Elucidate molecular mechanisms of 173 compounds for potential breast cancer therapeutics: Insights through integrating network pharmacology, molecular docking and molecular dynamics simulation

All over the world, breast cancer is one of the most common cancers in women and is identified as the prevalent cause of death. Hence, the urgency of developing novel anti-breast cancer drugs for combating this deadly disease with potential efficiency is associated with current therapeutics. To address this issue, in our present work we collected recently analyzed 173 compounds from the scientific literature as much information as possible during 2021-2024 for the first time to elucidate the underlying molecular mechanisms associated with breast cancer via comprehensive analysis that integrates network pharmacology, molecular docking, molecular dynamics, and Molecular Mechanics with Generalized Born and Surface Area solvation (MM/GBSA). Molecular properties and drug-likeness were screened for obtained compounds to probe into the mechanism of action. The compound-target network, protein-protein interaction (PPI) network, Gene Ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed with the aim of analyzing molecular mechanisms associated with breast cancer. Afterward, 12 potentially active compounds were carefully identified along with 192 common targets, including 8 pertinent core targets such as PIK3R1, PIK3CB, PIK3CA, PIK3CD, AKT1, AKT2, AKT3, and PTPN11. Molecular docking simulations revealed a robust score between AKT1-Capivasertib, PTPN11-Olaparib, PIK3R1-(1S)-2-(4-phenylmethoxyphenyl)-N-(pyridin-2-ylmethyl)cyclopropan-1-amine, PIK3CA-(1S)-2-(4-phenylmethoxyphenyl)-N-(pyridin-2-ylmethyl)cyclopropan-1-amine, PIK3CB-Capivasertib, AKT2-Ibuprofen Sodium, PIK3CD-Capivasertib and AKT3-N-(2-Hydroxyphenyl)-2-propylpentanamide complexes with strong binding interactions of 9.2353, 9.2016, 8.7742, 7.8234, 7.7083, 7.6387, 7.3778 and 6.6705, respectively. The key findings of outcome are corroborated by molecular dynamics simulation at 300K for 200ns to reinforce intermolecular mechanism between pertinent core targets and potential active compounds. In addition, overall free binding energy is calculated for eight complexes employing MM/GBSA, and the results indicate that Capivasertib has energetically favourable binding towards PIK3CD with binding free energy of -41.14 kcal/mol. Finally, the light of these results provides new insights into understanding the mechanism of action, including compounds, targets, potent biological processes, cellular components, molecular functions, and pathways involved that may represent an essential part of current breast cancer therapeutics.

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Publication Details

Journal
Chinese Journal of Analytical Chemistry
Published
2025-05-06
DOI
https://doi.org/10.1016/j.cjac.2025.100557
Citations
1
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
1.50

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article

Elucidate molecular mechanisms of 173 compounds for potential breast cancer therapeutics: Insights through integrating network pharmacology, molecular docking and molecular dynamics simulation

Min Yao, Sanjeevi Pandiyan, Li Wang, Tao Ruan et al.
1 citations
Chinese Journal of Analytical Chemistry
Computational Drug Discovery Methods
1.50
article

Elucidate molecular mechanisms of 173 compounds for potential breast cancer therapeutics: Insights through integrating network pharmacology, molecular docking and molecular dynamics simulation

Min Yao, Sanjeevi Pandiyan, Li Wang, Tao Ruan, Zhuheng Zhong
article en
1 citations

Abstract

All over the world, breast cancer is one of the most common cancers in women and is identified as the prevalent cause of death. Hence, the urgency of developing novel anti-breast cancer drugs for combating this deadly disease with potential efficiency is associated with current therapeutics. To address this issue, in our present work we collected recently analyzed 173 compounds from the scientific literature as much information as possible during 2021-2024 for the first time to elucidate the underlying molecular mechanisms associated with breast cancer via comprehensive analysis that integrates network pharmacology, molecular docking, molecular dynamics, and Molecular Mechanics with Generalized Born and Surface Area solvation (MM/GBSA). Molecular properties and drug-likeness were screened for obtained compounds to probe into the mechanism of action. The compound-target network, protein-protein interaction (PPI) network, Gene Ontology (GO) functional enrichment, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed with the aim of analyzing molecular mechanisms associated with breast cancer. Afterward, 12 potentially active compounds were carefully identified along with 192 common targets, including 8 pertinent core targets such as PIK3R1, PIK3CB, PIK3CA, PIK3CD, AKT1, AKT2, AKT3, and PTPN11. Molecular docking simulations revealed a robust score between AKT1-Capivasertib, PTPN11-Olaparib, PIK3R1-(1S)-2-(4-phenylmethoxyphenyl)-N-(pyridin-2-ylmethyl)cyclopropan-1-amine, PIK3CA-(1S)-2-(4-phenylmethoxyphenyl)-N-(pyridin-2-ylmethyl)cyclopropan-1-amine, PIK3CB-Capivasertib, AKT2-Ibuprofen Sodium, PIK3CD-Capivasertib and AKT3-N-(2-Hydroxyphenyl)-2-propylpentanamide complexes with strong binding interactions of 9.2353, 9.2016, 8.7742, 7.8234, 7.7083, 7.6387, 7.3778 and 6.6705, respectively. The key findings of outcome are corroborated by molecular dynamics simulation at 300K for 200ns to reinforce intermolecular mechanism between pertinent core targets and potential active compounds. In addition, overall free binding energy is calculated for eight complexes employing MM/GBSA, and the results indicate that Capivasertib has energetically favourable binding towards PIK3CD with binding free energy of -41.14 kcal/mol. Finally, the light of these results provides new insights into understanding the mechanism of action, including compounds, targets, potent biological processes, cellular components, molecular functions, and pathways involved that may represent an essential part of current breast cancer therapeutics.

Chinese Journal of Analytical ChemistryVol. 53(9)
Nantong University (CN)
National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China
Openalex Percentile: Top 17%
Computational Drug Discovery Methods
1.50
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