Staff View: Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction

Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction

Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizer...

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Main Authors:	Frimayanti, N., Yam, M.L., Lee, H.B., Othman, R., Zain, Sharifuddin Md, Rahman, N.A.
Format:	Article
Language:	English
Published:	2011
Subjects:	R Medicine
Online Access:	http://eprints.um.edu.my/3459/1/22.pdf http://eprints.um.edu.my/3459/ http://www.ncbi.nlm.nih.gov/pubmed/22272096
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spelling	my.um.eprints.34592019-10-25T09:11:16Z http://eprints.um.edu.my/3459/ Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction Frimayanti, N. Yam, M.L. Lee, H.B. Othman, R. Zain, Sharifuddin Md Rahman, N.A. R Medicine Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2) (CV) value and r(2) prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC(50) values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r(2) prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set. 2011 Article PeerReviewed application/pdf en http://eprints.um.edu.my/3459/1/22.pdf Frimayanti, N. and Yam, M.L. and Lee, H.B. and Othman, R. and Zain, Sharifuddin Md and Rahman, N.A. (2011) Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction. International Journal of Molecular Sciences, 12 (12). http://www.ncbi.nlm.nih.gov/pubmed/22272096
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
language	English
topic	R Medicine
spellingShingle	R Medicine Frimayanti, N. Yam, M.L. Lee, H.B. Othman, R. Zain, Sharifuddin Md Rahman, N.A. Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
description	Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r(2) value, r(2) (CV) value and r(2) prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC(50) values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r(2) prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set.
format	Article
author	Frimayanti, N. Yam, M.L. Lee, H.B. Othman, R. Zain, Sharifuddin Md Rahman, N.A.
author_facet	Frimayanti, N. Yam, M.L. Lee, H.B. Othman, R. Zain, Sharifuddin Md Rahman, N.A.
author_sort	Frimayanti, N.
title	Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
title_short	Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
title_full	Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
title_fullStr	Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
title_full_unstemmed	Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction
title_sort	validation of quantitative structure-activity relationship (qsar) model for photosensitizer activity prediction
publishDate	2011
url	http://eprints.um.edu.my/3459/1/22.pdf http://eprints.um.edu.my/3459/ http://www.ncbi.nlm.nih.gov/pubmed/22272096
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score	13.211869

Validation of quantitative structure-activity relationship (QSAR) model for photosensitizer activity prediction

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