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A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method

Quantitative relationships between molecular structure of forty eight aldehyde compounds with their known Cathepsin K inhibitory effects were discovered by partial least squares (PLS) method. Evaluation of a test set of 10 compounds with the developed PLS model revealed that this model is reliable w...

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Autores principales: Shahlaei, M., Fassihi, A., Saghaie, L., Arkan, E., Pourhossein, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3249776/
https://www.ncbi.nlm.nih.gov/pubmed/22224089
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author Shahlaei, M.
Fassihi, A.
Saghaie, L.
Arkan, E.
Pourhossein, A.
author_facet Shahlaei, M.
Fassihi, A.
Saghaie, L.
Arkan, E.
Pourhossein, A.
author_sort Shahlaei, M.
collection PubMed
description Quantitative relationships between molecular structure of forty eight aldehyde compounds with their known Cathepsin K inhibitory effects were discovered by partial least squares (PLS) method. Evaluation of a test set of 10 compounds with the developed PLS model revealed that this model is reliable with a good predictability. Since the QSAR study was performed on the basis of theoretical descriptors calculated completely from the molecular structures, the proposed model could potentially provide useful information about the activity of the studied compounds. Various tests and criteria such as leave-one-out cross validation, leave-many-out cross validation, and also criteria suggested by Tropsha were employed to examine the predictability and robustness of the developed model.
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spelling pubmed-32497762012-01-05 A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method Shahlaei, M. Fassihi, A. Saghaie, L. Arkan, E. Pourhossein, A. Res Pharm Sci Original Article Quantitative relationships between molecular structure of forty eight aldehyde compounds with their known Cathepsin K inhibitory effects were discovered by partial least squares (PLS) method. Evaluation of a test set of 10 compounds with the developed PLS model revealed that this model is reliable with a good predictability. Since the QSAR study was performed on the basis of theoretical descriptors calculated completely from the molecular structures, the proposed model could potentially provide useful information about the activity of the studied compounds. Various tests and criteria such as leave-one-out cross validation, leave-many-out cross validation, and also criteria suggested by Tropsha were employed to examine the predictability and robustness of the developed model. Medknow Publications & Media Pvt Ltd 2011 /pmc/articles/PMC3249776/ /pubmed/22224089 Text en Copyright: © Journal of Research in Pharmaceutical Sciences http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Shahlaei, M.
Fassihi, A.
Saghaie, L.
Arkan, E.
Pourhossein, A.
A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title_full A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title_fullStr A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title_full_unstemmed A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title_short A modeling study of aldehyde inhibitors of human cathepsin K using partial least squares method
title_sort modeling study of aldehyde inhibitors of human cathepsin k using partial least squares method
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3249776/
https://www.ncbi.nlm.nih.gov/pubmed/22224089
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