Group- based quantitative structural activity relationship analysis of B-cell Lymphoma Extra Large (BCL-XL) inhibitors

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

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Abstract

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.

Item Type:	Article (Journal)
Additional Information:	4341/41552
Uncontrolled Keywords:	2D descriptors; Bcl-XL inhibitors; G-QSAR; Multiple regression method; Simulated annealing
Subjects:	R Medicine > RS Pharmacy and materia medica
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Pharmacy > Department of Pharmaceutical Technology
Depositing User:	Dr Danjuma Abdullahi Abubakar
Date Deposited:	27 Feb 2015 18:24
Last Modified:	20 Sep 2017 17:58
URI:	http://irep.iium.edu.my/id/eprint/41552

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