Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment

The present research was centered on the development of a predictive model aimed at assessing the responses of prostate tumors to a range of compounds within the scope of the pIC50 project. Our approach involved the utilization of a quantitative structure-activity relationship (QSAR) methodology, in...

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Main Authors: Auwal Salisu Isa, Adamu Uzairu, Umar Mele Umar, Muhammad Tukur Ibrahim, David Ebuka Arthur, Samuel Ndaghiya Adawara
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-09-01
Series:Biomedical Analysis
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Online Access:http://www.sciencedirect.com/science/article/pii/S2950435X24000301
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author Auwal Salisu Isa
Adamu Uzairu
Umar Mele Umar
Muhammad Tukur Ibrahim
David Ebuka Arthur
Samuel Ndaghiya Adawara
author_facet Auwal Salisu Isa
Adamu Uzairu
Umar Mele Umar
Muhammad Tukur Ibrahim
David Ebuka Arthur
Samuel Ndaghiya Adawara
author_sort Auwal Salisu Isa
collection DOAJ
description The present research was centered on the development of a predictive model aimed at assessing the responses of prostate tumors to a range of compounds within the scope of the pIC50 project. Our approach involved the utilization of a quantitative structure-activity relationship (QSAR) methodology, incorporating a genetic algorithm (GA) and multiple linear regression analyses (MLRA) applied to a dataset comprising 128 derivatives. The resultant model demonstrated a robust predictive capacity, supported by Remarkable internal and external validation metrics (R² = 0.9143 for internal consistency and R²ext. = 0.9523 for external validation), thus indicating its reliability in prognosis of tumor responses. Additionally, molecular docking simulations yielded valuable insights into the interactions between the ligands and target proteins, highlighting the significance of specific amino acid residues in the binding mechanism. These interactions were characterized by hydrogen bonds, halogen bonds, and pi-cation interactions, pointing to a substantial binding affinity with a score of −10.9 kJ/mol. The comprehensive molecular understanding obtained, including the critical role of ligand functional groups in determining interaction types, pointing out the utility of the model in identifying potential therapeutic agents. Furthermore, the study highlighted the modulation of the androgen receptor as an essential target in the treatment of prostate cancer. Molecular docking highlighted important interactions that can inform the design of novel anti-prostate cancer agents. Through the application of GA-MLR techniques, the study not only confirmed the efficacy of the predictive model in understanding prostate cancer responses but also showcased the potential of QSAR modeling in advancing prostate cancer research. The outcomes furnish a solid basis for further exploration of therapeutic compounds, emphasizing the intricate interplay between molecular structure and biological activity in the domain of drug development.
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spelling doaj-art-aa5eab4a426a48839c6072ee110496842025-08-20T02:51:40ZengKeAi Communications Co., Ltd.Biomedical Analysis2950-435X2024-09-011324026910.1016/j.bioana.2024.09.001Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatmentAuwal Salisu Isa0Adamu Uzairu1Umar Mele Umar2Muhammad Tukur Ibrahim3David Ebuka Arthur4Samuel Ndaghiya Adawara5Department of Chemistry, Faculty Science, Yobe State University, Damaturu, Yobe State P.M.B 1222, Nigeria; Corresponding author.Department of Chemistry, Faculty of Physical Science, Ahmadu Bello University, Zaria, NigeriaDepartment of Chemistry, Faculty Science, Yobe State University, Damaturu, Yobe State P.M.B 1222, NigeriaDepartment of Chemistry, Faculty of Physical Science, Ahmadu Bello University, Zaria, NigeriaDepartment of chemistry, Faculty of science university of Maiduguri, Borno State, NigeriaDepartment of chemistry, Faculty of science university of Maiduguri, Borno State, NigeriaThe present research was centered on the development of a predictive model aimed at assessing the responses of prostate tumors to a range of compounds within the scope of the pIC50 project. Our approach involved the utilization of a quantitative structure-activity relationship (QSAR) methodology, incorporating a genetic algorithm (GA) and multiple linear regression analyses (MLRA) applied to a dataset comprising 128 derivatives. The resultant model demonstrated a robust predictive capacity, supported by Remarkable internal and external validation metrics (R² = 0.9143 for internal consistency and R²ext. = 0.9523 for external validation), thus indicating its reliability in prognosis of tumor responses. Additionally, molecular docking simulations yielded valuable insights into the interactions between the ligands and target proteins, highlighting the significance of specific amino acid residues in the binding mechanism. These interactions were characterized by hydrogen bonds, halogen bonds, and pi-cation interactions, pointing to a substantial binding affinity with a score of −10.9 kJ/mol. The comprehensive molecular understanding obtained, including the critical role of ligand functional groups in determining interaction types, pointing out the utility of the model in identifying potential therapeutic agents. Furthermore, the study highlighted the modulation of the androgen receptor as an essential target in the treatment of prostate cancer. Molecular docking highlighted important interactions that can inform the design of novel anti-prostate cancer agents. Through the application of GA-MLR techniques, the study not only confirmed the efficacy of the predictive model in understanding prostate cancer responses but also showcased the potential of QSAR modeling in advancing prostate cancer research. The outcomes furnish a solid basis for further exploration of therapeutic compounds, emphasizing the intricate interplay between molecular structure and biological activity in the domain of drug development.http://www.sciencedirect.com/science/article/pii/S2950435X24000301QSARDocking AnalysisADMETProstate cancerDUA145
spellingShingle Auwal Salisu Isa
Adamu Uzairu
Umar Mele Umar
Muhammad Tukur Ibrahim
David Ebuka Arthur
Samuel Ndaghiya Adawara
Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
Biomedical Analysis
QSAR
Docking Analysis
ADMET
Prostate cancer
DUA145
title Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
title_full Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
title_fullStr Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
title_full_unstemmed Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
title_short Halogenated 2,4-diphenyl indeno[1,2-B]pyridinol derivatives as potential inhibitors of the androgen receptor (PDB ID: 58TE): A study of QSAR modeling, molecular docking, and pharmacokinetics for prostate cancer treatment
title_sort halogenated 2 4 diphenyl indeno 1 2 b pyridinol derivatives as potential inhibitors of the androgen receptor pdb id 58te a study of qsar modeling molecular docking and pharmacokinetics for prostate cancer treatment
topic QSAR
Docking Analysis
ADMET
Prostate cancer
DUA145
url http://www.sciencedirect.com/science/article/pii/S2950435X24000301
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