QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors

This study presents a computational approach for designing potent compounds against breast cancer. A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer rece...

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Main Authors: Auwal Isa, Adamu Uzairu, umar Umar, Muhammad Tukur Ibrahim, Abdullahi Umar
Format: Article
Language:English
Published: Iranian Chemical Science and Technologies Association 2024-04-01
Series:Journal of Chemistry Letters
Subjects:
Online Access:https://www.jchemlett.com/article_187161_9e11dbad6e377f8bc2aaadc446f85d36.pdf
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author Auwal Isa
Adamu Uzairu
umar Umar
Muhammad Tukur Ibrahim
Abdullahi Umar
author_facet Auwal Isa
Adamu Uzairu
umar Umar
Muhammad Tukur Ibrahim
Abdullahi Umar
author_sort Auwal Isa
collection DOAJ
description This study presents a computational approach for designing potent compounds against breast cancer. A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer receptors. The model's reliability is validated with external metrics, emphasizing precision and strong relationships. Molecular docking investigations explore interactions between 2,4-diphenyl indenol [1,2-b] pyridinol derivatives and breast cancer receptors (2RMJ, 4OAR, 4RDH, 3ERT). Remarkable binding patterns are observed, insinuating at potential DNA gyrase inhibition. The compound's molecular properties and descriptors offer valuable insights into physicochemical characteristics, druglikeness, and potential pharmacological behavior. These findings contribute to drug design and development for personalized breast cancer therapy.This research integrates computational methodologies with experimental data, paving the way for effective and targeted breast cancer treatments. The study emphasizes the potential of computational analysis to enhance precision and efficacy in breast cancer treatment strategies.
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publishDate 2024-04-01
publisher Iranian Chemical Science and Technologies Association
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series Journal of Chemistry Letters
spelling doaj-art-216365e66b1c423c986367e77f27ffb82025-08-20T03:16:46ZengIranian Chemical Science and Technologies AssociationJournal of Chemistry Letters2821-01232717-18922024-04-0151445710.22034/jchemlett.2024.424800.1146187161QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptorsAuwal Isa0Adamu Uzairu1umar Umar2Muhammad Tukur Ibrahim3Abdullahi Umar4Department of Chemistry faculty of science Yobe state UniversityDepartment of Chemistry, Ahmadu Bello University, Zariachemistry department, faculty of science. yobe state universityDepartment of Chemistry Ahamadu, Bello University, P.M.B.1044, Zaria, NigeriaDepartment of chemistry, Faculty of physical sciences, Ahmadu Bello University, Zaria, Kaduna, NigeriaThis study presents a computational approach for designing potent compounds against breast cancer. A robust quantitative structure-activity relationship (QSAR) model, developed using genetic algorithms and multilinear regression analysis, predicts chemical activity (pGI50) against breast cancer receptors. The model's reliability is validated with external metrics, emphasizing precision and strong relationships. Molecular docking investigations explore interactions between 2,4-diphenyl indenol [1,2-b] pyridinol derivatives and breast cancer receptors (2RMJ, 4OAR, 4RDH, 3ERT). Remarkable binding patterns are observed, insinuating at potential DNA gyrase inhibition. The compound's molecular properties and descriptors offer valuable insights into physicochemical characteristics, druglikeness, and potential pharmacological behavior. These findings contribute to drug design and development for personalized breast cancer therapy.This research integrates computational methodologies with experimental data, paving the way for effective and targeted breast cancer treatments. The study emphasizes the potential of computational analysis to enhance precision and efficacy in breast cancer treatment strategies.https://www.jchemlett.com/article_187161_9e11dbad6e377f8bc2aaadc446f85d36.pdfbreast cancer (bc)protein data bankmolecular descriptorlee-yang-parr hybrid (b3lyp)concordant correlation coefficient (ccc)
spellingShingle Auwal Isa
Adamu Uzairu
umar Umar
Muhammad Tukur Ibrahim
Abdullahi Umar
QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
Journal of Chemistry Letters
breast cancer (bc)
protein data bank
molecular descriptor
lee-yang-parr hybrid (b3lyp)
concordant correlation coefficient (ccc)
title QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
title_full QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
title_fullStr QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
title_full_unstemmed QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
title_short QSAR, docking and pharmacokinetic studies of 2,4-diphenyl indenol [1,2-B] pyridinol derivatives targeting breast cancer receptors
title_sort qsar docking and pharmacokinetic studies of 2 4 diphenyl indenol 1 2 b pyridinol derivatives targeting breast cancer receptors
topic breast cancer (bc)
protein data bank
molecular descriptor
lee-yang-parr hybrid (b3lyp)
concordant correlation coefficient (ccc)
url https://www.jchemlett.com/article_187161_9e11dbad6e377f8bc2aaadc446f85d36.pdf
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