The Wnt/β-catenin signaling pathway typically shows aberrant activation in various cancer cells, especially colorectal cancer cells. This signaling pathway regulates the expression of a variety of tumor-related proteins, including c-myc and cyclin D1, and plays essential roles in tumorigenesis and in the development of many cancers. Small molecules that block the interactions between β-catenin and Tcf4, a downstream stage of activation of the Wnt/β-catenin signaling pathway, could efficiently cut off this signal transduction and thereby act as a novel class of anticancer drugs. This paper reviews the currently reported inhibitors that target β-catenin/Tcf4 interactions, focusing on the discovery approaches taken in the design of these inhibitors and their bioactivities. A brief perspective is then shared on the future discovery and development of this class of inhibitors.Impact statement: This mini-review summarized the current knowledge of inhibitors of interactions of beta-catenin/Tcf4 published to date according to their discovery approaches, and discussed their in vitro and in vivo activities, selectivities, and pharmacokinetic properties. Several reviews presently available now in this field describe modulators of the Wnt/beta-catenin pathway, but are generally focused on the bioactivities of these inhibitors. By contrast, this review focused on the drug discovery approaches taken in identifying these types of inhibitors and provided our perspective on further strategies for future drug discoveries. This review also integrated many recently published and important works on highly selective inhibitors as well as rational drug design. We believe that the findings and strategies summarized in this review have broad implications and will be of interest throughout the biochemical and pharmaceutical research community.

Cannabidiol (CBD), a non-psychoactive ingredient extracted from the hemp plant, has shown therapeutic effects in a variety of diseases, including anxiety, nervous system disorders, inflammation, and tumors. CBD can exert its antitumor effect by regulating the cell cycle, inducing tumor cell apoptosis and autophagy, and inhibiting tumor cell invasion, migration, and angiogenesis. This article reviews the proposed antitumor mechanisms of CBD, aiming to provide references for the clinical treatment of tumor diseases and the rational use of CBD.

Radiation therapy is an important treatment choice for unresectable advanced human lung cancers, and a critical adjuvant treatment for surgery. However, radiation as a lung cancer treatment remains far from satisfactory due to problems associated with radiation resistance in cancer cells and severe cytotoxicity to non-cancer cells, which arise at doses typically administered to patients. We have recently identified a promising novel inhibitor of β-catenin/Tcf4 interaction, named BC-23 (C₂₁H₁₄ClN₃O₄S), which acts as a potent cell death enhancer when used in combination with radiation. Sequential exposure of human p53-null non-small cell lung cancer (NSCLC) H1299 cells to low doses of x-ray radiation, followed 1 hour later by administration of minimally cytotoxic concentrations of BC-23, resulted in a highly synergistic induction of clonogenic cell death (combination index <1.0). Co-treatment with BC-23 at low concentrations effectively inhibits Wnt/β-catenin signaling and down-regulates c-Myc and cyclin D1 expression. S phase arrest and ROS generation are also involved in the enhancement of radiation effectiveness mediated by BC-23. BC-23 therefore represents a promising new class of radiation enhancer.

The COVID-19 pandemic caused by SARS-CoV-2 remains a global public health threat and has prompted the development of antiviral therapies. Artificial intelligence may be one of the strategies to facilitate drug development for emerging and re-emerging diseases. The main protease (M^pro) of SARS-CoV-2 is an attractive drug target due to its essential role in the virus life cycle and high conservation among SARS-CoVs. In this study, we used a data augmentation method to boost transfer learning model performance in screening for potential inhibitors of SARS-CoV-2 M^pro. This method appeared to outperform graph convolution neural network, random forest and Chemprop on an external test set. The fine-tuned model was used to screen for a natural compound library and a de novo generated compound library. By combination with other in silico analysis methods, a total of 27 compounds were selected for experimental validation of anti-M^pro activities. Among all the selected hits, two compounds (gyssypol acetic acid and hyperoside) displayed inhibitory effects against M^pro with IC50 values of 67.6 μM and 235.8 μM, respectively. The results obtained in this study may suggest an effective strategy of discovering potential therapeutic leads for SARS-CoV-2 and other coronaviruses.