SYT11

更新于：2025-05-07

基本信息

别名

DKFZp781D015、KIAA0080、MGC10881

+ [6]

简介

Synaptotagmin family member involved in vesicular and membrane trafficking which does not bind Ca(2+). Inhibits clathrin-mediated and bulk endocytosis, functions to ensure precision in vesicle retrieval. Plays an important role in dopamine transmission by regulating endocytosis and the vesicle-recycling process. Essential component of a neuronal vesicular trafficking pathway that differs from the synaptic vesicle trafficking pathway but is crucial for development and synaptic plasticity. In macrophages and microglia, inhibits the conventional cytokine secretion, of at least IL6 and TNF, and phagocytosis. In astrocytes, regulates lysosome exocytosis, mechanism required for the repair of injured astrocyte cell membrane (By similarity). Required for the ATP13A2-mediated regulation of the autophagy-lysosome pathway (PubMed:27278822).

关联

项与 SYT11 相关的药物

OCG-01-2020

靶点

SYT11

作用机制

SYT11抑制剂

在研机构

One Curegen Co., Ltd.

原研机构

One Curegen Co., Ltd.

在研适应症

结直肠癌 [+2]

非在研适应症-

最高研发阶段药物发现

首次获批国家/地区-

首次获批日期1800-01-20

100 项与 SYT11 相关的临床结果

登录后查看更多信息

100 项与 SYT11 相关的转化医学

登录后查看更多信息

0 项与 SYT11 相关的专利（医药）

登录后查看更多信息

项与 SYT11 相关的文献（医药）

2025-06-01·Bioorganic Chemistry

In vitro and in vivo antidiabetic evaluation of new Coumarin and Chromone derivatives: Design, synthesis and molecular modeling

Article

作者: Serry, Aya M ; Hamed, Karima A ; Abdelhafez, Omaima M ; Khalil, Wagdy K B ; Shalaby, Mohamed B ; Ahmed, Eman Y ; Mabrouk, Mohamed I

Diabetes mellitus is a chronic metabolic disease characterized by an imbalance in glucose homeostasis, which raises blood glucose levels. α-glucosidase enzyme hydrolyzes polysaccharides to produce glucose and since glucose is one of the primary energy sources in eukaryotes, α-glucosidase is a target for postprandial hyperglycemia regulation. The design and synthesis of new oxadiazole coumarin (5a,b and 6a,b), acryloyl chromone (10a-c) and pyrazolyl chromone (11a-c) derivatives as naturally based scaffolds are presented in this work. The new compounds were assessed as antidiabetic agents targeting α-glucosidase enzyme. With an IC₅₀ value of 119.7 ± 4.3 μM, compound 11c demonstrated the most promising α-glucosidase inhibitory activity, superior to the standard drug acarbose (IC₅₀ = 300.9 ± 10.9 μM). Furthermore, compared to the group of diabetic rats, the in vivo investigations demonstrated that medium and high dosages of 11c ameliorated the expression of diabetic related genes (GCK, SYT11, SNAP-25 and Ins1). According to the molecular docking results, 11c possessed the best binding energy score (-9.1 kcal/mol) within the α-glucosidase active site, outperforming the rest of the derivatives and the reference inhibitor acarbose (-8.2 kcal/mol). Lastly, an in silico molecular dynamic simulation and a pharmacokinetic study were performed on compound 11c.

