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Tang X, Zhou Y, Wang Y, Lin Y, Pan S, Che Q, Sang J, Gao Z, Zhang W, Wang Y, Li G, Gao L, Wang Z, Yang X, Liu A, Wang S, Yu B, Xu P, Wang Z, Zhang Z, Yang P, Xie W, Sun H, Li W. Direct Synthesis of α- and β-2'-Deoxynucleosides with Stereodirecting Phosphine Oxide via Remote Participation. J Am Chem Soc 2024; 146:8768-8779. [PMID: 38483318 DOI: 10.1021/jacs.4c01780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
2'-Deoxynucleosides and analogues play a vital role in drug development, but their preparation remains a significant challenge. Previous studies have focused on β-2'-deoxynucleosides with the natural β-configuration. In fact, their isomeric α-2'-deoxynucleosides also exhibit diverse bioactivities and even better metabolic stability. Herein, we report that both α- and β-2'-deoxynucleosides can be prepared with high yields and stereoselectivity using a remote directing diphenylphosphinoyl (DPP) group. It is particularly efficient to prepare α-2'-deoxynucleosides with an easily accessible 3,5-di-ODPP donor. Instead of acting as a H-bond acceptor on a 2-(diphenylphosphinoyl)acetyl (DPPA) group in our previous studies for syn-facial O-glycosylation, the phosphine oxide moiety here acts as a remote participating group to enable highly antifacial N-glycosylation. This proposed remote participation mechanism is supported by our first characterization of an important 1,5-briged P-heterobicyclic intermediate via variable-temperature NMR spectroscopy. Interestingly, antiproliferative assays led to a α-2'-deoxynucleoside with IC50 values in the low micromole range against central nervous system tumor cell lines SH-SY5Y and LN229, whereas its β-anomer exhibited no inhibition at 100 μM. Furthermore, the DPP group significantly enhanced the antitumor activities by 10 times.
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Affiliation(s)
- Xintong Tang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Yueer Zhou
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Yingjie Wang
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
| | - Yetong Lin
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Shuheng Pan
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Qianwei Che
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Jinpeng Sang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Ziming Gao
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Weiting Zhang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Yuanyuan Wang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Guolong Li
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Longwei Gao
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Zhimei Wang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Xudong Yang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Ao Liu
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Suyu Wang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Biao Yu
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
| | - Peng Xu
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai 200032, China
| | - Zhe Wang
- Department of TCMs Pharmaceuticals, School of Traditional Chinese Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Zhaolun Zhang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Peng Yang
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Weijia Xie
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Haopeng Sun
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
| | - Wei Li
- Department of Medicinal Chemistry, School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, Jiangsu 211198, China
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Sun Z, Liu X, Wang F, Sun J, Sui Y, Che Q, Shu Q. POS0558 A INFLAMMATORY FACTOR-BASED NOMOGRAM PREDICTS FIRST REMISSION TIME OF RHEUMATOID ARTHRITIS PATIENTS WITH BASELINE GALECTIN-9. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BackgroundRheumatoid arthritis (RA) is an autoimmune disease. The core treatment principle of RA is to achieve remission or low disease activity as soon as possible to ensure optimal outcomes. Predicting the first remission time according to the patient’s risk factors is very important for the choice of treatment scheme.ObjectivesWe aimed to verify the prognostic value of inflammatory factors in RA and establish a nomogram based on Human Interleukin-6(IL-6), Galectin-9(Gal-9)and disease activity to predict the first remission time after conventional synthetic DMARDstreatment.Methods184 RA active patients(DAS28-ESR> 3.2, ACR 1987 criteria or EULAR 2010 criteria) were enrolled in the rheumatology department of Qilu Hospital of Shandong University from June 2014 to June 2020.129 patients were assigned to the development cohort and 55 patients were assigned to the validation cohort randomly. Baseline clinical data and plasma were collected. The expressions of Tumour Necrosis Factor α (TNF-α), Vascular Endothelial Growth Factor (VEGF), IL-6 and Gal-9 in plasma of RA patients were detected by ELISA. All patients were treated with csDMARDs and we recorded activity of each follow-up visit until 36 months. Lasso regression and Cox regression analysis were used to screen the 14 variables (including activity indices and cytokines) at baseline, and the prediction model was established to draw the nomogram.ResultsPatient age, CRP, IL-6, Gal-9, HAQ and DAS28-ESR were the significant prognostic factors in the lasso and Cox regression analyses, especially Gal-9. The multivariate analysis revealed that IL-6≤ 9.04 pg/ml(HR =0.54, 95% CI:0.31–0.95), Gal-9≤ 4490 pg/ml(HR =0.43, 95% CI:0.21–0.89) were independent protective factors (Table 1). Above-mentioned six factors were included in our model as predictors (Figure 1). The