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Bystander‐killing payloads can significantly overcome the tumor heterogeneity issue and enhance the clinical potential of antibody‐drug conjugates (ADC), but the rational design and identification of effective bystander warheads constrain the broader implementation of this strategy. Here, graph attention networks (GAT) are constructed for a rational bystander killing scoring model and ADC construction workflow for the first time. To generate efficient bystander‐killing payloads, this model is utilized for score‐directed exatecan derivatives design. Among them, Ed9, the most potent payload with satisfactory permeability and bioactivity, is further used to construct ADC. Through linker optimization and conjugation, novel ADCs are constructed that perform excellent anti‐tumor efficacy and bystander‐killing effect in vivo and in vitro. The optimal conjugate T‐VEd9 exhibited therapeutic efficacy superior to DS‐8201 against heterogeneous tumors. These results demonstrate that the effective scoring approach can pave the way for the discovery of novel ADC with promising bystander payloads to combat tumor heterogeneity. [ABSTRACT FROM AUTHOR]

Predicting the biological properties of molecules is crucial in computer-aided drug development, yet it's often impeded by data scarcity and imbalance in many practical applications. Existing approaches are based on self-supervised learning or 3D data and using an increasing number of parameters to improve performance. These approaches may not take full advantage of established chemical knowledge and could inadvertently introduce noise into the respective model. In this study, we introduce a more elegant transformer-based framework with focused attention for molecular representation (TransFoxMol) to improve the understanding of artificial intelligence (AI) of molecular structure property relationships. TransFoxMol incorporates a multi-scale 2D molecular environment into a graph neural network + Transformer module and uses prior chemical maps to obtain a more focused attention landscape compared to that obtained using existing approaches. Experimental results show that TransFoxMol achieves state-of-the-art performance on MoleculeNet benchmarks and surpasses the performance of baselines that use self-supervised learning or geometry-enhanced strategies on small-scale datasets. Subsequent analyses indicate that TransFoxMol's predictions are highly interpretable and the clever use of chemical knowledge enables AI to perceive molecules in a simple but rational way, enhancing performance. [ABSTRACT FROM AUTHOR]

Molecular clustering analysis has been developed to facilitate visual inspection in the process of structure-based virtual screening. However, traditional methods based on molecular fingerprints or molecular descriptors limit the accuracy of selecting active hit compounds, which may be attributed to the lack of representations of receptor structural and protein–ligand interaction during the clustering. Here, a novel deep clustering framework named ClusterX is proposed to learn molecular representations of protein–ligand complexes and cluster the ligands. In ClusterX, the graph was used to represent the protein–ligand complex, and the joint optimisation can be used efficiently for learning the cluster-friendly features. Experiments on the KLIFs database show that the model can distinguish well between the binding modes of different kinase inhibitors. To validate the effectiveness of the model, the clustering results on the virtual screening dataset further demonstrated that ClusterX achieved better or more competitive performance against traditional methods, such as SIFt and extended connectivity fingerprints. This framework may provide a unique tool for clustering analysis and prove to assist computational medicinal chemists in visual decision-making. [ABSTRACT FROM AUTHOR]

While neuroblastoma accounts for 15% of childhood tumor-related deaths, treatments against neuroblastoma remain scarce and mainly consist of cytotoxic chemotherapeutic drugs. Currently, maintenance therapy of differentiation induction is the standard of care for neuroblastoma patients in clinical, especially high-risk patients. However, differentiation therapy is not used as a first-line treatment for neuroblastoma due to low efficacy, unclear mechanism, and few drug options. Through compound library screening, we accidently found the potential differentiation-inducing effect of AKT inhibitor Hu7691. The protein kinase B (AKT) pathway is an important signaling pathway for regulating tumorigenesis and neural differentiation, yet the relation between the AKT pathway and neuroblastoma differentiation remains unclear. Here, we reveal the anti-proliferation and neurogenesis effect of Hu7691 on multiple neuroblastoma cell lines. Further evidence including neurites outgrowth, cell cycle arrest, and differentiation mRNA marker clarified the differentiation-inducing effect of Hu7691. Meanwhile, with the introduction of other AKT inhibitors, it is now clear that multiple AKT inhibitors can induce neuroblastoma differentiation. Furthermore, silencing AKT was found to have the effect of inducing neuroblastoma differentiation. Finally, confirmation of the therapeutic effects of Hu7691 is dependent on inducing differentiation in vivo , suggesting that Hu7691 is a potential molecule against neuroblastoma. Through this study, we not only define the key role of AKT in the progression of neuroblastoma differentiation but also provide potential drugs and key targets for the application of differentiation therapies for neuroblastoma clinically. This study not only defines the key role of AKT in the progression of neuroblastoma differentiation but also provides potential drugs and key targets for the application of differentiation therapies for neuroblastoma clinically. [Display omitted] [ABSTRACT FROM AUTHOR]

