Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors
B-cell Lymphoma Extra Large (Bcl-xL) belongs to B-cell Lymphoma two (Bcl-2) family and owing to its anti-apoptotic role in many cancers, is proven to be an attractive target for anti-cancer therapy. Different classes of potent anti-Bcl-xL small molecules inhibitors have been discovered, and both t...
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International Journal of Pharmacy and Pharmaceutical Science
2014
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iium-415522017-09-20T09:58:07Z http://irep.iium.edu.my/41552/ Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors Abdul Samat, Nadia Hanis Mohammed Abdulkader, Abdul Rahman Mohamed, Farahidah Abdullahi, Abubakar Danjuma RS Pharmacy and materia medica B-cell Lymphoma Extra Large (Bcl-xL) belongs to B-cell Lymphoma two (Bcl-2) family and owing to its anti-apoptotic role in many cancers, is proven to be an attractive target for anti-cancer therapy. Different classes of potent anti-Bcl-xL small molecules inhibitors have been discovered, and both three-dimensional (3D) and two-dimensional (2D) Quantitative Structural Activity Relationship (QSAR) approaches have been used to study and predict the biological activities of new inhibitors prior to their synthesis. Objectives: This study was aimed to generate new candidate small inhibitory molecules against Bcl-xL by using G-QSAR analysis of known Bcl-xL inhibitors. Methods: In the present study, we used group-based QSAR (G-QSAR)—a novel fragment-based method—to develop QSAR models from known BclxL inhibitors. A set of Bcl-xL inhibitors adopted from extant literature was fragmented into three common fragments, and a pool of 214 descriptors was calculated for each one. Results: Two models were obtained by using different combination of variable selection and model building method; stepwise-multiple linear regression (STP-MLR) and simulated annealing-multiple linear regression (SA-MLR). STP-MLR was found to be the best mode, with r2 = 0.80, q2 = 0.70 and predictive r2 = 0.87. Conclusion: The G-QSAR results indicate that the generated models are statistically significant and can be used for design and generation of new potent inhibitors. International Journal of Pharmacy and Pharmaceutical Science 2014 Article PeerReviewed application/pdf en http://irep.iium.edu.my/41552/1/ijpps_nadia_gp_based_qsar_bcl.pdf application/pdf en http://irep.iium.edu.my/41552/4/41552_Group-%20based%20quantitative_scopus.pdf Abdul Samat, Nadia Hanis and Mohammed Abdulkader, Abdul Rahman and Mohamed, Farahidah and Abdullahi, Abubakar Danjuma (2014) Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors. International Journal of Pharmacy and Pharmaceutical Sciences, 6 (5). pp. 284-290. ISSN 0975-1491 http://www.ijppsjournal.com/ |
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RS Pharmacy and materia medica Abdul Samat, Nadia Hanis Mohammed Abdulkader, Abdul Rahman Mohamed, Farahidah Abdullahi, Abubakar Danjuma Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
description |
B-cell Lymphoma Extra Large (Bcl-xL) belongs to B-cell Lymphoma two (Bcl-2) family and owing to its anti-apoptotic role in many cancers, is
proven to be an attractive target for anti-cancer therapy. Different classes of potent anti-Bcl-xL small molecules inhibitors have been discovered,
and both three-dimensional (3D) and two-dimensional (2D) Quantitative Structural Activity Relationship (QSAR) approaches have been used to
study and predict the biological activities of new inhibitors prior to their synthesis.
Objectives: This study was aimed to generate new candidate small inhibitory molecules against Bcl-xL by using G-QSAR analysis of known Bcl-xL inhibitors.
Methods: In the present study, we used group-based QSAR (G-QSAR)—a novel fragment-based method—to develop QSAR models from known BclxL
inhibitors. A set of Bcl-xL inhibitors adopted from extant literature was fragmented into three common fragments, and a pool of 214 descriptors
was calculated for each one.
Results: Two models were obtained by using different combination of variable selection and model building method; stepwise-multiple linear
regression (STP-MLR) and simulated annealing-multiple linear regression (SA-MLR). STP-MLR was found to be the best mode, with r2 = 0.80, q2 =
0.70 and predictive r2 = 0.87.
Conclusion: The G-QSAR results indicate that the generated models are statistically significant and can be used for design and generation of new
potent inhibitors. |
format |
Article |
author |
Abdul Samat, Nadia Hanis Mohammed Abdulkader, Abdul Rahman Mohamed, Farahidah Abdullahi, Abubakar Danjuma |
author_facet |
Abdul Samat, Nadia Hanis Mohammed Abdulkader, Abdul Rahman Mohamed, Farahidah Abdullahi, Abubakar Danjuma |
author_sort |
Abdul Samat, Nadia Hanis |
title |
Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
title_short |
Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
title_full |
Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
title_fullStr |
Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
title_full_unstemmed |
Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors |
title_sort |
group- based quantitative structural activity relationship analysis of b-cell lymphoma extra large (bcl-xl) inhibitors |
publisher |
International Journal of Pharmacy and Pharmaceutical Science |
publishDate |
2014 |
url |
http://irep.iium.edu.my/41552/ http://irep.iium.edu.my/41552/ http://irep.iium.edu.my/41552/1/ijpps_nadia_gp_based_qsar_bcl.pdf http://irep.iium.edu.my/41552/4/41552_Group-%20based%20quantitative_scopus.pdf |
first_indexed |
2023-09-18T20:59:29Z |
last_indexed |
2023-09-18T20:59:29Z |
_version_ |
1777410527408947200 |