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)

We present a computational protocol which uses the known three-dimensional structure of a target enzyme to identify possible ligands from databases of compounds with low molecular weight. This is accomplished by first mapping the essential interactions in the binding site with the program GRID. The resulting regions of favorable interaction between target and ligand are translated into a database query, and with UNITY a flexible 3D database search is performed. The feasibility of this approach is calibrated with thrombin as the target. Our results show that the resulting hit lists are enriched with thrombin inhibitors compared to the total database.
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PMID:Computer based screening of compound databases: 1. Preselection of benzamidine-based thrombin inhibitors. 1089 14

We present a computational procedure aimed at understanding enzyme selectivity and guiding the design of drugs with respect to selectivity. It starts from a set of 3D structures of the target proteins characterized by the program GRID. In the multivariate description proposed, the variables are organized and scaled in a different way than previously published methodologies. Then, consensus principal component analysis (CPCA) is used to analyze the GRID descriptors, allowing the straightforward identification of possible modifications in the ligand to improve its selectivity toward a chosen target. As an important new feature the computational method is able to work with more than two target proteins and with several 3D structures for each protein. Additionally, the use of a 'cutout tool' allows to focus on the important regions around the active site. The method is validated for a total number of nine structures of the three homologous serine proteases thrombin, trypsin, and factor Xa. The regions identified by the method as being important for selectivity are in excellent agreement with available experimental data and inhibitor structure-activity relationships.
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PMID:GRID/CPCA: a new computational tool to design selective ligands. 1095 11

Pastor and Cruciani [J. Med. Chem. 38 (1995) 4637] and Kastenholz et al. [J. Med. Chem. 43 (2000) 3033] pioneered methods for comparing related receptors, with the ultimate goal of designing selective ligands. Such methods start with a reasonable superposition of high-resolution three-dimensional (3D) structures of the receptors. Next, molecular field maps are calculated for each receptor. Then the maps are analyzed to determine which map features are correlated with a particular subset of receptors. We present a method FLOGTV, based on the trend vector paradigm [J. Chem. Inf. Comput. Sci. 25 (1985) 64] to perform the analysis. This is mathematically simpler than the GRID/CPCA method of Kastenholz et al. and allows for the simultaneous comparison of many receptor structures. Also, the trend vector paradigm provides a method of selecting isopotential contours that are well above "noise". We demonstrate the method on four examples: HIV proteases versus two-domain acid proteases, thrombin versus trypsin and factor Xa, bacterial dihydrofolate reductases (DHFRs) versus vertebrate DHFRs, and P38 versus ERK protein kinases.
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PMID:A simple method for visualizing the differences between related receptor sites. 1246 40

Pastor and Cruciani [J. Med. Chem. 38 (1995) 4637] and Kastenholz et al. [J. Med. Chem. 43 (2000) 3033] pioneered methods for comparing related receptors, with the ultimate goal of designing selective ligands. Such methods start with a reasonable superposition of high-resolution three-dimensional (3D) structures of the receptors. Next, molecular field maps are calculated for each receptor. Then the maps are analyzed to determine which map features are correlated with a particular subset of receptors. We present a method FLOGTV, based on the trend vector paradigm [J. Chem. Inf. Comput. Sci. 25 (1985) 64] to perform the analysis. This is mathematically simpler than the GRID/CPCA method of Kastenholz et al. and allows for the simultaneous comparison of many receptor structures. Also, the trend vector paradigm provides a method of selecting isopotential contours that are well above "noise". We demonstrate the method on four examples: HIV proteases versus two-domain acid proteases, thrombin versus trypsin and factor Xa, bacterial dihydrofolate reductases (DHFRs) versus vertebrate DHFRs, and P38 versus ERK protein kinases.
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PMID:A simple method for visualizing the differences between related receptor sites. 1241 33

Mona, also called Gads, is a molecular adapter that plays a key role in T-cell and platelet signalling by linking the adaptors Src homology 2 domain-containing leukocyte phosphoprotein of 76 kDa (Slp-76) and linker for activation of T cells (LAT) upon T-cell receptor and collagen receptor activation. Platelets express a specific form of Mona mRNA, called 1B, which is transcribed from a megakaryocyte-specific promoter. Mona 1B mRNA differ from 1A transcripts found in T cells and some myeloid cells only by the 5'UTR. We report here that 1B mRNA expressing cells do not express detectable amounts of Mona protein, in contrast to 1A expressing cells, and we show that 1B 5'UTR contains upstream open reading frames (uORFs). Mutating the corresponding uAUG restored efficient Mona translation, or that of an unrelated ORF. This suggested that Mona protein expression in 1B mRNA expressing cells is tightly controlled at the translational level. Accordingly, Mona protein was not detected in resting platelets. Strikingly, platelet activation by thrombin resulted in the rapid induction of Mona protein expression, suggesting that translation inhibition of 1B mRNA may be relieved in activated platelets.
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PMID:Upstream open reading frames regulate translation of Mona/Gads adapter mRNA in the megakaryocytic lineage. 1248 79

