, Karolina
Pluskota, Robert
Koba, Marcin
Mądra-Gackowska, Katarzyna
Woźniak, Alina
author_sort Gackowski, Marcin
collection PubMed
description An approach using multivariate adaptive regression splines (MARSplines) was applied for quantitative structure–activity relationship studies of the antitumor activity of anthrapyrazoles. At the first stage, the structures of anthrapyrazole derivatives were subjected to geometrical optimization by the AM1 method using the Polak–Ribiere algorithm. In the next step, a data set of 73 compounds was coded over 2500 calculated molecular descriptors. It was shown that fourteen independent variables appearing in the statistically significant MARS model (i.e., descriptors belonging to 3D-MoRSE, 2D autocorrelations, GETAWAY, burden eigenvalues and RDF descriptors), significantly affect the antitumor activity of anthrapyrazole compounds. The study confirmed the benefit of using a modern machine learning algorithm, since the high predictive power of the obtained model had proven to be useful for the prediction of antitumor activity against murine leukemia L1210. It could certainly be considered as a tool for predicting activity against other cancer cell lines.
format Online
Article
Text
id pubmed-9104800
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-91048002022-05-14 Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives Gackowski, Marcin Szewczyk-Golec, Karolina Pluskota, Robert Koba, Marcin Mądra-Gackowska, Katarzyna Woźniak, Alina Int J Mol Sci Article An approach using multivariate adaptive regression splines (MARSplines) was applied for quantitative structure–activity relationship studies of the antitumor activity of anthrapyrazoles. At the first stage, the structures of anthrapyrazole derivatives were subjected to geometrical optimization by the AM1 method using the Polak–Ribiere algorithm. In the next step, a data set of 73 compounds was coded over 2500 calculated molecular descriptors. It was shown that fourteen independent variables appearing in the statistically significant MARS model (i.e., descriptors belonging to 3D-MoRSE, 2D autocorrelations, GETAWAY, burden eigenvalues and RDF descriptors), significantly affect the antitumor activity of anthrapyrazole compounds. The study confirmed the benefit of using a modern machine learning algorithm, since the high predictive power of the obtained model had proven to be useful for the prediction of antitumor activity against murine leukemia L1210. It could certainly be considered as a tool for predicting activity against other cancer cell lines. MDPI 2022-05-04 /pmc/articles/PMC9104800/ /pubmed/35563523 http://dx.doi.org/10.3390/ijms23095132 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gackowski, Marcin
Szewczyk-Golec, Karolina
Pluskota, Robert
Koba, Marcin
Mądra-Gackowska, Katarzyna
Woźniak, Alina
Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title_full Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title_fullStr Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title_full_unstemmed Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title_short Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Antitumor Activity of Anthrapyrazole Derivatives
title_sort application of multivariate adaptive regression splines (marsplines) for predicting antitumor activity of anthrapyrazole derivatives
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104800/
https://www.ncbi.nlm.nih.gov/pubmed/35563523
http://dx.doi.org/10.3390/ijms23095132
work_keys_str_mv AT gackowskimarcin applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives
AT szewczykgoleckarolina applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives
AT pluskotarobert applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives
AT kobamarcin applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives
AT madragackowskakatarzyna applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives
AT wozniakalina applicationofmultivariateadaptiveregressionsplinesmarsplinesforpredictingantitumoractivityofanthrapyrazolederivatives