Figure 4 - uploaded by Michael Arowosegbe
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Receptor ligand interaction for PF357 within the GSK3B active site. The purple lines represent hydrogen bonds and their arrows signify the order of proton transfer. The red line represents the carion-π stacking.
Source publication
GSK3B has been an interesting drug target in the pharmaceutical industry. Its dysfunctional expression has prognostic significance in the top 3 cause of death associated with non-communicable diseases (cancer, Alzheimer's disease and type 2 diabetes). Previous studies have shown clearly that inhibiting GSK3B has proven therapeutic significance in A...
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Context 1
... implemented the power of Glide XP to predict the chemical interaction of GSK3B/PF-367 and GSK3B/BT-000775 using the ligand interaction diagram interface in Maestro (Schrodinger Inc.). The software effectively predicted the same binding of PF-367 to GSK3B as shown in Figure 4. For BT-000775, ( Figure 5) the amide nitrogen on prayzole ring donates a proton to ASP 133 to form a hydrogen bond while Val 135 establishes a hydrogen bond with the nitrogen on the same ring. ...
Context 2
... implemented the power of Glide XP to predict the chemical interaction of GSK3B/PF-367 and GSK3B/BT-000775 using the ligand interaction diagram interface in Maestro (Schrodinger Inc.). The software effectively predicted the same binding of PF-367 to GSK3B as shown in Figure 4. For BT-000775, ( Figure 5) the amide nitrogen on prayzole ring donates a proton to ASP 133 to form a hydrogen bond while Val 135 establishes a hydrogen bond with the nitrogen on the same ring. ...
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Citations
... Glycogen synthase kinase-3β (GSK3β), initially recognized as an enzyme responsible for glycogen synthase phosphorylation and deactivation, is now recognized as a ubiquitous signaling molecule pivotal in various cellular functions. GSK3β is a promising drug target for numerous neurological disorders, including Alzheimer's disease, Parkinson's disease, schizophrenia, and bipolar disorder, as well as conditions related to energy metabolism and cell death, such as diabetes and cancer [6,7]. The extensive use of this kinase in various diseases stems from its role as an active protein kinase that regulates nearly 40 protein substrates, all of which are modulated by signaling pathways such as Wnt, insulin, and brain-derived neurotrophic factor (BDNF). ...
Glycogen synthase kinase-3β (GSK3β) not only plays a crucial role in regulating sperm maturation but also is pivotal in orchestrating the acrosome reaction. Here, we integrated single-molecule long-read and short-read sequencing to comprehensively examine GSK3β expression patterns in adult Diannan small-ear pig (DSE) testes. We identified the most important transcript ENSSSCT00000039364 of GSK3β, obtaining its full-length coding sequence (CDS) spanning 1263 bp. Gene structure analysis located GSK3β on pig chromosome 13 with 12 exons. Protein structure analysis reflected that GSK3β consisted of 420 amino acids containing PKc-like conserved domains. Phylogenetic analysis underscored the evolutionary conservation and homology of GSK3β across different mammalian species. The evaluation of the protein interaction network, KEGG, and GO pathways implied that GSK3β interacted with 50 proteins, predominantly involved in the Wnt signaling pathway, papillomavirus infection, hippo signaling pathway, hepatocellular carcinoma, gastric cancer, colorectal cancer, breast cancer, endometrial cancer, basal cell carcinoma, and Alzheimer’s disease. Functional annotation identified that GSK3β was involved in thirteen GOs, including six molecular functions and seven biological processes. ceRNA network analysis suggested that DSE GSK3β was regulated by 11 miRNA targets. Furthermore, qPCR expression analysis across 15 tissues highlighted that GSK3β was highly expressed in the testis. Subcellular localization analysis indicated that the majority of the GSK3β protein was located in the cytoplasm of ST (swine testis) cells, with a small amount detected in the nucleus. Overall, our findings shed new light on GSK3β’s role in DSE reproduction, providing a foundation for further functional studies of GSK3β function.
... z = 27.613 (18,23). 3D structure of the VAV1 gene was detected as "6NFA" code from the PDB database (18). ...
... The structural study of GSK-3β inhibitors were observed certain interactions between to the ATP binding site via hydrogen bonds with Asp133 or Val135 (two key binding residues) [13]. Based on the urea moiety's substituent, we revealed two distinct mechanisms of binding. ...