Thrombin inhibitors are potentially useful in medicine for their anticoagulant and antithrombotic effects. We synthesized and evaluated diverse heterocycle-activated ketones based on the d-Phe-Pro-Arg, and related thrombin active-site recognition motifs, as candidate inhibitors. The peptide-based alpha-ketoheterocycles were typically prepared by either an imidate or a Weinreb amide route (Schemes 1 and 2), the latter of which proved to be more general. Test compounds were generally assayed for inhibition of human alpha-thrombin and bovine trypsin. From a structure-based design standpoint, the heterocycle allows one to explore and adjust interactions within the S1' subsite of thrombin. The preferred alpha-ketoheterocycle is a pi-rich 2-substituted azole with at least two heteroatoms proximal to the carbon bearing the keto group, and a preferred thrombin inhibitor is 2-ketobenzothiazole 3, with a potent K(i) value of 0.2 nM and ca. 15-fold selectivity over trypsin. 2-Ketobenzothiazole 13 exhibited exceedingly potent thrombin inhibition (K(i) = 0.000 65 nM; slow tight binding). Several alpha-ketoheterocycles had thrombin K(i) values in the range 0.1-400 nM. The "Arg" unit in the alpha-ketoheterocycles can be sensitive to stereomutation under mildy basic conditions. For example, 2-ketothiazoles 4 and 59 readily epimerize at pH 7.4, although they are fairly stable stereochemically at pH 3-4; thus, suitable conditions had to be selected for the enzymatic assays. Lead d-Phe-Pro-Arg 2-benzothiazoles 3, 4, and 68 displayed good selectivity for thrombin over other key coagulation enzymes (e.g., factor Xa, plasmin, protein Ca, uPA, tPA, and streptokinase); however, their selectivity for thrombin over trypsin was modest (<25-fold). Compounds 3, 4, and 68 exhibited potent in vitro antithrombotic activity as measured by inhibition of gel-filtered platelet aggregation induced by alpha-thrombin (IC(50) = 30-40 nM). They also proved to be potent anticoagulant/antithrombotic agents in vivo on intravenous administration, as determined in the canine arteriovenous shunt (ED(50) = 0.45-0.65 mg/kg) and the rabbit deep vein thrombosis (ED(50) = 0.1-0.4 mg/kg) models. Intravenous administration of 3, and several analogues, to guinea pigs caused hypotension and electrocardiogram abnormalities. Such cardiovascular side effects were also observed with some nonguanidine inhibitors and inhibitors having recognition motifs other than d-Phe-Pro-Arg. 2-Benzothiazolecarboxylates 4 and 68 exhibited significantly diminished cardiovascular side effects, and benzothiazolecarboxylic acid 4 had the best profile with respect to therapeutic index. The X-ray crystal structures of the ternary complexes 3-thrombin-hirugen and 4-thrombin-hirugen depict novel interactions in the S(1)' region, with the benzothiazole ring forming a hydrogen bond with His-57 and an aromatic stacking interaction with Trp-60D of thrombin's insertion loop. The benzothiazole ring of 3 displaces the Lys-60F side chain into a U-shaped gauche conformation, whereas the benzothiazole carboxylate of 4 forms a salt bridge with the side chain of Lys-60F such that it adopts an extended anti conformation. Since 3 has a 10-fold greater affinity for thrombin than does 4, any increase in binding energy resulting from this salt bridge is apparently offset by perturbations across the enzyme (viz. Figure 4). The increased affinity and selectivity of 2-ketobenzothiazole inhibitors, such as 3, may be primarily due to the aromatic stacking interaction with Trp-60D. However, energy contour calculations with the computer program GRID also indicate a favorable interaction between the benzothiazole sulfur atom and a hydrophobic patch on the surface of thrombin.
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PMID:In-depth study of tripeptide-based alpha-ketoheterocycles as inhibitors of thrombin. Effective utilization of the S1' subsite and its implications to structure-based drug design. 1577 42

