👤 Jianwei Shuai

In this study, we investigated the effects and molecular mechanisms by which Scutellaria barbata flavonoids (SBFs) enhance neurogenesis and ameliorate memory impairment mediated by CREB phosphorylation in rats, using a network pharmacology approach. The active ingredients of SBFs and their targets were identified using the Traditional Chinese Medicine Systems Pharmacology platform. An Alzheimer's disease (AD) model was established by intracerebroventricular injection of Aβ25-35 combined with AlCl₃ and RHTGF-β1 (composited Aβ) in rats. The Morris water maze was used to confirm the successful establishment of the AD rat model. Successfully modeled rats were randomly divided into three groups: a model group and two treatment groups receiving either 140 mg/kg SBFs or 0.5 mg/kg Rolipram (positive control). After 38 days, the Morris water maze test was performed to assess learning and memory abilities. Hematoxylin-eosin (HE) staining, immunohistochemistry, quantitative PCR (qPCR), and Western blotting (WB) were conducted to evaluate neuronal morphology, NeuN protein expression, the mRNA levels of TrkB, RSK, CREB, and BDNF, and the protein expression of NeuN, TrkB, RSK, P-CREB-Ser133, and BDNF in the hippocampus and cerebral cortex of the rats. These results indicate that SBFs and Rolipram ameliorate learning and memory impairment, reduce neuropathological changes, promote neurogenesis, and upregulate the BDNF- RSK-CREB signaling pathway through the activation of CREB phosphorylation. The findings suggest that the effects of SBFs are similar to those of Rolipram and that SBFs may also act as activators of CREB phosphorylation. Overall, SBFs promote neurogenesis and improve learning and memory deficits, possibly by enhancing CREB phosphorylation. This study identified the key targets and signaling pathways of SBFs in AD, indicating that SBFs represent a promising multitarget therapeutic candidate for the treatment of AD. However, our research has some limitations. Further studies are needed to determine the absorption route, major active components, and metabolic forms of the bioactive substances in SBFs. In future work, we aim to clarify the potential mechanisms of SBFs in AD by integrating multiple omics approaches and to evaluate the safety and efficacy of SBFs in AD treatment. Thirty-seven targets were identified based on the intersection between AD-related targets and the components of SBFs. SBFs were involved in anti-AD activity through the MAPK signaling pathway, including the BDNF-RSK-CREB pathway. SBFs attenuated memory impairment, ameliorated neuropathological changes, increased NeuN protein expression, and regulated the mRNA expression of TrkB, RSK, CREB, and BDNF, as well as the protein expression of NeuN, TrkB, RSK, P-CREB-Ser133, and BDNF. Rolipram produced similar effects to SBFs. Network pharmacology analysis and animal experiments confirmed that SBFs promote neurogenesis and ameliorate learning and memory impairment in AD model rats, primarily by facilitating CREB phosphorylation, similar to Rolipram. This study indicates that SBFs may be a promising therapeutic candidate for the treatment of AD. Show less

Studying the molecular properties of drugs and their interactions with human targets aids in better understanding the clinical performance of drugs and guides drug development. In computer-aided drug discovery, it is crucial to utilize effective molecular feature representations for predicting molecular properties and designing ligands with high binding affinity to targets. However, designing an effective multi-task and self-supervised strategy remains a significant challenge for the pretraining framework. In this study, a multi-task self-supervised deep learning framework is proposed, MTSSMol, which utilizes ≈10 million unlabeled drug-like molecules for pretraining to identify potential inhibitors of fibroblast growth factor receptor 1 (FGFR1). During the pretraining of MTSSMol, molecular representations are learned through a graph neural networks (GNNs) encoder. A multi-task self-supervised pretraining strategy is proposed to fully capture the structural and chemical knowledge of molecules. Extensive computational tests on 27 datasets demonstrate that MTSSMol exhibits exceptional performance in predicting molecular properties across different domains. Moreover, MTSSMol's capability is validated to identify potential inhibitors of FGFR1 through molecular docking using RoseTTAFold All-Atom (RFAA) and molecular dynamics simulations. Overall, MTSSMol provides an effective algorithmic framework for enhancing molecular representation learning and identifying potential drug candidates, offering a valuable tool to accelerate drug discovery processes. All of the codes are freely available online at https:// github.com/zhaoqi106/MTSSMol. Show less

