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)

We have studied the interaction of a chimeric construct containing an origin of replication (from bovine papilloma virus) and a hormonally regulated transcription unit (long terminal repeat from the mouse mammary tumor virus, driving the v-Ha-ras gene) with the nuclear scaffold and matrix from mouse fibroblasts. We used two experimental approaches because the nuclear matrix protein composition depends largely on the isolation conditions, making its definition mostly operational. In situ studies and in vitro experiments performed in 1361.5 cells, a cell line in which multiple copies of the construct have been established, indicate that two interesting regions of the construct interact with the nuclear matrix. The first region is located in the v-Ha-ras gene 5'-flanking sequences. These sequences come from the Harvey virus and contain a piece of the virus like 30S (VL30) sequences in which the v-Ha-ras gene is embedded. This DNA fragment was coupled to the thymidine kinase (TK) promoter driving the reporter luciferase gene and assayed in transient transfection experiments. Its insertion, in the sense orientation, upstream of the TK promoter resulted in a moderate enhancement (2-3-fold) of the luciferase activity. The second region is the most interesting from a physiological point of view. It contains the plasmid maintenance sequence 1 (PMS-1) and the core origin of replication of the bovine papilloma virus. Differences in the results from in situ (nuclear scaffold) and in vitro (nuclear matrix) experiments suggest that the components involved in the interaction with PMS-1 and the viral origin of replication are different. This may be of importance in the context of the recently proposed view that PMS-1 could be part of a composite origin of replication and provide information at a distance.
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PMID:Interaction with the nuclear matrix of a chimeric construct containing a replication origin and a transcription unit. 133 95

Virtual ligand screening methods based on the structure of the receptor are extensively used to facilitate the discovery of lead compounds. In the present study, we investigated the LigandFit package on four different proteins (coagulation factor VIIa, estrogen receptor, thymidine kinase, and neuraminidase), a relatively large compound collection of 65,560 unique "drug-like" molecules and four focused libraries (1950 molecules each). We performed virtual screening experiments with the large database and evaluated six scoring functions available in the package (DockScore, LigScore1, LigScore2, PLP1, PLP2, and PMF). The results showed that LigandFit is an efficient program, especially when used with LigScore1. Similar computations were carried out using focused libraries. In this situation the LigScore1 scoring function outperformed the other ones on three out of the four proteins tested. Even for the difficult neuraminidase case, the LigandFit/LigScore1 combination was still reasonably successful. Assessment of docking accuracy was also performed and again, we found that LigandFit (with DockScore and the CFF parameters) was performing well. On the basis of these results and observed increased enrichments after LigandFit/Ligscore1 screening on focused libraries, we suggest that using this program as a final step of a hierarchical protocol can be very beneficial to assist lead finding.
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PMID:Structure-based virtual ligand screening with LigandFit: pose prediction and enrichment of compound collections. 1751 Sep 58

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