New thienopyrimidine derivatives were designed and synthesized as GSK-3β inhibitors based on the structure of active binding site of GSK-3β enzyme. In this study, compounds 6b and 6a were found to be moderate GSK-3β inhibitors with IC50s 10.2 and 17.3 μM, respectively. Molecular docking study was carried out by docking the targeted compounds in the binding site of the GSK-3β enzyme using the MOE program. Moreover, ADME study was performed to predict certain pharmacokinetic properties. The results showed that all synthesized compounds may not be able to penetrate the blood brain barrier; so, the chances of CNS side effects are predicted to be low. CYP1D6 is predicted to be inhibited by compounds (5a, 5d, 6a, 9a and 9b), So drug-drug interactions are expected upon administration of these compounds.
Graphical Abstract
... Both of them have similar structures and substrates but different functions (20,21). In the early stage, it has been reported that GSK3B is participated in the malignant development of PC (22,23). Here, the Western Blot results revealed that knockdown of EPS8L3 can markedly reduce the GSK3B expression in PC cells; and the recovery experimentations also suggested that overexpression of GSK3B can reversal the prohibitive effect of silencing EPS8L3 on the proliferative ability and metastasis of PC cells. ...
Background:
We intended to investigate the role and regulatory mechanism of EPS8L3 in increase the development of pancreatic cancer (PC).
Methods:
In order to analyze the relationship between EPS8L3 level and clinicopathological indicators of PC patients, qRT-PCR was used to detect the expression of EPS8L3 in tumor specimens of 40 PC patients. EPS8L3 knockdown models were then constructed in PC cell lines. Furthermore, the effect of EPS8L3 on PC cell function was analyzed by CCK-8 and Transwell assay. Dual luciferase reporter gene assay and recovery assay were used to further investigate the underlying mechanism.
Results:
qRT-PCR results indicated that EPS8L3 was highly expressed in PC tissues compared with adjacent ones. At the same time, the incidence of distant metastasis was higher in PC patients with high EPS8L3 level. In vitro analysis such as CCK-8 and Transwell experimentations indicated that knockdown of EPS8L3 markedly inhibited the proliferative and metastatic ability. Bio-informatics together with luciferase report assay proposing that EPS8L3 can target GSK3B. Western Blot results revealed that knockdown of EPS8L3 markedly reduced the GSK3B expression in PC cells, and there was a positively associated between the two in PC cells. In addition, the recovery experimentation proved that EPS8L3 and GSK3B have a mutual regulation effect. Overexpression of GSK3B can reversal the prohibitive effect of EPS8L3 knockdown on the malignant development of PC cells, thereby jointly regulating the occurrence and development of PC.
Conclusions:
EPS8L3 promotes the development of PC by regulating GSK3B, suggesting that EPS8L3 can be used as a biomarker for early diagnosis and treatment of PC.
... In another study, the binding score of the molecule Tideglusib, which had significant results in clinical trials, was determined as -9.4 in docking studies [17]. According to a study conducted with the inhibitor coded PF-367, hydrogen bond formation occurred between the amino acids Val 135 and Asp 133 and the ligand, and it was found that there was a π-bond interaction with Arg 141 [10]. According to our findings, emodin molecule similarly formed hydrogen formation with Val133 and Asp 133 amino acids (Figure 3). ...
... The crystal structure suitable for GSK3-β was downloaded from the Protein Data Bank with reference to a study by Adewale J. Ogunleye and his colleagues. (PDB Code: 5K5N) [10]. ...
... Zhang et al., 2019), and inhibition of it was considered efficient in suppressing tumor growth (Edderkaoui et al., 2018;Wu et al., 2019). Moreover, there have been many studies on GSK3B inhibitors, including Metavert molecule in PAAD (Edderkaoui et al., 2018), BT-000775 molecule in BRCA (Ogunleye et al., 2019), BIO molecule in TNBCs (triple-negative breast cancers) (Vijay et al., 2019), AR-A014418 and SB-216763 molecules in STSs (soft tissue sarcomas) (Abe et al., 2020), etc. ...