resulting model containing six factors had good discrimination ability in both the development cohort (C-index, 0.729) and the validation cohort (C-index, 0.710). Time-dependent ROC curve (Figure 2), calibration analysis (Figure 3) and decision curve analysis (DCA) show that the nomogram has significant discriminant power, stability and clinical practicability in predicting the first remission time.ConclusionWe constructed and validated a nomogram with baseline activity indices and cytokines that can predict first remission time in RA patients after csDMARDs treatment. Using this simple-to-use model with plasma Gal-9 at baseline, the remission rate can be determined for an individual patient and could be useful for the early identification of high-risk patients.References[1]SUN J, SUI Y, WANG Y, et al. Galectin-9 expression correlates with therapeutic effect in rheumatoid arthritis [J]. Scientific reports, 2021, 11(1): 5562.[2]ZHANG L, CHEN F, GENG S, et al. Methotrexate (MTX) Plus Hydroxychloroquine versus MTX Plus Leflunomide in Patients with MTX-Resistant Active Rheumatoid Arthritis: A 2-Year Cohort Study in Real World [J]. Journal of inflammation research, 2020, 13: 1141-50.[3]FORNARO M, CACCIAPAGLIA F, LOPALCO G, et al. Predictors of long-term clinical remission in rheumatoid arthritis [J]. European journal of clinical investigation, 2021, 51(2): e13363.AcknowledgementsFunded by ECCM Program of Clinical Research Center of Shandong University (No. 2021SDUCRCB010)Disclosure of InterestsNone declared.
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Wang H, Che Q, Chen J, Zhang Y, Shu Q. POS0555 THE NON-APOPTOTIC PROGRAMMED-CELL-DEATH-RELATED SIGNATURE PREDICTS ANTI-TNF THERAPY NONRESPONSE IN PATIENTS WITH RHEUMATOID ARTHRITIS. Ann Rheum Dis 2022. [DOI: 10.1136/annrheumdis-2022-eular.3416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
BackgroundEULAR guideline in rheumatoid arthritis (RA) recommended the primary failure of the first-line conventional synthetic modifying anti-rheumatic drugs (csDMARDs) patients switching to tumor necrosis factor alpha inhibitors (TNFi) [1]. Nevertheless, approximately 30-40% csDMARDs-IR patients also experience inefficacy of TNFi [2]. There is still no index to predict whether TNFi would be responded or not. Moreover, only few studies had focused on the relationship between TNFi nonresponse and other cell programmed deaths except apoptosis.ObjectivesTo predict the possibility of TNFi response prior to prescript in RA patients with the biomarkers of non-apoptotic programmed cell death in synovial cells.MethodsThe datasets of 22 TNFi treated RA synovial samples were enrolled from the Gene Expression Omnibus (GEO) database (GSE140036 and GSE15602). And the differentially expressed genes (DEGs) and modules related to TNFi treatment through weight gene correlation network analysis (WGCNA) were identified with the R packages “limma” and “WGCNA”. Then the enrichment analysis among the shared genes was performed through the R.4.1.2, Metascape website, and WebGestalt website. Following with the confirmation of the non-apoptotic programmed cell death (NAPCD) genes in the shared genes with Student’s T-Test. Furthermore, the TNFi treatment cohort was clustered based on the hub genes, making the receiver operating characteristic (ROC) curve analysis. Moreover, the least absolute shrinkage and selection operator (LASSO) model was constructed to identify the predictive genes.Results2624 DEGs were identified significantly, including 161 upregulated genes and 2463 downregulated genes. One module with TNFi treatment was constructed in WGCNA, significant in both response and nonresponse. Then the gene signatures for TNFi nonresponse were collected from overlaps 2260 genes in above. And we found 38 NAPCD genes might play role in TNFi nonresponse, but reserved 33 genes which statistically significant with T-Test. 22 TNFi treated synovial samples in GEO database could be classified into response or nonresponse subgroups. The ROC curve showed that the AUC for 32 genes in these samples ranged from 0.7 to 0.9, expected for CD46. At last, the LASSO model indicated that CASP5, CAPN10, ITGB4, NLRP2, and SLC2A8 could predict the TNFi nonresponse, as the risk score = CASP5 × 0.028 + CAPN10 × 0.064 + ITGB4× 0.080+ NLRP2 × 0.317+ SLC2A8 × 0.090 (Figure 1).Figure 1.Predictive model of TNFi nonresponse based on NAPCD genes. (A) Volcano map of differential expressed genes; (B) Correlation heat map of gene modules and phenotypes, the red is positively correlated with the phenotype, blue is negatively correlated with the phenotype; (C) The shared 38 genes of TNFi response & nonresponse DEGs, among the WGCNA turquoise module and cell programmed death genes; (D) Consensus clustering matrix for k = 2; (E) The ROC curve of 33 genes; (F) LASSO regression of the 32 genes,except for CD46; (G) Nomogram for predicting TNFi nonresponse in TNFi treatment RA cohort, indicated five possible indicators (CASP5, CAPN10, ITGB4, NLRP2, and SLC2A8) were closely related to TNFi nonresponse.ConclusionOur study firstly screened out the 38 NAPCD candidate genes signatures in RA synovial tissues which took part in TNFi nonresponse through WGCNA and DEGs. Further analysis confirmed that five possible indicators (CASP5, CAPN10, ITGB4, NLRP2, and SLC2A8) were closely related to TNFi nonresponse.References[1]van Delft MAM, Huizinga TWJ: An overview of autoantibodies in rheumatoid arthritis. Journal of autoimmunity 2020, 110:102392.[2]Aletaha D: Precision medicine and management of rheumatoid arthritis. Journal of autoimmunity 2020, 110:102405.AcknowledgementsFunded by ECCM Program of Clinical Research Center of Shandong University.Disclosure of InterestsNone declared.
