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1.
Phys Rev Lett ; 116(1): 012501, 2016 Jan 08.
Article in English | MEDLINE | ID: mdl-26799013

ABSTRACT

We report the determination of the Q(EC) value of the mirror transition of (11)C by measuring the atomic masses of (11)C and (11)B using Penning trap mass spectrometry. More than an order of magnitude improvement in precision is achieved as compared to the 2012 Atomic Mass Evaluation (Ame2012) [Chin. Phys. C 36, 1603 (2012)]. This leads to a factor of 3 improvement in the calculated Ft value. Using the new value, Q(EC)=1981.690(61) keV, the uncertainty on Ft is no longer dominated by the uncertainty on the Q(EC) value. Based on this measurement, we provide an updated estimate of the Gamow-Teller to Fermi mixing ratio and standard model values of the correlation coefficients.

2.
Phys Rev Lett ; 114(23): 232502, 2015 Jun 12.
Article in English | MEDLINE | ID: mdl-26196795

ABSTRACT

We report the first direct measurement of the (14)O superallowed Fermi ß-decay QEC value, the last of the so-called "traditional nine" superallowed Fermi ß decays to be measured with Penning trap mass spectrometry. (14)O, along with the other low-Z superallowed ß emitter, (10)C, is crucial for setting limits on the existence of possible scalar currents. The new ground state QEC value, 5144.364(25) keV, when combined with the energy of the 0(+) daughter state, Ex(0(+))=2312.798(11) keV [F. Ajzenberg-Selove, Nucl. Phys. A523, 1 (1991)], provides a new determination of the superallowed ß-decay QEC value, QEC(sa)=2831.566(28) keV, with an order of magnitude improvement in precision, and a similar improvement to the calculated statistical rate function f. This is used to calculate an improved Ft value of 3073.8(2.8) s.

3.
Bioorg Med Chem Lett ; 20(9): 2832-6, 2010 May 01.
Article in English | MEDLINE | ID: mdl-20356739

ABSTRACT

The purpose of the work was to identify novel inhibitors of the enzyme NQO2. Using computational molecular modelling, a QSAR (R(2)=0.88) was established, relating inhibitory potency with calculated binding affinity. From this, the imidazoacridin-6-one, NSC660841, was identified as the most potent inhibitor of NQO2 yet reported (IC(50)=6 nM).


Subject(s)
Acridines/chemistry , Acridones/chemistry , Enzyme Inhibitors/chemistry , Imidazoles/chemistry , Quinone Reductases/antagonists & inhibitors , Acridines/pharmacology , Acridones/pharmacology , Binding Sites , Catalytic Domain , Computer Simulation , Databases, Factual , Enzyme Inhibitors/chemical synthesis , Enzyme Inhibitors/pharmacology , Humans , Imidazoles/pharmacology , Quantitative Structure-Activity Relationship , Quinone Reductases/metabolism , Thermodynamics
4.
Bioorg Med Chem Lett ; 13(21): 3705-9, 2003 Nov 03.
Article in English | MEDLINE | ID: mdl-14552762

ABSTRACT

Structure-based computational screening of the National Cancer Institute database of anticancer compounds identified novel non-nucleobase-derived inhibitors of human thymidine phosphorylase as candidates for lead optimization. The hierarchical in silico screening strategy predicted potentially strong low molecular weight ligands exhibiting a range of molecular scaffolds. Of the thirteen ligands assayed for activity, all displayed inhibitory activity against Escherichia coli thymidine phosphorylase. One compound, hydrazine carboxamide 2-[(1-methyl-2,5-dioxo-4-pentyl-4-imidazolidinyl)methylene], was found to inhibit E. coli thymidine phosphorylase with an IC(50) value of 20 microM and an IC(50) value of 77 microM against human thymidine phosphorylase. As this hydantoin derivative lacks the undesirable ionic sites of existing tight-binding nucleobase-derived inhibitors, such as 5-chloro-6-[(2-iminopyrrolidin-1-yl)methyl]uracil hydrochloride, it provides an opportunity for the design of potent thymidine phosphorylase inhibitors with improved pharmacokinetic properties.


