Identificação in silico de potenciais inibidores da via wnt canônica em adenocarcinoma mamário humano

Abstract

Breast cancer is the leading worldwide cause of cancer-related deaths in women, being the triple-negative breast cancer type the one presenting the worst prognosis. The prospection and development of new substances with antitumoral potential is of great importance for the treatment of this disease. The objective of this work was to identify a commercial drug or ligand, through bioinformatics analysis, that could potentially bind to the FZD7 transmembrane protein and inactivate the Wnt signaling pathway in triple-negative breast cancer cells (TNBC). We aimed to computationally model the FZD7, Wnt3 and Wnt3a proteins, make them available in protein model databases, and conduct docking analysis to assess the binding free energy between FZD7 and the selected commercially available ligands. To select the proteins to be studied and modeled, a search for overexpressed TNBC proteins was done within the GEO database. The Wnt3 and Wnt3a proteins were modeled by homology modeling, using the Modeller software, and the FZD7 protein was modeled by homology modeling and ab initio modeling, using the I-TASSER online tool. Ramachandran plots were generated for the constructed models and RMSD analysis were conducted to assess their stereochemical quality. The ligands were selected based on their similarity to the palmitoleic acid and were gathered from the ZINC database. Docking analysis were conducted, using the Autodock Vina software, to assess the binding energy between the FZD7's cysteine-rich domain (CRD) and the selected ligands. The best generated models for Wnt3 and Wnt3a were deposited in the PMDB. A total of 30 commercially available ligands were found in the ZINC database. The docking results show that the ligands zinc08221009, zinc13546050, zinc05260769, zinc04529321, and zinc05972969 are good candidates for novel drug development. To the best of our knowledge, there are no available quality models of the Wnt3 and Wnt3a proteins in public databases. The created models and conducted analysis by the present work will most certainly help in future researches on the Wnt signaling pathway and its components.