Khám phá các dẫn xuất thiazole mới có hoạt tính kháng ung thư vú (MCF-7) bằng phương pháp In silico

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Tác giả: Thanh Nhan Cao, Minh Quang Nguyễn, Văn Tất Phạm

Ngôn ngữ: vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học và Công nghệ - Trường Đại học Bình Dương, 2024

Mô tả vật lý:

Bộ sưu tập: Báo, Tạp chí

ID: 399309

Thêm vào giỏ Liên kết toàn văn

Nghiên cứu tìm kiếm các dẫn xuất thiazole mới có hoạt tính kháng ung thư vú (MCF-7) bằng cách xây dựng mô hình QSAR dựa trên hồi quy tuyến tính đa biến (QSARMLR) và mạngthần kinh nhân tạo (QSARANN) trên tập dữ liệu thực nghiệm gồm 53 dẫn xuất của thiazole vớicác giá trị IC50 kết hợp với đánh giá tính giống dược và mô phỏng docking. Kết quả mô hìnhQSARMLR có tám mô tả được phát triển thành công, với giá trị thống kê của R2train = 0,875 vàQ2LOO = 0,834. Dựa trên các mô tả của mô hình QSARMLR, mô hình mạng thần kinh QSARANNvới kiến trúc I(8)-HL(9)-O(1) cũng đã được xây dựng có giá trị thống kê là R2 = 0,918, Q2test =0,934 và Q2CV = 0,916. Sử dụng phân tích miền ứng dụng và quan sát ngoại biên (AD andoutliers), các mô hình đã được sử dụng để dự đoán 120 dẫn xuất thiết kế mới dựa trên khungthiazole, và các giá trị IC50 của 10 dẫn xuất thiazole mới đã được xác định thuộc miền AD.Ngoài ra, các dẫn xuất đã được đánh giá khả năng kháng với ung thư vú dương tính với estrogenbằng cách gắn chúng vào thụ thể Polo-like kinase (PLK1) và đánh giá đặc tính dược động họccủa chúng theo quy tắc của Lipinski và Ghose. Kết quả, chúng tôi đã phát hiện ra dẫn xuấthiaxole TAZ5 có hoạt tính cao chống lại dòng tế bào ung thư vú MCF-7.The work validated the pharmacokinetic characteristics and docking approach, anddiscovered novel thiazole compounds with MCF-7 breast anti-cancer efficacy usingquantitative structure-activity relationships (QSAR) models. Using an experimental dataset of53 thiazole derivatives with IC50 values, QSAR models were developed using multivariatelinear regression (QSARMLR) and artificial neural networks (QSARANN). Eight descriptions,with statistical values of R2train = 0.875 and Q2LOO = 0.834, comprised the successfullydeveloped QSARMLR model. Based on the descriptors of the QSARMLR model, which hasstatistical values of R2 = 0.918, Q2test = 0.934, and Q2CV = 0.916, the QSARANN neural networkmodel with the architectural network of I(8)-HL(9)-O(1) has also been constructed. Using theAD and outliers analysis, the models were utilized to forecast 120 new design derivatives basedon the thiazole framework, and the IC50 values of 10 new thiazole derivatives were determined.Additionally, the derivatives were assessed for resistance to estrogen-positive breast cancer bydocking them onto the Polo-like kinases (Plk1) receptor and screening them forpharmacokinetic features in accordance with Lipinski and Ghose guidelines. Consequently, itwas discovered that the thiazole TAZ5 had promising derivative activity against the primaryMCF-7 breast cancer cell line.

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