Subject(s)
Enzyme Inhibitors/pharmacology , Escherichia coli/enzymology , Hydrazines/chemical synthesis , Hydrazines/pharmacology , Imidazoles/chemical synthesis , Imidazoles/pharmacology , Thymidine Phosphorylase/antagonists & inhibitors , Binding Sites , Computer Simulation , Crystallography, X-Ray , Databases, Genetic , Drug Design , Drug Evaluation, Preclinical , Humans , Kinetics , Models, Molecular , Recombinant Proteins/chemistry , Structure-Activity Relationship , Thymidine/metabolism
5.
Biophys J ; 81(3): 1373-88, 2001 Sep.
Article in English | MEDLINE | ID: mdl-11509352

ABSTRACT

Carbohydrate ligands are important mediators of biomolecular recognition. Microcalorimetry has found the complex-type N-linked glycan core pentasaccharide beta-GlcNAc-(1-->2)-alpha-Man-(1-->3)-[beta-GlcNAc-(1-->2)-alpha-Man-(1-->6)]-Man to bind to the lectin, Concanavalin A, with almost the same affinity as the trimannoside, Man-alpha-(1-->6)-[Man-alpha-(1-->3)]-Man. Recent determination of the structure of the pentasaccharide complex found a glycosidic linkage psi torsion angle to be distorted by 50 degrees from the NMR solution value and perturbation of some key mannose-protein interactions observed in the structures of the mono- and trimannoside complexes. To unravel the free energy contributions to binding and to determine the structural basis for this degeneracy, we present the results of a series of nanosecond molecular dynamics simulations, coupled to analysis via the recently developed MM-GB/SA approach (Srinivasan et al., J. Am. Chem. Soc. 1998, 120:9401-9409). These calculations indicate that the strength of key mannose-protein interactions at the monosaccharide site is preserved in both the oligosaccharides. Although distortion of the pentasaccharide is significant, the principal factor in reduced binding is incomplete offset of ligand and protein desolvation due to poorly matched polar interactions. This analysis implies that, although Concanavalin A tolerates the additional 6 arm GlcNAc present in the pentasaccharide, it does not serve as a key recognition determinant.


Subject(s)
Concanavalin A/metabolism , Oligosaccharides/metabolism , Acetylation , Calorimetry , Carbohydrate Conformation , Carbohydrate Sequence , Computer Simulation , Concanavalin A/chemistry , Entropy , Hydroxylation , Ligands , Methylation , Models, Molecular , Oligosaccharides/chemistry , Protein Binding , Protein Conformation , Solutions , Solvents/metabolism , Substrate Specificity , Thermodynamics
6.
J Mol Graph Model ; 18(4-5): 358-67, 526, 2000.
Article in English | MEDLINE | ID: mdl-11143555

ABSTRACT

Traditional de novo design algorithms are able to generate many thousands of ligand structures that meet the constraints of a protein structure, but these structures are often not synthetically tractable. In this article, we describe how concepts from structure-based de novo design can be used to explore the search space in library design. A key feature of the approach is the requirement that specific templates are included within the designed structures. Each template corresponds to the "central core" of a combinatorial library. The template is positioned within an acyclic chain whose length and bond orders are systematically varied, and the conformational space of each structure that results (core plus chain) is explored to determine whether it is able to link together two or more strongly interacting functional groups or pharmacophores located within a protein binding site. This fragment connection algorithm provides "generic" 3D molecules in the sense that the linking part (minus the template) is built from an all-carbon chain whose synthesis may not be easily achieved. Thus, in the second phase, 2D queries are derived from the molecular skeletons and used to identify possible reagents from a database. Each potential reagent is checked to ensure that it is compatible with the conformation of its parent 3D conformation and the constraints of the binding site. Combinations of these reagents according to the combinatorial library reaction scheme give product molecules that contain the desired core template and the key functional/pharmacophoric groups, and would be able to adopt a conformation compatible with the original molecular skeleton without any unfavorable intermolecular or intramolecular interactions. We discuss how this strategy compares with and relates to alternative approaches to both structure-based library design and de novo design.


Subject(s)
Combinatorial Chemistry Techniques , Drug Design , Algorithms , Computer Graphics , Computer Simulation , Indicators and Reagents , Ligands , Models, Molecular , Molecular Structure
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