The mechanistic target of rapamycin (mTOR) pathway plays a critical role in cell growth and metabolic homeostasis. The ribosomal protein S6 kinases S6K1 and S6K2 are the major effectors of the mTOR pathway key to translation efficiency, but the underlying regulatory mechanisms remain largely unclear. In this study, we searched for mTOR regulators and found that the splicing factor SRRM2 modulates the levels of S6K1 and S6K2, thereby activating the mTOR-S6K pathway. Interestingly, SRRM2 facilitates the expression of S6K2 by modulating alternative splicing, and enhances the stability of the S6K1 protein by regulating the E3 ubiquitin ligase WWP2. Moreover, SRRM2 is highly expressed in colorectal cancer (CRC) tissues and is associated with a poor prognosis. SRRM2 promotes CRC growth in vitro and in vivo. Combined, these data reveal an oncogenic role of SRRM2 in CRC through activating the mTOR-S6K pathway by two different approaches, further suggesting SRRM2 as a potential therapeutic target for CRC. Show less

Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is an oncogenic long noncoding RNA that has been found to promote carcinogenesis and metastasis in many tumors. However, the underlying role of MALAT1 in the progression and metastasis of hepatocellular carcinoma (HCC) remains unclear. In this study, aberrantly elevated levels of MALAT1 were detected in both HCC specimens and cell lines. We found that knockdown of MALAT1 caused retardation in proliferation, migration, and invasion both in vivo and in vitro. Mechanistic investigations showed that Snail family transcriptional repressor 1 (SNAI1) is a direct target of microRNA (miR)-22 and that MALAT1 modulates SNAI1 expression by acting as a competing endogenous RNA for miR-22. Inhibition of miR-22 restored SNAI1 expression suppressed by MALAT1 knockdown. Furthermore, MALAT1 facilitated the enrichment of enhancer of zeste homolog 2 (EZH2) at the promoter region of miR-22 and E-cadherin, which was repressed by MALAT1 knockdown. Cooperating with EZH2, MALAT1 positively regulated SNAI1 by repressing miR-22 and inhibiting E-cadherin expression, playing a vital role in epithelial to mesenchymal transition. In conclusion, our results reveal a mechanism by which MALAT1 promotes HCC progression and provides a potential target for HCC therapy. Show less

Clinical diagnosis of SLE is currently challenging due to its heterogeneity. Many autoantibodies are associated with SLE and are considered potential diagnostic markers, but systematic screening and validation of such autoantibodies is lacking. This study aimed to systematically discover new autoantibodies that may be good biomarkers for use in SLE diagnosis. Sera from 15 SLE patients and 5 healthy volunteers were analysed using human proteome microarrays to identify candidate SLE-related autoantibodies. The results were validated by screening of sera from 107 SLE patients, 94 healthy volunteers and 60 disease controls using focussed arrays comprised of autoantigens corresponding to the identified candidate antibodies. Logistic regression was used to derive and validate autoantibody panels that can discriminate SLE disease. Extensive ELISA screening of sera from 294 SLE patients and 461 controls was performed to validate one of the newly discovered autoantibodies. A total of 31, 11 and 18 autoantibodies were identified to be expressed at significantly higher levels in the SLE group than in the healthy volunteers, disease controls and healthy volunteers plus disease control groups, respectively, with 25, 7 and 13 of these differentially expressed autoantibodies being previously unreported. Diagnostic panels comprising anti-RPLP2, anti-SNRPC and anti-PARP1, and anti-RPLP2, anti-PARP1, anti-MAK16 and anti- RPL7A were selected. Performance of the newly discovered anti-MAK16 autoantibody was confirmed by ELISA. Some associations were seen with clinical characteristics of SLE patients, such as disease activity with the level of anti-PARP1 and rash with the level of anti-RPLP2, anti-MAK16 and anti- RPL7A. The combined autoantibody panels identified here show promise for the diagnosis of SLE and for differential diagnosis of other major rheumatic immune diseases. Show less

In this issue of Molecular Cell, Lee et al. (2009) report that SUMOylation of nuclear receptors LXRalpha and LXRbeta plays a critical role in the transrepression of IFN-gamma-induced STAT1-dependent inflammatory responses in brain astrocytes. Show less