Structure-based and ligand-based drug design for HER 2 receptor

Area of Science:

• Oncology
• Pharmacology
• Computational Chemistry

Background:

• Human epidermal growth factor receptor 2 (HER2) is over-expressed in many carcinomas.
• Current HER2 inhibitors have significant side effects.
• Novel therapeutic strategies are needed to target HER2-positive cancers.

Purpose of the Study:

• To design novel HER2 inhibitors using traditional Chinese medicine (TCM).
• To identify potent HER2 inhibitors with potentially reduced side effects through computational drug design.

Main Methods:

• Homology modeling was used to build the HER2 structure.
• Structure-based and ligand-based drug design approaches were employed.
• Docking, de novo evolution, and pharmacophore mapping were utilized to identify and refine candidate compounds.

Main Results:

• A pharmacophore model was developed using 32 known HER2 inhibitors.
• Key interactions, including hydrogen bonds and pi-stacking, were identified between ligands and HER2 residues (Phe731, Lys753, Asp863, Asp808).
• CLC015-5, CLC604-11, and CLC604-18 emerged as the most promising candidates, showing consistency across both computational approaches.

Conclusions:

• The study successfully identified novel potential HER2 inhibitors derived from TCM.
• The identified compounds (CLC015-5, CLC604-11, CLC604-18) warrant further investigation for their therapeutic potential in HER2-driven cancers.
• Computational drug design integrating structure- and ligand-based methods is effective for discovering new anticancer agents.