Bioinformatics and computational studies of marine natural products in identifying novel VEGFR-2 inhibitors for breast cancer treatment
Angiogenesis, a hallmark feature of cancer, is the process through which new blood vessels are formed from the preexisting vessels around the cancerous tissue. Growing cancer cells rely on these newly formed blood vessels to receive essential nutrients and oxygen. This process occurs when membrane r...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Results in Chemistry |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211715625004904 |
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| Summary: | Angiogenesis, a hallmark feature of cancer, is the process through which new blood vessels are formed from the preexisting vessels around the cancerous tissue. Growing cancer cells rely on these newly formed blood vessels to receive essential nutrients and oxygen. This process occurs when membrane receptor VEGFR (VEGF receptor) is stimulated by its ligand (VEGF) Vascular Endothelial Growth Factor. Among the VEGFR family, VEGFR-2 receptor plays a pivotal role in promoting angiogenesis. Consequently, inhibiting the VEGFR-2 receptor will retard the process of angiogenesis and thus can be regarded as a new therapeutic target to treat several types of cancer including breast cancer. Therefore, the purpose of this work was to find novel natural inhibitors against VEGFR-2 receptor. To achieve this, High-Throughput Virtual Screening (HTVS) were employed to computationally screen the Comprehensive Marine Natural Products Database (CMNPD) consisting of 31,561 marine natural products targeting the VEGFR-2 receptor. Molecular docking calculations and Molecular Dynamics (MD) simulations were employed for 100 ns. Furthermore, analyses like Molecular Mechanics/Generalized Born Surface Area (MM/GBSA), Principal Component Analysis (PCA), Free Energy Landscape (FEL) and Density Functional Theory (DFT) analyses were also performed to evaluate binding energies and stability of top scoring inhibitors against the VEGFR-2. The results identified three promising compounds, namely Phenylnannolone C (CMNPD18650), Coibacin A (CMNPD22292), and Phenylnannolone A (CMNPD18648) with binding affinities ranging from −9.0 kcal/mol to −9.7 kcal/mol. These compounds showed promising binding score, along with excellent interactions in terms of binding residues, active site compatibility, and bond distances against the VEGFR-2. In addition, all three compounds were shown to target VEGFR-2 in a manner similar to Sorafenib, an approved anti-angiogenesis drug. These results also highlight the use of a computational workflow in drug discovery and give cause for belief that natural compounds can win the battle against resistant breast cancer. |
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| ISSN: | 2211-7156 |