5-Methylcytosine (m 5 C) is a kind of methylation modification that occurs in both DNA and RNA and is present in the highly abundant tRNA and rRNA. It has an important impact on various human diseases including cancer. The function of m 5 C is modulated by regulatory proteins, including methyltransferases (writers) and special binding proteins (readers). This study aims at comprehensive study of the m 5 C RNA methylation-related genes and the main pathways under m 5 C RNA methylation in gastrointestinal (GI) cancer. Our result showed that the expression of m 5 C writers and reader was mostly up-regulated in GI cancer. The NSUN2 gene has the highest proportion of mutations found in GI cancer. Importantly, in liver cancer, higher expression of almost all m 5 C regulators was significantly associated with lower patient survival rate. In addition, the expression level of m 5 C-related genes is significantly different at various pathological stages. Finally, we have found through bioinformatics analysis that m 5 C regulatory proteins are closely related to the ErbB/PI3K-Akt signaling pathway and GSK3B was an important target for m 5 C regulators. Besides, the compound termed streptozotocin may be a key candidate drug targeting on GSK3B for molecular targeted therapy in GI cancer.
Background:
Alzheimer disease (AD) is a degenerative brain disease, which may lead to severe memory loss and other cognitive disorders. However, few effective drugs are available in the clinic at present. Curcumin, a major ingredient of traditional Chinese medicine, Curcuma Longa, has various pharmacological activities. Therefore, exploring clinical drugs based on the inhibition of AD pathological features is imperative.
Methods:
First, we utilized the HERB database and Swisstarget Prediction database to get the related targets of curcumin and intersected with the AD targets. The intersection targets were used to construct the protein-protein interaction network and performed gene ontology and kyoto encyclopedia of genes and genomes analyses. Further, we obtained targets of curcumin against AD-related tau and aβ pathology via the AlzData database. These targets were applied to perform GEO and receiver operating characteristic analyses. Finally, the reliability of the core targets was evaluated using molecular docking technology.
Results:
We identified 49 targets of curcumin against AD, and kyoto encyclopedia of genes and genomes pathway enrichment analysis demonstrated that the Alzheimer disease pathway (has05010) was significantly enriched. Even more, we obtained 16 targets of curcumin-related Aβ and tau pathology. Among these targets, 8 targets involved the Alzheimer disease pathway and the biological process analyses showed that positive regulation of cytokine production (GO:0001819) was significantly enriched. Bioinformatic analyses indicated that HMOX1, CSF1R, NFKB1, GSK3B, BACE1, AR, or PTGS1 expression was significantly different compared to the control group in the AD patients. Finally, molecular docking studies suggested these genes have a good binding force with curcumin.
Conclusions:
In this study, we identified curcumin exerted the effect of treating AD by regulating multitargets and multichannels through the method of network pharmacology.
Alzheimer's disease (AD) is the most common cause of dementia, affecting approximately 35 million people worldwide. The current treatment options for people with AD consist of drugs designed to slow the rate of decline in memory and cognition, but these treatments are not curative, and patients eventually suffer complete cognitive injury. With the substantial amounts of published data on targets for this disease, we proposed that machine learning software could be used to find novel small-molecule treatments that can supplement the AD drugs currently on the market. In order to do this, we used publicly available data in ChEMBL to build and validate Bayesian machine learning models for AD target proteins. The first AD target that we have addressed with this method is the serine−threonine kinase glycogen synthase kinase 3 beta (GSK3β), which is a proline-directed serine−threonine kinase that phosphorylates the microtubule-stabilizing protein tau. This phosphorylation prompts tau to dissociate from the microtubule and form insoluble oligomers called paired helical filaments, which are one of the components of the neurofibrillary tangles found in AD brains. Using our Bayesian machine learning model for GSK3β consisting of 2368 molecules, this model produced a five-fold cross validation ROC of 0.905. This model was also used for virtual screening of large libraries of FDA-approved drugs and clinical candidates. Subsequent testing of selected compounds revealed a selective small-molecule inhibitor, ruboxistaurin, with activity against GSK3β (avg IC 50 = 97.3 nM) and GSK3α (IC 50 = 695.9 nM). Several other structurally diverse inhibitors were also identified. We are now applying this machine learning approach to additional AD targets to identify approved drugs or clinical trial candidates that can be repurposed as AD therapeutics. This represents a viable approach to accelerate drug discovery and do so at a fraction of the cost of traditional high throughput screening.
