Anti-apoptotic protein Mcl-1 plays an important role in protecting cell from death in acute myeloid leukemia (AML). The apoptosis blocking activity of Mcl-1 is inhibited by BH3-only protein Noxa. We found that dihydroartemisinin (DHA) and its derivative X-11 are potent apoptosis inducers in AML cells and act through a Noxa-mediate pathway; X-11 is four-fold more active than DHA. DHA and X-11-induced apoptosis is associated with induction of Noxa; apoptosis is blocked by silencing Noxa. DHA and X-11 induce Noxa expression by upregulating the transcription factor FOXO3a in a reactive oxygen species-mediated pathway. Interfering with the integrity of the endoperoxide moiety of DHA and X-11, as well as chelating intracellular iron with deferoxamine, diminish apoptosis and Noxa induction. AML cells expressing Bcl-xL, or with overexpression of Bcl-2, have decreased sensitivity to DHA and X-11-induced apoptosis which could be overcome by addition of Bcl-2/Bcl-xL inhibitor ABT-737. DHA and X-11 represent a new group of AML cells-apoptosis inducing compounds which work through Noxa up-regulation utilizing the specific endoperoxide moiety and intracellular iron.

BACKGROUND Herbicides, as efficient weed control measures, play a crucial role in ensuring food security. The emergence of herbicide‐resistant weeds has negatively affected food security and promoted the demand for new and improved herbicides. The balance between bioavailability and the potency of a compound is one of the most pressing challenges in the development of novel ideal herbicides. Herbicide‐likeness analysis is crucial for the evaluation of this balance and thus may help to address this issue. Many herbicide‐likeness analysis methods have been developed to screen potential novel lead compounds. However, there remains a lack of user‐friendly and integrated tools to comprehensively evaluate herbicide‐likeness. RESULTS Herbicide‐likeness of compounds was assessed through integrated analysis incorporating the physicochemical properties of commercial herbicides, a qualitative rule, and three quantitative scoring functions developed for evaluating herbicide‐likeness. HerbiPAD (http://agroda.gzu.edu.cn:9999/ccb/database/HerbiPAD/) is a free web platform integrated with the collected database and scoring model. This platform contains 542 approved herbicides and > 29 000 physicochemical descriptors. The accuracy of HerbiPAD in distinguishing known herbicides from nonherbicides was 84.2%. In the case study, HerbiPAD evaluated 60 new compounds from seven different herbicide targets, and the accuracy of predicting better bioavailability was 83.3%. CONCLUSIONS HerbiPAD was designed to quickly and efficiently evaluate herbicide‐likeness by integrating qualitative and quantitative analyses. The simple and effective interpretation of the analysis interface may help noncomputational experts understand herbicide‐likeness. © 2020 Society of Chemical Industry

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Unfavorable bioavailability is an important aspect underlying the failure of drug candidates. Computational approaches for evaluating drug-likeness can minimize these risks. Over the past decades, computational approaches for evaluating drug-likeness have sped up the process of drug development and were also quickly derived to pesticide-likeness. As a result of many critical differences between drugs and pesticides, many kinds of methods for drug-likeness cannot be used for pesticide-likeness. Therefore, it is crucial to comprehensively compare and analyze the differences between drug-likeness and pesticide-likeness, which may provide a basis for solving the problems encountered during the evaluation of pesticide-likeness. Here, we systematically collected the recent advances of drug-likeness and pesticide-likeness and compared their characteristics. We also evaluated the current lack of studies on pesticide-likeness, the molecular descriptors and parameters adopted, the pesticide-likeness model on pesticide target organisms, and comprehensive analysis tools. This work may guide researchers to use appropriate methods for developing pesticide-likeness models. It may also aid non-specialists to understand some important concepts in drug-likeness and pesticide-likeness.

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