Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line
The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC50) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 compounds were in the...
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doaj-b1a063a42d864a4d8efb627ccfcd20a92020-11-25T01:14:57ZengElsevierData in Brief2352-34092016-12-019C57357810.1016/j.dib.2016.09.036Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell lineYum Eryanti0Adel Zamri1Neni Frimayanti2Unang Supratman3Tati Herlina4Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Riau, Pekan Baru, 26293 IndonesiaDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Riau, Pekan Baru, 26293 IndonesiaDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Riau, Pekan Baru, 26293 IndonesiaDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Padjadjaran University, Jalan Raya Bandung-Sumedang Km 21, Jatinangor 45363, Sumedang, IndonesiaDepartment of Chemistry, Faculty of Mathematics and Natural Sciences, Padjadjaran University, Jalan Raya Bandung-Sumedang Km 21, Jatinangor 45363, Sumedang, IndonesiaThe dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC50) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 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, r2 value, r2 (CV) value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set.http://www.sciencedirect.com/science/article/pii/S2352340916306084QSARMurine leukemia cell lineMLRA |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yum Eryanti Adel Zamri Neni Frimayanti Unang Supratman Tati Herlina |
spellingShingle |
Yum Eryanti Adel Zamri Neni Frimayanti Unang Supratman Tati Herlina Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line Data in Brief QSAR Murine leukemia cell line MLRA |
author_facet |
Yum Eryanti Adel Zamri Neni Frimayanti Unang Supratman Tati Herlina |
author_sort |
Yum Eryanti |
title |
Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_short |
Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_full |
Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_fullStr |
Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_full_unstemmed |
Dataset of curcumin derivatives for QSAR modeling of anti cancer against P388 cell line |
title_sort |
dataset of curcumin derivatives for qsar modeling of anti cancer against p388 cell line |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2016-12-01 |
description |
The dataset of curcumin derivatives consists of 45 compounds (Table 1) with their anti cancer biological activity (IC50) against P388 cell line. 45 curcumin derivatives were used in the model development where 30 of these compounds were in the training set and the remaining 15 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, r2 value, r2 (CV) value of 0.81, 0.67 were obtained. The QSAR model was also employed to predict the biological activity of compounds in the test set. Predictive correlation coefficient r2 values of 0.88 were obtained for the test set. |
topic |
QSAR Murine leukemia cell line MLRA |
url |
http://www.sciencedirect.com/science/article/pii/S2352340916306084 |
work_keys_str_mv |
AT yumeryanti datasetofcurcuminderivativesforqsarmodelingofanticanceragainstp388cellline AT adelzamri datasetofcurcuminderivativesforqsarmodelingofanticanceragainstp388cellline AT nenifrimayanti datasetofcurcuminderivativesforqsarmodelingofanticanceragainstp388cellline AT unangsupratman datasetofcurcuminderivativesforqsarmodelingofanticanceragainstp388cellline AT tatiherlina datasetofcurcuminderivativesforqsarmodelingofanticanceragainstp388cellline |
_version_ |
1725155408100720640 |