1403/02/07
مجید تفریحی

مجید تفریحی

مرتبه علمی: استادیار
ارکید:
تحصیلات: دکترای تخصصی
اسکاپوس:
دانشکده: دانشکده علوم پایه
نشانی:
تلفن: 01135305252

مشخصات پژوهش

عنوان
Structure based pharmacophore modeling, virtual screening and molecular docking approaches for identification of natural anti-cancer metastasis agents targeting Wnt/β-catenin pathway
نوع پژوهش
Presentation
کلیدواژه‌ها
β-catenin inhibitors; Cancer metastasis; molecular docking; pharmacophore modeling
سال
2022
پژوهشگران Majid Tafrihi ، Neda Vaghefinejad

چکیده

Cancer metastasis is a multi-stage process in which a cancer cell spreads from the primary site of the lesion, passes through the circulatory system, and establishes a secondary tumor at a new nonadjacent organ. Dietary phytochemicals (DPs) modulate numerous biological events including epigenetic changes and signaling transduction pathways such as Wnt/β-catenin. Some of these compounds which stabilize cell-cell adhesions are controversial topics that change the expression of a variety of Wnt target genes. So they may induce cell-cycle arrest, apoptosis, and/or inhibition of Epithelial-Mesenchymal Transition (EMT) and metastasis. Natural molecules that target the Wnt/β-catenin pathway include flavonoids, polyphenols, terpenes and terpenoids, secosteroids, and alkaloids. In this study, we aimed to discover novel potent WNT/β-catenin pathway inhibitors through β-catenin (PDB ID: 1JDH) structure-based virtual screening and pharmacophore modeling. 28 bioactive molecules were selected from different plants, after which we performed analyzes such as molecular docking, pharmacophore modeling, and Lipinski's Rule of Five (RO5) filter. The Camptothecin molecule had the best ligand-based pharmacophore model and docking energy. This model was applied to screen Pubchem molecular library with more than 9.3 million compounds for the novel β-catenin inhibitor. The hits were subsequently subjected to molecular docking after being filtered by Lipinski’s rules. After screening the molecular library through molecular docking, pharmacophore modeling, and Lipinski's Rule of Five (RO5) filter, we proposed eight compounds out of 539 structurally representative top hits as the most potent inhibitors (Compound CID: 11317647; 102335601; 137313625; 129670516; 57244149; 90680097; 90680098; 57016104). Finally, the novel inhibitors proposed in this study need further consideration to uncovering cancer treatment and with the generated pharmacophore model, more potent β-catenin inhibitors can be ea