Telatinib

Endometrial carcinoma (EC) is a type of cancer that originates in the lining of the uterus, known as the endometrium. It is associated with various treatment options such as surgery, radiation therapy, chemotherapy, and hormone therapy, each presenting unique challenges and limitations. Beta-catenin, a protein involved in the development and progression of several cancers, including EC, plays a crucial role. Abnormal beta-catenin signaling is often linked to the emergence of specific EC subtypes, affecting tumor growth and invasion.

The study's objective is to identify compounds targeting the beta-catenin protein for treating endometrial cancer (EC) using in silico drug design. Our approach includes molecular docking to evaluate binding affinities, ADME profiling for pharmacokinetic properties, toxicity assessments, and molecular dynamics simulations to assess compound stability and interactions.

Approximately one thousand anti-cancer phytochemicals were sourced from PubChem and subjected to molecular docking simulations against the beta-catenin protein. The compounds were evaluated based on their binding affinities, with the top five selected for further analysis. These five molecules underwent toxicity and ADME profiling. The Prediction of Activity Spectra for Substances (PASS) tool was used to identify compounds targeting CTNNB1. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were employed to establish quantitative structure-activity relationship (QSAR) models for the five CTNNB1 antagonist molecules.

The selected five compounds, namely Pazopanib, Binimetinib, Telatinib, 4-(2,3-Dihydrobenzo[ b][1,4]dioxin-6-yl)-3-((5-nitrothiazol-2-yl)thio)-1H-1,2,4-triazol-5(4H)-one, and Ribavirin, demonstrated efficacy against CTNN1. MD simulations of the docked complexes confirmed the stability of these drugs in binding to the target protein. All five molecules showed promising safety and effectiveness profiles according to their ADME and toxicity evaluations.

Through a comprehensive screening process employing in silico drug design methods, this study successfully identified five potential human anticancer drug candidates targeting the beta-catenin protein. These findings offer a foundation for further experimental validation and development towards the treatment of EC.

The recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlighted a critical need to discover more effective antivirals. While therapeutics for SARS-CoV-2 exist, its nonstructural protein 13 (Nsp13) remains a clinically untapped target. Nsp13 is a helicase responsible for unwinding double-stranded RNA during viral replication and is essential for propagation. Like other helicases, Nsp13 has two active sites: a nucleotide binding site that hydrolyzes nucleoside triphosphates (NTPs) and a nucleic acid binding channel that unwinds double-stranded RNA or DNA. Targeting viral helicases with small molecules, as well as the identification of ligand binding pockets, have been ongoing challenges, partly due to the flexible nature of these proteins. Here, we use a virtual screen to identify ligands of Nsp13 from a collection of clinically used drugs. We find that a known ion channel inhibitor, IOWH-032, inhibits the dual ATPase and helicase activities of SARS-CoV-2 Nsp13 at low micromolar concentrations. Kinetic and binding assays, along with computational and mutational analyses, indicate that IOWH-032 interacts with the RNA binding interface, leading to displacement of nucleic acid substrate, but not bound ATP. Evaluation of IOWH-032 with microbial helicases from other superfamilies reveals that it is selective for coronavirus Nsp13. Furthermore, it remains active against mutants representative of observed SARS-CoV-2 variants. Overall, this work provides a new inhibitor for Nsp13 and provides a rationale for a recent observation that IOWH-032 lowers SARS-CoV-2 viral loads in human cells, setting the stage for the discovery of other potent viral helicase modulators.