In this study, a set of strategies for structure-based design using GRID molecular interaction fields (MIFs) to derive a pharmacophoric representation of a protein is reported. Thrombin, one of the key enzymes involved in the blood coagulation cascade, was chosen as the model system since abundant published experimental data are available related to both crystal structures and structurally diverse sets of inhibitors. First, a virtual screening methodology was developed either using a pharmacophore representation of the protein based on GRID MIFs or using GRID MIFs from the 3D structure of a set of chosen thrombin inhibitors. The search was done in a 3D multiconformation version of the Available Chemical Directory (ACD) database, which had been spiked with 262 known thrombin inhibitors (multiple conformers available per compound). The model managed to find 80% of the known thrombin inhibitors among the 74,291 conformers in the ACD by only searching 5% of the database; hence, a 15-fold enrichment of the library was achieved. Second, a scaffold hopping methodology was developed using GRID MIFs, giving the scaffold interaction pattern and the shape of the scaffold, together with the distance between the anchor points. The scaffolds reported by Dolle in the Journal of Combinatorial Chemistry summaries (2000 and 2001) and scaffolds built or derived from ligands cocomplexed with the thrombin enzyme were parameterized using a new set of descriptors and saved into a searchable database. The scaffold representation from the database was then compared to a template scaffold (from a thrombin crystal structure), and the thrombin-derived scaffolds included in the database were found among the top solutions. To validate the usefulness of the methodology to replace the template scaffold, the entire molecule was built (scaffold and side chains) and the resulting compounds were docked into the active site of thrombin. The docking solutions showed the same binding pattern as the cocomplexed compound, hence, showing that this method can be a valuable tool for medicinal chemists to select interchangeable core structures (scaffolds) in an easy manner and retaining the binding properties from the original ligand.
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PMID:Virtual screening and scaffold hopping based on GRID molecular interaction fields. 1618 Sep 8

A new GRID-based method for scaffold hopping (SHOP) is presented. In a fully automatic manner, scaffolds were identified in a database based on three types of 3D-descriptors. SHOP's ability to recover scaffolds was assessed and validated by searching a database spiked with fragments of known ligands of three different protein targets relevant for drug discovery using a rational approach based on statistical experimental design. Five out of eight and seven out of eight thrombin scaffolds and all seven HIV protease scaffolds were recovered within the top 10 and 31 out of 31 neuraminidase scaffolds were in the 31 top-ranked scaffolds. SHOP also identified new scaffolds with substantially different chemotypes from the queries. Docking analysis indicated that the new scaffolds would have similar binding modes to those of the respective query scaffolds observed in X-ray structures. The databases contained scaffolds from published combinatorial libraries to ensure that identified scaffolds could be feasibly synthesized.
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PMID:SHOP: scaffold HOPping by GRID-based similarity searches. 1748 78

A novel approach was developed to rationally interface structure- and ligand-based drug design through the rescoring of docking poses and automated generation of molecular alignments for 3D quantitative structure-activity relationship investigations. The procedure was driven by a genetic algorithm optimizing the value of a novel fitness function, accounting simultaneously for best regressions among binding-energy docking scores and affinities and for minimal geometric deviations from properly established crystal-based binding geometry. The GRID/CPCA method, as implemented in GOLPE, was used to feature molecular determinants of ligand binding affinity for each molecular alignment. In addition, unlike standard procedures, a novel multipoint equation was adopted to predict the binding affinity of ligands in the prediction set. Selectivity was investigated through square plots reporting experimental versus recalculated binding affinities on the targets under examination. The application of our approach to the modeling of affinity data of a large series of 3-amidinophenylalanine inhibitors of thrombin, trypsin, and factor Xa generated easily interpretable and independent models with robust statistics. As a further validation study, our approach was successfully applied to a series of 3,4,7-substituted coumarins, acting as selective MAO-B inhibitors.
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PMID:An integrated approach to ligand- and structure-based drug design: development and application to a series of serine protease inhibitors. 1854 May 90

A multiobjective optimization algorithm was proposed for the automated integration of structure- and ligand-based molecular design. Driven by a genetic algorithm, the herein proposed approach enabled the detection of a number of trade-off QSAR models accounting simultaneously for two independent objectives. The first was biased toward best regressions among docking scores and biological affinities; the second minimized the atom displacements from a properly established crystal-based binding topology. Based on the concept of dominance, 3D QSAR equivalent models profiled the Pareto frontier and were, thus, designated as nondominated solutions of the search space. K-means clustering was, then, operated to select a representative subset of the available trade-off models. These were effectively subjected to GRID/GOLPE analyses for quantitatively featuring molecular determinants of ligand binding affinity. More specifically, it was demonstrated that a) diverse binding conformations occurred on the basis of the ligand ability to profitably contact different part of protein binding site; b) enzyme selectivity was better approached and interpreted by combining diverse equivalent models; and c) trade-off models were successful and even better than docking virtual screening, in retrieving at high sensitivity active hits from a large pool of chemically similar decoys. The approach was tested on a large series, very well-known to QSAR practitioners, of 3-amidinophenylalanine inhibitors of thrombin and trypsin, two serine proteases having rather different biological actions despite a high sequence similarity.
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PMID:Improving quantitative structure-activity relationships through multiobjective optimization. 1978 53


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