Khám phá hợp chất flavonoid và theaflavin từ chi Camellia ở Việt Nam theo hướng ức chế Keap1-Nrf2 bằng phương pháp sàng lọc in silico
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Từ khóa:
Mô hình học máy
ức chế phức hợp Keap1-Nrf2
chi Camellia
docking phân tử
in silico
Tóm tắt
Các cây thuộc chi Chè Camellia từ lâu đã được chứng minh có khả năng chống stress oxy hóa thông qua sự dập tắt các gốc tự do. Nghiên cứu này sử dụng phương pháp sàng lọc ảo in silico tích hợp thuật toán học máy để dự đoán khả năng chống oxy hóa thông qua việc tăng cường biểu hiện Nrf2 của 5 loài thuộc chi chè Camellia bao gồm Camellia sinensis, Camellia quephongensis, Camellia oleifera, Camellia amplexicaulis và Camellia japonica. Mô hình học máy phân loại hợp chất được xây dựng dựa trên bốn thuật toán học máy bao gồm Support vector machines (SVM), Random forests (RF), Extreme gradient boosting (XGBoost) và Multilayer Perceptron (MLP). Từ mô hình phân loại có hiệu suất tối ưu, nghiên cứu đã xác định được 33 hợp chất tiềm năng. Các hợp chất được phân loại có khả năng kích hoạt Nrf2 được docking phân tử trên với thụ thể Keap1-Nrf2 (PDB ID: 2FLU). Kết quả cho thấy, có bốn hợp chất với số điểm docking tốt nhất là camellianoside (-10,4 kcal/mol), theaflavin-3-gallate (-9,9 kcal/mol), theaflavin-3'-gallate (-9,8 kcal/mol) và camelliaside B (-9,7 kcal/mol).
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Nguyễn Minh Quân, Đoàn Nguyễn Việt Hà, Nguyễn Bùi Quốc Huy, Giang Thị Kim Liên, Lê Nguyễn Thiên Hân, và Nguyễn Minh Hiền. “Khám Phá hợp chất Flavonoid Và Theaflavin từ Chi Camellia ở Việt Nam Theo hướng ức Chế Keap1-Nrf2 bằng phương pháp sàng lọc in Silico”. Tạp Chí Khoa học Và Công nghệ - Đại học Đà Nẵng, vol 22, số p.h 11A, Tháng Mười-Một 2024, tr 43-52, https://jst-ud.vn/jst-ud/article/view/9421.
