Allyl ether of mansonone G as a potential anticancer agent for colorectal cancer

Prediction and Interpretation Microglia Cytotoxicity by Machine Learning

Ameliorating microglia-mediated neuroinflammation is a crucial strategy in developing new drugs for neurodegenerative diseases. Plant compounds are an important screening target for the discovery of drugs for the treatment of neurodegenerative diseases. However, due to the spatial complexity of phytochemicals, it becomes particularly important to evaluate the effectiveness of compounds while avoiding the mixing of cytotoxic substances in the early stages of compound screening. Traditional high-throughput screening methods suffer from high cost and low efficiency. A computational model based on machine learning provides a novel avenue for cytotoxicity determination. In this study, a microglia cytotoxicity classifier was developed using a machine learning approach. First, we proposed a data splitting strategy based on the molecule murcko generic scaffold, under this condition, three machine learning approaches were coupled with three kinds of molecular representation methods to construct microglia cytotoxicity classifier, which were then compared and assessed by the predictive accuracy, balanced accuracy, F1-score, and Matthews Correlation Coefficient. Then, the recursive feature elimination integrated with support vector machine (RFE-SVC) dimension reduction method was introduced to molecular fingerprints with high dimensions to further improve the model performance. Among all the microglial cytotoxicity classifiers, the SVM coupled with ECFP4 fingerprint after feature selection (ECFP4-RFE-SVM) obtained the most accurate classification for the test set (ACC of 0.99, BA of 0.99, F1-score of 0.99, MCC of 0.97). Finally, the Shapley additive explanations (SHAP) method was used in interpreting the microglia cytotoxicity classifier and key substructure smart identified as structural alerts. Experimental results show that ECFP4-RFE-SVM have reliable classification capability for microglia cytotoxicity, and SHAP can not only provide a rational explanation for microglia cytotoxicity predictions, but also offer a guideline for subsequent molecular cytotoxicity modifications.

Therapeutic potential of ethoxy mansonone G: A comprehensive exploration of its anticancer actions in breast cancer, colorectal cancer, and non-small cell lung carcinoma

Mansonone G (MG), a 1,2-naphthoquinones with antiestrogenic, antimicrobial, and anti-adipogenic activities, is derived from the heartwood of Mansonia gagei Drumm. Ethoxy mansonone G (EMG), an essential derivative of MG, has anticancer and antioxidant agent. EMG also has antiestrogen activity and is demonstrated to lower estrogen receptor expression in endocrine-resistant cells. EMG significantly inhibits cell division, invasion, and anchorage-dependent growth in all cancer types. Through the stimulation of the tumor protein (p53) and extracellular signal-regulated kinase (ERK) signaling cascades, it also causes apoptosis. Moreover, it manifests its anti-cancerous effects in toll-like receptor pathways, c-Jun N-terminal kinase (c-JNK), and nuclear factor kappa B (NF-κB). EMG inhibits the phosphorylation of glycogen synthase kinase (GSK3), Erk, protein kinase B (Akt), and mammalian target of rapamycin (mTOR). By interfering with molecular cascades, EMG significantly reduces the metabolism of cancer cells. This paper focuses on the potential use of EMG in cancer treatment. Moreover, it states the methodology by which specific assays establish the anti-cancerous role of EMG. Breast cancer, non-small cell lung cancer, and colorectal cancer are only a few of the cancers for which EMG was shown to be effective. Through further research, EMG may be developed as a therapeutic solution to complications caused by cancer. This study presents EMG as a novel candidate for cancer therapy, offering a unique combination of pharmacological advantages and mechanistic insights that warrant further exploration and development toward addressing the complexities of cancer treatment.

Discovery of a Dual-Target Inhibitor of CDK7 and HDAC1 That Induces Apoptosis and Inhibits Migration in Colorectal Cancer

Aberrant expression or dysfunction of cyclin-dependent kinase 7(CDK7) and histone deacetylase 1 (HDAC1) are associated with the occurrence and progression of various cancers. In this study, we developed a series of dual-target inhibitors by designing and synthesizing compounds that incorporate the pharmacophores of THZ2 and SAHA. The most potent dual-target inhibitor displayed robust inhibitory activity against several types of cancer cells and demonstrated promising inhibitory effects on both CDK7 and HDAC1. After further mechanistic studies, it was discovered that this inhibitor effectively arrested HCT-116 cells at the G2 phase and induced apoptosis. Additionally, it also significantly hindered the migration of HCT-116 cells and exhibited notable anti-tumor effects. These findings offer strong support for the development of dual-target inhibitors of CDK7 and HDAC1 and provide a promising avenue for future cancer therapy.