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This chapter employs computer simulation methods to systematically explore the anticancer activity and mechanisms of leaf extracts. High-potential active components are screened using the TCMSP and PubChem databases, and their target sites are predicted using SwissTargetPrediction, SEA, and STITCH. Cancer-related targets are obtained by integrating the Cancer Gene Census, KEGG Pathway, and STRING databases, and a component-target-disease network and protein-protein interaction (PPI) network are constructed. The network centrality of key targets is analyzed using Cytoscape and MCODE plugins. GO and KEGG enrichment analysis reveals the biological processes and cancer-related signaling pathways in which the key targets are involved. Finally, molecular docking validation is performed using AutoDock and Schrödinger, and component-target pairs with binding energies ≤ −8.0 kcal/mol are screened to analyze their binding modes (e.g., hydrogen bonds, hydrophobic interactions). The chapter proposes potential anticancer mechanisms of leaf extracts, providing theoretical foundations and data support for subsequent experimental validation and the development of natural product-based anticancer drugs.

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Determination of Anticancer Properties of Leaf Extract: An In Silico Approach

  • 章节

  • 发表日期：

    2026年

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  • Zhenzhen Si,
  • Ning Xu,
  • Peng Chen

摘要

This chapter employs computer simulation methods to systematically explore the anticancer activity and mechanisms of leaf extracts. High-potential active components are screened using the TCMSP and PubChem databases, and their target sites are predicted using SwissTargetPrediction, SEA, and STITCH. Cancer-related targets are obtained by integrating the Cancer Gene Census, KEGG Pathway, and STRING databases, and a component-target-disease network and protein-protein interaction (PPI) network are constructed. The network centrality of key targets is analyzed using Cytoscape and MCODE plugins. GO and KEGG enrichment analysis reveals the biological processes and cancer-related signaling pathways in which the key targets are involved. Finally, molecular docking validation is performed using AutoDock and Schrödinger, and component-target pairs with binding energies ≤ −8.0 kcal/mol are screened to analyze their binding modes (e.g., hydrogen bonds, hydrophobic interactions). The chapter proposes potential anticancer mechanisms of leaf extracts, providing theoretical foundations and data support for subsequent experimental validation and the development of natural product-based anticancer drugs.