Multitarget inhibition of CDK2, EGFR, and tubulin by phenylindole derivatives: Insights from 3D-QSAR, molecular docking, and dynamics for cancer therapy.
Cancer remains one of the leading causes of death globally, presenting significant challenges to healthcare systems due to its complexity and the limitations of current therapeutic strategies. Despite advancements in anticancer drug development, monotherapies often fail to provide long-term efficacy...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0326245 |
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| Summary: | Cancer remains one of the leading causes of death globally, presenting significant challenges to healthcare systems due to its complexity and the limitations of current therapeutic strategies. Despite advancements in anticancer drug development, monotherapies often fail to provide long-term efficacy due to the emergence of drug resistance. This resistance is primarily due to the activation of compensatory pathways in cancer cells, which allows them to bypass the effects of single-target therapies. To overcome this, targeting multiple key proteins simultaneously has emerged as a promising strategy to enhance therapeutic outcomes and address resistance mechanisms. In this study, 2-Phenylindole derivatives were explored as MCF7 breast cancer cell line inhibitors using 3D-QSAR modeling to design more effective compounds. The CoMSIA/ SEHDA model demonstrated high reliability (R² = 0.967) and a strong Leave-One-Out cross-validation coefficient (Q² = 0.814), further validated by external testing (R²Pred = 0.722). Six new compounds with potent inhibitory activity were designed, and their favorable ADMET profiles were confirmed. Molecular docking studies revealed that the newly designed compounds exhibited better binding affinities (-7.2 to -9.8 kcal/mol) to key cancer-related targets (CDK2, EGFR, and Tubulin) compared to the reference drug and the most active molecule (molecule 39) in the dataset. Additionally, 100 ns molecular dynamics simulations confirmed the stability of the best-docked complexes, highlighting their potential as promising candidates for anticancer drug development. |
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| ISSN: | 1932-6203 |