The screening strategy based on α-glucosidase inhibition has been widely employed for the discovery of antidiabetic drugs, but it still faces some challenges in practical applications, such as poor stability of enzyme, high consumption of test compounds, low sensitivity of screening methods and so on. In this work, a bifunctional hybrid enzyme-catalytic metal organic framework reactor (GAA@ GOx@Cu-MOF) with a flower-shaped globular structure was innovatively prepared via self-assembling of α-glucosidase (GAA), glucose oxidase (GOx), Cu 2+ , and 4,4′-bipyridine. It was found that GAA@GOx@Cu-MOF not only enjoyed merits of high stability, selectivity, and sensitivity but also possessed the character of assembly line work, with about 4.58 times enhanced enzyme activity compared with the free enzyme system. Based on the above characteristics, a highly sensitive screening of GAA inhibitors could be achieved with the detection limit of 7.05 nM for acarbose. Furthermore, the proposed method was successfully applied to the screening of oleanolic acid derivatives as potential antidiabetic drugs. Therefore, it was expected that this work could provide new insights and inspirations for the screening of clinical antidiabetic drugs and for further exploration of functional MOF composites.

Bacterial infections remain the leading cause of death worldwide today. The emergence of antibiotic resistance has urged the development of alternative antibacterial technologies to complement or replace traditional antibiotic treatments. In this regard, metal nanomaterials have attracted great attention for their controllable antibacterial functions that are less prone to resistance. This review discusses a particular family of stimuli-activable metal-bearing nanomaterials (denoted as SAMNs) and the associated on-demand antibacterial strategies. The various SAMN-enabled antibacterial strategies stem from basic light and magnet activation, with the addition of bacterial microenvironment responsiveness and/or bacteriatargeting selectivity and therefore offer higher spatiotemporal controllability. The discussion focuses on nanomaterial design principles, antibacterial mechanisms, and antibacterial performance, as well as emerging applications that desire on-demand and selective activation (i.e., medical antibacterial treatments, surface anti-biofilm, water disinfection, and wearable antibacterial materials). The review concludes with the authors' perspectives on the challenges and future directions for developing industrial translatable next-generation antibacterial strategies.

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Ursolic acid (UA) is a major pentacyclic triterpenoid in plants, vegetables and fruits, which has been reported to have a potential anti-diabetic activity. Despite various semi-synthetic ursolic acid derivatives already described, new derivatives still need to be designed and synthesized to further improve the anti-diabetic activity. In the present study, two series of novel UA derivatives, were synthesized and their structures were confirmed. The enzyme inhibition activities of semi-synthesized analogues against α-glucosidase were screened in vitro. The results indicated that most of UA derivatives showed a significant inhibitory activity, especially analogues UA-O-i with the IC50 values of 0.71 ± 0.27 μM, which was more potential than other analogues and the positive control. Furthermore, molecular docking studies were also investigated to verify the in vitro study. Structure modification at the C-3 and C-2 positions of UA was an effective approach to obtain the desired ligand from UA, whose structure was in accordance with the active pocket. Besides, suitable hydrophobic group at the position of C-2 might play an important role for the docking selectivity and binding affinity between the ligand and the homology modelling protein. These results could be helpful for designing more potential α-glucosidase inhibitors from UA in the future.

Chinese medicine is known to treat complex diseases with multiple components and multiple targets. However, the main effective components and their related key targets and functions remain to be identified. Herein, a network analysis method was developed to identify the main effective components and key targets of a Chinese medicine, Lianhua-Qingwen Formula (LQF). The LQF is commonly used for the prevention and treatment of viral influenza in China. It is composed of 11 herbs, gypsum and menthol with 61 compounds being identified in our previous work. In this paper, these 61 candidate compounds were used to find their related targets and construct the predicted-target (PT) network. An influenza-related protein-protein interaction (PPI) network was constructed and integrated with the PT network. Then the compound-effective target (CET) network and compound-ineffective target network (CIT) were extracted, respectively. A novel approach was developed to identify effective components by comparing CET and CIT networks. As a result, 15 main effective components were identified along with 61 corresponding targets. 7 of these main effective components were further experimentally validated to have antivirus efficacy in vitro. The main effective component-target (MECT) network was further constructed with main effective components and their key targets. Gene Ontology (GO) analysis of the MECT network predicted key functions such as NO production being modulated by the LQF. Interestingly, five effective components were experimentally tested and exhibited inhibitory effects on NO production in the LPS induced RAW 264.7 cell. In summary, we have developed a novel approach to identify the main effective components in a Chinese medicine LQF and experimentally validated some of the predictions.

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