Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound   Target Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound

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Query: EC:3.4.21.5 (thrombin)
33,306 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The mouse mammary tumor virus (MMTV) protease gene was cloned into pGEX-2T, an Escherichia coli expression vector containing the glutathione S-transferase coding region of Schistosoma japonicum. The chimeric protein was formed by fusion of the glutathione S-transferase with a hexapeptide which contains a thrombin cleavage site, followed by the MMTV protease. Affinity chromatography on a glutathione-Sepharose 4B column was used to isolate the chimeric protein. After thrombin cleavage, the glutathione S-transferase and the protease were separated by gel filtration chromatography on a Sephadex G-75 column. The overall yield of the protease purification procedure was about 1 mg of protease/liter of culture, and the specific activity was 380 pmol/min.micrograms of enzyme. Like other retroviral proteases, the MMTV enzyme was active as a dimer, showed maximum activity at pH between 4 and 6, and could be inhibited by pepstatin A and a phosphinic acid derivative HIV-1 protease inhibitor. Enzymatic characterization of this protease reveals its broad specificity, showing a clear preference for the oligopeptide substrate mimicking the cleavage site at the amino-terminal end of the capsid protein (kcat/Km = 9725.5 M-1.s-1). The chimeric protein was also an active dimer and showed a similar Km (17 microM) for such an oligopeptide, although its kcat was about 10 times smaller. Autocatalytic processing of the MMTV protease was observed after expression of clones containing the natural cleavage site, as it occurs at the amino-terminal end of the viral protease, instead of the thrombin-sensitive sequence.
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PMID:Purification and characterization of the mouse mammary tumor virus protease expressed in Escherichia coli. 133 Nov 10

The high-molecular-weight dendritic cytoskeletal protein known as microtubule-associated protein (MAP)-2 displays the capacity to stimulate tubulin polymerization and to associate with microtubules. Serine proteases cleave MAP-2 into a C-terminal M(r) 28,000-35,000 microtubule-binding fragment and a larger N-terminal M(r) 240,000 projection-arm region. We now show that human immunodeficiency virus (HIV) proteinase also progressively degrades purified MAP-2 in vitro. This proteolysis reaction is characterized by transient accumulation of at least six intermediates, and most abundant of these is an M(r) 72,000 species that retains the ability to associate with taxol-stabilized microtubules. Treatment of this M(r) 72,000 species with thrombin releases the same M(r) 28,000 component as that derived from thrombin action on intact high-molecular-weight MAP-2, indicating that the viral aspartoproteinase action preferentially occurs further toward the N-terminus. The association of the M(r) 72,000 component with microtubules can be disrupted by the presence of a 21-amino acid peptide analogue of the second repeated sequence in the MAP-2 microtubule-binding region. We also studied HIV proteinase action on MAP-2 in the presence of tubulin and other MAPs that recycle with tubulin, and contrary to other published studies we found no effect of such treatment on microtubule self-assembly behavior. Cleavage of isolated MAP-2 by the HIV enzyme at high salt concentrations, followed by desalting and addition of tubulin, also resulted in microtubule assembly, albeit with slightly reduced efficiency.
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PMID:Cleavage of bovine brain microtubule-associated protein-2 by human immunodeficiency virus proteinase. 149 13

The Moloney murine leukemia virus (Mo-MuLV) protease has been cloned into the prokaryotic expression vector pGEX-2T, expressed in fusion with the glutathione S-transferase from Schistosoma japonicum, and purified to apparent homogeneity after thrombin cleavage of the chimeric protein. The purified protease showed maximum activity at pH 6.0 and was inhibited by several aspartyl protease inhibitors, found to be active toward the human immunodeficiency virus-1 (HIV-1) protease. Peptides representing maturation cleavage sites in Gag and Gag-Pol polyproteins were accurately cleaved by the recombinant protease, and kinetic parameters have been determined. In addition, oligopeptides mimicking the cleavage site found in the transmembrane protein and leading to the formation of p15E and p2E were also hydrolyzed at the expected position. The Mo-MuLV protease appears to be more closely related to the HIV-1 protease than to the mouse mammary tumor virus enzyme, based on its substrate specificity and sensitivity to aspartyl protease inhibitors.
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PMID:Moloney murine leukemia virus protease: bacterial expression and characterization of the purified enzyme. 837 34

The interaction of novel series of synthetic inhibitors with various serine proteases (leukocyte elastase, thrombin, cathepsin G, chymotrypsin, plasminogen activators and plasmin) and an aspartic protease (HIV-1 protease) were studied. Various aspects were analyzed: mechanism of action, structure-activity relationships, and in some cases, molecular modelling and biological evaluation. Functionalized cyclopeptides and N-aryl azetidin-2-ones behaved as suicide substrates acting specifically on trypsin-like proteases (thrombin or urokinase) and elastases, respectively. Novel hydrazinopeptides acted as reversible inhibitors of elastases. Coumarin derivatives inactivated very efficiently chymotrypsin-like proteases (k(inact)/K(I) = 760,000 M(-1) .s(-1)). Inhibitors of HIV-1 protease acting either as inactivators or dimerization inhibitors are under investigation. The inhibitors described above are useful for elucidating the biological roles of the target enzymes and constitute potential drugs.
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PMID:[Synthetic inhibitors targeting serine and aspartic acid proteases]. 877 49

