Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives

The assessment of cardiotoxicity is a persistent problem in medicinal chemistry. Quantitative structure–activity relationships (QSAR) are one possible way to build up models for cardiotoxicity. Here, we describe the results obtained with the Monte Carlo technique to develop hybrid optimal descriptor...

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Autores principales: Toropova, Alla P., Toropov, Andrey A., Roncaglioni, Alessandra, Benfenati, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535953/
https://www.ncbi.nlm.nih.gov/pubmed/37764363
http://dx.doi.org/10.3390/molecules28186587
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author Toropova, Alla P.
Toropov, Andrey A.
Roncaglioni, Alessandra
Benfenati, Emilio
author_facet Toropova, Alla P.
Toropov, Andrey A.
Roncaglioni, Alessandra
Benfenati, Emilio
author_sort Toropova, Alla P.
collection PubMed
description The assessment of cardiotoxicity is a persistent problem in medicinal chemistry. Quantitative structure–activity relationships (QSAR) are one possible way to build up models for cardiotoxicity. Here, we describe the results obtained with the Monte Carlo technique to develop hybrid optimal descriptors correlated with cardiotoxicity. The predictive potential of the cardiotoxicity models (pIC50, Ki in nM) of piperidine derivatives obtained using this approach provided quite good determination coefficients for the external validation set, in the range of 0.90–0.94. The results were best when applying the so-called correlation intensity index, which improves the predictive potential of a model.
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spelling pubmed-105359532023-09-29 Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives Toropova, Alla P. Toropov, Andrey A. Roncaglioni, Alessandra Benfenati, Emilio Molecules Article The assessment of cardiotoxicity is a persistent problem in medicinal chemistry. Quantitative structure–activity relationships (QSAR) are one possible way to build up models for cardiotoxicity. Here, we describe the results obtained with the Monte Carlo technique to develop hybrid optimal descriptors correlated with cardiotoxicity. The predictive potential of the cardiotoxicity models (pIC50, Ki in nM) of piperidine derivatives obtained using this approach provided quite good determination coefficients for the external validation set, in the range of 0.90–0.94. The results were best when applying the so-called correlation intensity index, which improves the predictive potential of a model. MDPI 2023-09-12 /pmc/articles/PMC10535953/ /pubmed/37764363 http://dx.doi.org/10.3390/molecules28186587 Text en © 2023 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
Toropova, Alla P.
Toropov, Andrey A.
Roncaglioni, Alessandra
Benfenati, Emilio
Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title_full Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title_fullStr Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title_full_unstemmed Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title_short Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives
title_sort using the correlation intensity index to build a model of cardiotoxicity of piperidine derivatives
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10535953/
https://www.ncbi.nlm.nih.gov/pubmed/37764363
http://dx.doi.org/10.3390/molecules28186587
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