Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes
Abstract Chronic myelogenous leukemia (CML) which is resulted from the BCR-ABL tyrosine kinase (TK) chimeric oncoprotein, is a malignant clonal disorder of hematopoietic stem cells. Imatinib is used as an inhibitor of BCR-ABL TK in the treatment of CML patients. The main object of the present manusc...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-26279-8 |
| _version_ | 1798005269216624640 |
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| author | Hamideh Hamzehali Shahram Lotfi Shahin Ahmadi Parvin Kumar |
| author_facet | Hamideh Hamzehali Shahram Lotfi Shahin Ahmadi Parvin Kumar |
| author_sort | Hamideh Hamzehali |
| collection | DOAJ |
| description | Abstract Chronic myelogenous leukemia (CML) which is resulted from the BCR-ABL tyrosine kinase (TK) chimeric oncoprotein, is a malignant clonal disorder of hematopoietic stem cells. Imatinib is used as an inhibitor of BCR-ABL TK in the treatment of CML patients. The main object of the present manuscript is focused on constructing quantitative activity relationships (QSARs) models for the prediction of inhibition potencies of a large series of imatinib derivatives against BCR-ABL TK. Herren, the inbuilt Monte Carlo algorithm of CORAL software is employed to develop QSAR models. The SMILES notations of chemical structures are used to compute the descriptor of correlation weights (CWs). QSAR models are established using the balance of correlation method with the index of ideality of correlation (IIC). The data set of 306 molecules is randomly divided into three splits. In QSAR modeling, the numerical value of R2, Q2, and IIC for the validation set of splits 1 to 3 are in the range of 0.7180–0.7755, 0.6891–0.7561, and 0.4431–0.8611 respectively. The numerical result of $${CR}_{p}^{2}$$ CR p 2 > 0.5 for all three constructed models in the Y-randomization test validate the reliability of established models. The promoters of increase/decrease for pIC50 are recognized and used for the mechanistic interpretation of structural attributes. |
| first_indexed | 2024-04-11T12:36:42Z |
| format | Article |
| id | doaj.art-71be19fd23f3433783e03a8a0eed8b98 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-11T12:36:42Z |
| publishDate | 2022-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-71be19fd23f3433783e03a8a0eed8b982022-12-22T04:23:36ZengNature PortfolioScientific Reports2045-23222022-12-011211910.1038/s41598-022-26279-8Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributesHamideh Hamzehali0Shahram Lotfi1Shahin Ahmadi2Parvin Kumar3Department of Chemistry, East Tehran Branch, Islamic Azad UniversityDepartment of Chemistry, Payame Noor University (PNU)Department of Pharmaceutical Chemistry, Faculty of Pharmaceutical Chemistry, Tehran Medical Sciences, Islamic Azad UniversityDepartment of Chemistry, Kurukshetra UniversityAbstract Chronic myelogenous leukemia (CML) which is resulted from the BCR-ABL tyrosine kinase (TK) chimeric oncoprotein, is a malignant clonal disorder of hematopoietic stem cells. Imatinib is used as an inhibitor of BCR-ABL TK in the treatment of CML patients. The main object of the present manuscript is focused on constructing quantitative activity relationships (QSARs) models for the prediction of inhibition potencies of a large series of imatinib derivatives against BCR-ABL TK. Herren, the inbuilt Monte Carlo algorithm of CORAL software is employed to develop QSAR models. The SMILES notations of chemical structures are used to compute the descriptor of correlation weights (CWs). QSAR models are established using the balance of correlation method with the index of ideality of correlation (IIC). The data set of 306 molecules is randomly divided into three splits. In QSAR modeling, the numerical value of R2, Q2, and IIC for the validation set of splits 1 to 3 are in the range of 0.7180–0.7755, 0.6891–0.7561, and 0.4431–0.8611 respectively. The numerical result of $${CR}_{p}^{2}$$ CR p 2 > 0.5 for all three constructed models in the Y-randomization test validate the reliability of established models. The promoters of increase/decrease for pIC50 are recognized and used for the mechanistic interpretation of structural attributes.https://doi.org/10.1038/s41598-022-26279-8 |
| spellingShingle | Hamideh Hamzehali Shahram Lotfi Shahin Ahmadi Parvin Kumar Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes Scientific Reports |
| title | Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes |
| title_full | Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes |
| title_fullStr | Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes |
| title_full_unstemmed | Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes |
| title_short | Quantitative structure–activity relationship modeling for predication of inhibition potencies of imatinib derivatives using SMILES attributes |
| title_sort | quantitative structure activity relationship modeling for predication of inhibition potencies of imatinib derivatives using smiles attributes |
| url | https://doi.org/10.1038/s41598-022-26279-8 |
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