Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: EC:2.7.1.21 (thymidine kinase)
 7,561 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

NO appears as an important determinant in auto and paracrine macrophage function. We hypothesized that NO switches monocyte/macrophage function from a pro- to an anti-inflammatory phenotype by activating anti-inflammatory properties of the peroxisome proliferator-activated receptor (PPAR)gamma. NO-releasing compounds (100 micro M S-nitrosoglutathione or 50 micro M spermine-NONOate) as well as inducible NO synthase induction provoked activation of PPARgamma. This was proven by EMSAs, with the notion that supershift analysis pointed to the involvement of PPARgamma. PCR analysis ruled out induction of PPARgamma mRNA as a result of NO supplementation. Reporter assays, with a construct containing a triple PPAR response element in front of a thymidine kinase minimal promoter driving the luciferase gene, were positive in response to NO delivery. DNA binding capacity as well as the transactivating capability of PPARgamma were attenuated by addition of the antioxidant N-acetyl-cysteine or in the presence of the NO scavenger 2-phenyl-4,4,5,6-tetramethyl-imidazoline-1-oxyl 3-oxide. Having established that NO but not lipophilic cyclic GMP analogs activated PPARgamma, we verified potential anti-inflammatory consequences. The oxidative burst of macrophages, evoked by phorbol ester, was attenuated in association with NO-elicited PPARgamma activation. A cause-effect relationship was demonstrated when PPAR response element decoy oligonucleotides, supplied in front of NO delivery, allowed to regain an oxidative response. PPARgamma-mediated down-regulation of p47 phagocyte oxidase, a component of the NAD(P)H oxidase system, was identified as one molecular mechanism causing inhibition of superoxide radical formation. We conclude that NO participates in controlling the pro- vs anti-inflammatory phenotype of macrophages by modulating PPARgamma.
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PMID:Activation of peroxisome proliferator-activated receptor gamma by nitric oxide in monocytes/macrophages down-regulates p47phox and attenuates the respiratory burst. 1219 33

Protein-ligand docking programs have been used to efficiently discover novel ligands for target proteins from large-scale compound databases. However, better scoring methods are needed. Generally, scoring functions are optimized by means of various techniques that affect their fitness for reproducing X-ray structures and protein-ligand binding affinities. However, these scoring functions do not always work well for all target proteins. A scoring function should be optimized for a target protein to enhance enrichment for structure-based virtual screening. To address this problem, we propose the supervised scoring model (SSM), which takes into account the protein-ligand binding process using docked ligand conformations with supervised learning for optimizing scoring functions against a target protein. SSM employs a rough linear correlation between binding free energy and the root mean square deviation of a native ligand for predicting binding energy. We applied SSM to the FlexX scoring function, that is, F-Score, with five different target proteins: thymidine kinase (TK), estrogen receptor (ER), acetylcholine esterase (AChE), phosphodiesterase 5 (PDE5), and peroxisome proliferator-activated receptor gamma (PPARgamma). For these five proteins, SSM always enhanced enrichment better than F-Score, exhibiting superior performance that was particularly remarkable for TK, AChE, and PPARgamma. We also demonstrated that SSM is especially good at enhancing enrichments of the top ranks of screened compounds, which is useful in practical drug screening.
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PMID:Supervised scoring models with docked ligand conformations for structure-based virtual screening. 1768 4

Since the evaluation of ligand conformations is a crucial aspect of structure-based virtual screening, scoring functions play significant roles in it. However, it is known that a scoring function does not always work well for all target proteins. When one cannot know which scoring function works best against a target protein a priori, there is no standard scoring method to know it even if 3D structure of a target protein-ligand complex is available. Therefore, development of the method to achieve high enrichments from given scoring functions and 3D structure of protein-ligand complex is a crucial and challenging task. To address this problem, we applied SCS (supervised consensus scoring), which employs a rough linear correlation between the binding free energy and the root-mean-square deviation (rmsd) of a native ligand conformations and incorporates protein-ligand binding process with docked ligand conformations using supervised learning, to virtual screening. We evaluated both the docking poses and enrichments of SCS and five scoring functions (F-Score, G-Score, D-Score, ChemScore, and PMF) for three different target proteins: thymidine kinase (TK), thrombin (thrombin), and peroxisome proliferator-activated receptor gamma (PPARgamma). Our enrichment studies show that SCS is competitive or superior to a best single scoring function at the top ranks of screened database. We found that the enrichments of SCS could be limited by a best scoring function, because SCS is obtained on the basis of the five individual scoring functions. Therefore, it is concluded that SCS works very successfully from our results. Moreover, from docking pose analysis, we revealed the connection between enrichment and average centroid distance of top-scored docking poses. Since SCS requires only one 3D structure of protein-ligand complex, SCS will be useful for identifying new ligands.
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PMID:Structure-based virtual screening with supervised consensus scoring: evaluation of pose prediction and enrichment factors. 1831 74

The effects of ghrelin on the proliferation and differentiation of 3T3-L1 preadipocytes and the possible mechanisms were investigated in this study. 3T3-L1 preadipocytes were cultured in vitro and treated with different concentrations of ghrelin. Proliferation of 3T3-L1 preadipocytes was evaluated by MTT method and mRNA levels of c-myc and thymidine kinase were detected by RT-PCR. Morphological changes of 3T3-L1 preadipocytes were observed and cell differentiation was measured by oil red O staining. The mRNA levels of peroxisome proliferator-activated receptor gamma (PPARgamma) and CAAT/enhancer binding protein (C/EBPalpha) in the cells at different differentiation stages were detected by RT-PCR. The results showed that ghrelin at concentrations of 10(-7) to 10(-15) mol/L could significantly promote preadipocyte proliferation (P<0.05), with the most pronounced effect observed at 10(-11) mol/L (P<0.01). Treatment of 3T3-L1 preadipocytes with ghrelin significantly increased the mRNA levels of c-myc and thymidine kinase (P<0.01). Morphological findings demonstrated that the great amount of lipid droplets appeared in the 3T3-L1 preadipocytes treated with ghrelin. Ghrelin could morphologically induce the differentiation of 3T3-L1 preadipocytes into mature adipocytes. Ghrelin significantly increased the mRNA levels of PPARgamma and C/EBPalpha during the differentiation, when compared with control group (P<0.05). The mRNA levels of PPARgamma and C/EBPalpha were obviously up-regulated with the differentiation of preadipocytes after the treatment of ghrelin. There were significant difference in the mRNA levels of PPARgamma and C/EBPalpha on day 2 and day 8 of the differentiation of 3T3-L1 preadipocytes (P<0.01). In conclusion, ghrelin could promote the proliferation and differentiation of 3T3-L1 preadipocytes by increasing the mRNA levels of PPARgamma and C/EBPalpha and therefore enhance the sensitivity of adipocytes against insulin.
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PMID:Effects of ghrelin on the proliferation and differentiation of 3T3-L1 preadipocytes. 1939 10