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Li Y, Koike K, Che Q, Yamaguchi M, Takahashi S. Changes in lactate dehydrogenase and 3-hydroxyacetyl-CoA dehydrogenase activities in rat skeletal muscle by the administration of Eucommia ulmoides OLIVER leaf with spontaneous running-training. Biol Pharm Bull 1999; 22:941-6. [PMID: 10513617 DOI: 10.1248/bpb.22.941] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
We examined the effect of Eucommia ulmoides OLIVER leaf on rat skeletal muscles together with spontaneous running-training in terms of the isozyme profile and specific activity of lactate dehydrogenase (LDH; EC 1.1.1.27) and 3-hydroxyacetyl-CoA dehydrogenase (HAD; EC 1.1.1.35). On the twenty-ninth day of the experimental period, a mandatory endurance running exercise (treadmill, 7 degrees grade) was conducted. Twenty-four hours later, the rats were sacrificed and the skeletal muscles and other organs were dissected. Due to the training, the HAD specific activity in the skeletal muscles had increased and a more oxidative metabolism had developed, which was further enhanced by the administration of the leaf. In soleus (SOL) muscle in the Eucommia leaf treated running-training group (ET), the LDH specific activity in the skeletal muscle was significantly higher than in the sedentary control group (SC). The isozyme profile of the group ET was significantly different when compared with the group SC. The changes in the LDH isozyme profile were larger in the SOL than that in extensor digitorum longus (EDL) muscle. The results show that mechanical training and the use of the leaf cooperatively increase the ability to avoid lactate accumulation in skeletal muscle. This effect is supported by the group where 67% of rats accomplished the endurance running exercise. Theses results suggest that the administration of Eucommia ulmoides OLIVER leaf along with light intensity training enhances the ability of a muscle to resist fatigue.
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Affiliation(s)
- Y Li
- Biochemistry Laboratory, College of Pharmacy, Nihon University, Funabashi, Chiba, Japan
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Li Y, Che Q. [Studies on chemical components of Carthamus tinctorius petals]. Yao Xue Xue Bao 1998; 33:626-8. [PMID: 12016905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
The flower petals of Carthamus tinctorius L. (Compositae) provide one of the most important drugs in traditional Chinese medicine[1] used for the treatment of gynecological diseases, heart diseases and inflammation[2]. Carthamin, safflor yellows A and B, safflomin A, and C, isocarthamin, isocarthamidin, hydroxysafflor yellow A, and tinctormine have been reported from these petals, as well as several new flavonoids and phenolic compounds[3]. A continuation of these studies has led to the isolation of four compounds including a new flavonoid glucoside. The dried petals of C. tinctorius, cultivated in Sichuan, China, were extracted with 95% ethanol, and the extract was partitioned between H2O and organic solvents (petroleum ether and EtOAc). The water fraction was subjected to Diaion D101 and Sephadex LH-20 column chromatography with elution by a gradient of EtOH in water to yield compounds 1-4. Compound I is 6-hydroxykaempferol 3-O-glucoside, compound II is a new compound named 6-hydroxykaempferol 7-O-glucoside, compound 3 is kaempferol 3-O-rutinoside and compound 4 is quercetin 3-O-glucoside.
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Affiliation(s)
- Y Li
- Department of Natural Medicines, School of Pharmaceutical Sciences, Bijing Medical University, Beijing 100083
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