2025-02-01·Biochemical Genetics

Constructing a Novel Amino Acid Metabolism Signature: A New Perspective on Pheochromocytoma Diagnosis, Immune Landscape, and Immunotherapy

Article

作者: Ren, Yilin ; Liu, Tonghu ; Zhao, Luyang ; Wang, Yu ; Gao, Yukui ; Li, Zhiyuan ; Sun, Weibo ; Yan, Zechen ; Shen, Linnuo ; Luan, Yongkun ; Yang, Xiaojie

AbstractPheochromocytoma/paraganglioma (PGPG) is a rare neuroendocrine tumor. Amino acid metabolism is crucial for energy production, redox balance, and metabolic pathways in tumor cell proliferation. This study aimed to build a risk model using amino acid metabolism-related genes, enhancing PGPG diagnosis and treatment decisions. We analyzed RNA-sequencing data from the PCPG cohort in the GEO dataset as our training set and validated our findings using the TCGA dataset and an additional clinical cohort. WGCNA and LASSO were utilized to identify hub genes and develop risk prediction models. The single-sample gene set enrichment analysis, MCPCOUNTER, and ESTIMATE algorithm calculated the relationship between amino acid metabolism and immune cell infiltration in PCPG. The TIDE algorithm predicted the immunotherapy efficacy for PCPG patients. The analysis identified 292 genes with differential expression, which are involved in amino acid metabolism and immune pathways. Six genes (DDC, SYT11, GCLM, PSMB7, TYRO3, AGMAT) were identified as crucial for the risk prediction model. Patients with a high-risk profile demonstrated reduced immune infiltration but potentially higher benefits from immunotherapy. Notably, DDC and SYT11 showed strong diagnostic and prognostic potential. Validation through quantitative Real-Time Polymerase Chain Reaction and immunohistochemistry confirmed their differential expression, underscoring their significance in PCPG diagnosis and in predicting immunotherapy response. This study’s integration of amino acid metabolism-related genes into a risk prediction model offers critical clinical insights for PCPG risk stratification, potential immunotherapy responses, drug development, and treatment planning, marking a significant step forward in the management of this complex condition.

2025-01-01·Annals of Neurosciences

From Diagnosis to Treatment: A Comprehensive Review of Biomarkers and Therapeutic Advances in Parkinson’s Disease

Review

作者: Abbas, Syed Raza ; Rangwala, Hussain Sohail ; Rangwala, Burhanuddin Sohail ; Fatima, Hareer ; Syed, Aina Marzia

Background Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the loss of dopaminergic neurons, resulting in motor symptoms. Ongoing research shows promise for long-term solutions. Summary Studies highlight the dysregulation of Syt11 and α-synuclein (α-syn) in PD. Disrupted α-syn homeostasis due to palmitoylation of Syt11 contributes to its aggregation, potentially playing a role in PD pathology. α-synuclein aggregates in stool samples show promise as an early diagnostic biomarker. Vocal impairments in PD may be linked to α-syn-induced neuropathology. Irisin, produced after exercise, promotes the degradation of pathologic α-syn. Progress has been made in identifying PD biomarkers. Retinal thinning and abnormal protein aggregates in skin biopsies provide noninvasive diagnostic indicators. Blood-based biomarkers like α-syn, DJ-1, and LRRK2 hold promise but face limitations. Artificial intelligence (AI) models enhance mitophagy, detect PD through sleep-breathing signals, and improve survival. AI analysis aids noninvasive assessment and risk prediction. Further understanding of PD involves studying pathological seeds and genetic mutations. Adenosine receptor regulation relates to early-onset PD, and specific gene mutations impact patient survival. Differentiated-induced pluripotent stem cells offer the potential for cell replacement therapy. Autoimmune features and T-cell involvement suggest intervention targets. Stem cell-based therapies and neurostimulation strategies show promise for improving motor function. Imaging reveals increased central inflammation in PD, suggesting an inflammatory role. Machine learning algorithms and home gait speed monitoring aid in diagnosis and disease progression tracking. Abnormal putamen gradients reflect dopaminergic loss and motor dysfunction. Antiepileptic drug prescriptions are associated with an increased PD risk. Personalized medicine, gut–brain axis involvement, and vestibular stimulation therapy offer potential PD treatment avenues. Genetic engineering techniques and deep brain stimulation show promise for alleviating PD symptoms. Key Message Ongoing research and technological advancements promise to improve PD screening, diagnosis, and treatment, bringing hope to affected individuals.