Nuclear export protein 1 (XPO1), a member of the nuclear export protein-p (Karyopherin-P) superfamily, regulates the transport of "cargo" proteins. To facilitate this important process, which is essential for cellular homeostasis, XPO1 must first recognize and bind the cargo proteins. To inhibit this process, small molecule inhibitors have been designed that inhibit XPO1 activity through covalent binding. However, the scaffolds for these inhibitors are very limited. While virtual screening may be used to expand the diversity of the XPO1 inhibitor skeleton, enormous computational resources would be required to accomplish this using traditional screening methods. In the present study, we report the development of a hybrid virtual screening workflow and its application in XPO1 covalent inhibitor screening. After screening, several promising XPO1 covalent molecules were obtained. Of these, compound 8 performed well in both tumor cell proliferation assays and a nuclear export inhibition assay. In addition, molecular dynamics simulations were performed to provide information on the mode of interaction of compound 8 with XPO1. This research has identified a promising new scaffold for XPO1 inhibitors, and it demonstrates an effective and resource-saving workflow for identifying new covalent inhibitors. [ABSTRACT FROM AUTHOR]

The emergence of imazalil (IMZ) resistance in Penicillium digitatum has become a great threat for controlling citrus green mold. In this paper, we investigated the antifungal efficiency and mechanism of an alkaloid antofine against an IMZ‐resistant P. digitatum strain Pdw03. Results showed that antofine exhibited a strong antifungal activity against the mycelial growth of strain Pdw03, with a minimum inhibitory concentration (MIC) and the minimum fungicidal concentration (MFC) of 1.56 × 10−3 and 1.25 × 10−2 g/L, respectively. In vivo application of antofine effectively delayed the disease progress and reduced the incidence of green mold in citrus fruit. The disease incidence of 10 × MFC antofine‐treated fruit after 6 days of storage was only 11% ± 4%, which was significantly lower than that of the control (100% ± 0%). Antofine treatment altered mycelial morphology of strain Pdw03 without affecting the cell wall integrity. Although the ergosterol contents remained stable, a decrease in the total lipid content induced by lipid peroxidation was observed at 30 min of exposure, indicating disruption of cell membrane permeability of strain Pdw03. In addition, the mitochondrial membrane potential (MMP) and adenosine triphosphate (ATP) contents were also decreased at 60 min of exposure. These results indicated that antofine inhibited the growth of strain Pdw03 by disrupting cell membrane permeability and impairing energy metabolism induced by oxidative burst. Practical applications: One of the most economically important postharvest diseases of citrus fruit is green mold caused by Penicillium digitatum. The pathogen is mainly controlled by using imazalil, but the prolonged and extensive application of this chemical fungicide has led to emergence of numerous IMZ‐resistant strains among P. digitatum isolates. Consequently, new and safe strategies for controlling citrus green mold caused by IMZ‐resistant P. digitatum strains are urgently needed. In this study, an alkaloid antofine effectively inhibited the growth of IMZ‐resistant P. digitatum strain Pdw03 and significantly decreased green mold incidence in the affected citrus fruits. Antofine induced membrane lipid peroxidation of Pdw03 mycelia, resulting in damage to the cell membrane and impairment of energy metabolism. Antofine is therefore a potential antifungal agent for the control of green mold, which provide theoretical guidance for the food industry. [ABSTRACT FROM AUTHOR]

Ticagrelor is the first reversible P2Y12 receptor antagonist that inhibits ADP‐induced platelet aggregation. In several areas of biomedical research, the deuterium strategy has been employed to slow down the rate of drug metabolism and improve the pharmacokinetic properties of drugs. In the present study, several deuterated analogs of ticagrelor, as well as their prodrugs, were designed and synthesized in order to improve the metabolic stability of ticagrelor. Further in vitro and in vivo pharmacokinetic experiments using the deuterated derivates 24 and 25 demonstrated that the metabolic stability of deuterated compounds was improved compared to that of the parent compound. In addition, the half‐life of the deuterated valine ester prodrug 31 (t1/2 =2.54±0.32 h) was significantly lengthened, reaching a value of approximately 40 % longer than that of ticagrelor (t1/2=1.77±0.14 h). [ABSTRACT FROM AUTHOR]