Structure-based design has emerged as a new tool in medicinal chemistry. A prerequisite for this new approach is an understanding of the principles of molecular recognition in protein-ligand complexes. If the three-dimensional structure of a given protein is known, this information can be directly exploited for the retrieval and design of new ligands. Structure-based ligand design is an iterative approach. First of all, it requires the crystal structure or a model derived from the crystal structure of a closely related homolog of the target protein, preferentially complexed with a ligand. This complex unravels the binding mode and conformation of a ligand under investigation and indicates the essential aspects determining its binding affinity. It is then used to generate new ideas about ways of improving an existing ligand or of developing new alternative bonding skeletons. Computational methods supplemented by molecular graphics are applied to assist this step of hypothesis generation. The features of the protein binding pocket can be translated into queries used for virtual computer screening of large compound libraries or to design novel ligands de novo. These initial proposals must be confirmed experimentally. Subsequently they are optimized toward higher affinity and better selectivity. The latter aspect is of utmost importance in defining and controlling the pharmacological profile of a ligand. A prerequisite to tailoring selectivity by rational design is a detailed understanding of molecular parameters determining selectivity. Taking examples from current drug development programs (HIV proteinase, t-RNA transglycosylase, thymidylate synthase, thrombin and, related serine proteinases), we describe recent advances in lead discovery via computer screening, iterative design, and understanding of selectivity discrimination.
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PMID:Recent developments in structure-based drug design. 1095 96

A new computational approach for the efficient docking of flexible ligands in a rigid protein is presented. It exploits the binding modes of functional groups determined by an exhaustive search with solvation. The search in ligand conformational space is performed by a genetic algorithm whose scoring function approximates steric effects and intermolecular hydrogen bonds. Ligand conformations generated by the genetic algorithm are docked in the protein binding site by optimizing the fit of their fragments to optimal positions of chemically related functional groups. We show that the use of optimal binding modes of molecular fragments allows to dock known inhibitors with about ten rotatable bonds in the active site of the uncomplexed and complexed conformations of thrombin and HIV-1 protease.
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PMID:Fragment-Based flexible ligand docking by evolutionary optimization. 1168 19

An improved version of the fragment-based flexible ligand docking approach SEED-FFLD is tested on inhibitors of human immunodeficiency virus type 1 protease, human alpha-thrombin and the estrogen receptor beta. The docking results indicate that it is possible to correctly reproduce the binding mode of inhibitors with more than ten rotatable bonds if the strain in their covalent geometry upon binding is not large. A high degree of convergence towards a unique binding mode in multiple runs of the genetic algorithm is proposed as a necessary condition for successful docking.
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PMID:Automated docking of highly flexible ligands by genetic algorithms: a critical assessment. 1469 75

This paper introduces a new strategy for structure-based drug design that combines high-quality docking with data from existing ligand-protein cocrystal X-ray structures. The main goal of SDOCKER, a new algorithm that implements this strategy, is docking accuracy improvement. In this new paradigm, simulated annealing molecular dynamics is used for conformational sampling and optimization and an additional similarity force is applied on the basis of the positions of ligands from X-ray data that focus the sampling on relevant regions of the active site. Because the structural information from both the ligand and protein active site is included, this approach is more effective in finding the optimal conformation for a ligand-protein complex than the classical docking or similarity overlays. Interestingly, it was found that a 3D similarity-only approach gives comparable docking accuracy to the regular force field approach used in classical docking, given the final structures are minimized in the presence of the protein. The combination of both, as implemented in SDOCKER, is shown here to be more accurate. A significant improvement in docking accuracy has been observed for three different test systems. Specifically an improvement of 10%, 17.5%, and 10% is seen for 37 HIV-1 protease, 32 thrombin, and 23 CDK2 ligands, respectively, compared to docking using the force field alone. In addition, SDOCKER's accuracy performance dependence on the similarity template is discussed. The strategy of utilizing existing ligand X-ray information should prove effective in light of the multitude of structures available from structural genomics approaches.
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PMID:SDOCKER: a method utilizing existing X-ray structures to improve docking accuracy. 1516 94

"Getting it right" refers to the careful modeling of all elements in the living system, i.e. biological macromolecules, ligands and water molecules. In addition, careful attention should be paid to the protonation state of ionizable functional groups on the ligands and residues at the active site. Computational technology based on the empirical HINT program is described to: (1) calculate free energy scores for ligand binding; (2) include the implicit and explicit effects of water in and around the ligand binding site; and (3) incorporate the effects of global and local pH in molecular models. This last point argues for the simultaneous consideration of a number of molecular models, each with different protonation profiles. Data from recent studies of protein-ligand systems (trypsin, thrombin, neuraminidase, HIV-1 protease and others) are used to illustrate the concepts in the paper. Also discussed are experimental factors related to accurate free energy predictions with this and other computational technologies.
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PMID:Getting it right: modeling of pH, solvent and "nearly" everything else in virtual screening of biological targets. 1518 7

The ability to find novel bioactive scaffolds in compound similarity-based virtual screening experiments has been studied comparing Tanimoto-based, ranking-based, voting, and consensus scoring protocols. Ligand sets for seven well-known drug targets (CDK2, COX2, estrogen receptor, neuraminidase, HIV-1 protease, p38 MAP kinase, thrombin) have been assembled such that each ligand represents its own unique chemotype, thus ensuring that each similarity recognition event between ligands constitutes a scaffold hopping event. In a series of virtual screening studies involving 9969 MDDR compounds as negative controls it has been found that atom pair descriptors and 3D pharmacophore fingerprints combined with ranking, voting, and consensus scoring strategies perform well in finding novel bioactive scaffolds. In addition, often superior performance has been observed for similarity-based virtual screening compared to structure-based methods. This finding suggests that information about a target obtained from known bioactive ligands is as valuable as knowledge of the target structures for identifying novel bioactive scaffolds through virtual screening.
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PMID:Scaffold hopping through virtual screening using 2D and 3D similarity descriptors: ranking, voting, and consensus scoring. 1650 72


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