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dc.contributor.authorAbdullahi, Sagiru Hamza-
dc.contributor.authorUzairu, Adamu-
dc.contributor.authorShallangwa, Gideon Adamu-
dc.contributor.authordkk.-
dc.date.accessioned2024-11-09T06:14:40Z-
dc.date.available2024-11-09T06:14:40Z-
dc.date.issued2023-
dc.identifier.issn1658-3612-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/7664-
dc.description.abstractObjectives: Breast tumor is ranked as the most common tumor type identified among women globally with over 1.7 million cases annually, representing 11.9% of the total number of cancer cases. Approved anti-breast tumor drugs exhibit several side effects and some patients develop resistance during the early treatment stage. This study aimed to use an in-silico approach to identify and design potential therapeutic agents. Methods: Robust 3D-QSAR models were developed using quinazoline-4(3H)-one analogs as EGFR inhibitors. The best model was then selected based on statistical parameters and was subsequently used to design more potent therapeutic agents. Molecular docking simulation was executed using the data set and the designed compounds to identify lead compounds which were further screened by pharmacokinetic profiling by applying SwissADME and pkCSM software. Results: Internal validations of the best CoMFA and CoMSIA models (R2 ¼ 0.855 and 0.895; Q2 ¼ 0.570 and 0.599) passed the threshold values for the establishment of a consistent QSAR model. The constructed models were further validated externally using six compounds as a test set, thus revealing a satisfactory predicted correlation coefficient (R2 pred ¼ 0.657 and 0.681). The CoMSIA_ SHE models with the best statistical parameters were further subjected to applicability domain checks and only three influentials were detected. These were then utilized to design five novel compounds with activities ranging from 5.62 to 6.03. Molecular docking studies confirmed that compounds 20 to 26, with docking scores ranging from 163.729 to 169.796, represented lead compounds with higher docking scores compared to Gefitinib ( 127.495). Furthermore, the designed compounds exhibited better docking scores ranging from 171.379 to 179.138. Conclusions: Pharmacological studies identified compounds 20, 24 26 and the designed compounds 2, 3, 5 as feasible drug candidates. However, these theoretical findings should now be validated experimentally.en_US
dc.language.isoen_USen_US
dc.publisherJournal of Taibah University Medical Sciencesen_US
dc.relation.ispartofseriesOriginal Article;1018-1029-
dc.subject3D-QSARen_US
dc.subjectADMETen_US
dc.subjectBreast canceren_US
dc.subjectLipinski’s ruleen_US
dc.subjectMolecular dockingen_US
dc.subjectQuinazolin-4(3H)-oneen_US
dc.titlePharmacokinetic profiling of quinazoline-4(3H)-one analogs as EGFR inhibitors: 3D-QSAR modeling, molecular docking studies and the design of therapeutic agentsen_US
dc.typeArticleen_US
Appears in Collections:Vol 18 No 5 (2023)

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