Sep 2026· Molecules· Vol 31, pp. 3478· 37 references
Biological Activity of Diterpenoids and Biflavonoids
Abstract
Cephalotaxine (1) is a parent compound within the cephalotaxine alkaloids class mainly derived from Cephalotaxus plants. In this study, by coupling 1 with cinnamic acid, 17 novel cephalotaxine-cinnamic acid derivatives (S1–S17) were designed and synthesized to enhance their anti-tumor efficacy. Among them, S10 showed the strongest cytotoxic activity against Huh7 cells, with the IC50 values of 9.3 and 5.9 μM after 24 h and 48 h, respectively, which were 21 and 32 times more potent than those of 1. In addition, compared with those against AML-12 cells, the proliferation inhibition rates of S10 against Huh7 cells were 5.0-fold lower, indicating a certain therapeutic window. Network pharmacology screening results indicate that S10 may exert regulatory effects closely related to cell migration and apoptosis through pathways such as PI3K/AKT. Molecular docking showed that S10 could effectively bind to the key targets PI3K and AKT. And the Western blot experiment results confirm that S10 could downregulate the expression of p-PI3K and p-AKT at the protein level while keeping total PI3K and AKT unchanged. Notably, S10 may regulate liver cancer cells by inhibiting the PI3K/AKT signaling pathway. Mechanistically, S10 induces S cycle arrest, reduces mitochondrial membrane potential, induces apoptosis, and inhibits migration and invasion. Overall, we reported S10 as a promising lead compound for the treatment of liver cancer.
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
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It is demonstrated that linker-free PROTACs can outperform traditional designs, marking a paradigm shift in PROTAC development for targeted protein degradation.
Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.