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STUDIES ON RADIATION INDUCED CROSSLINKING OF CIS 1,4-POLYBUTADIENE BY ^(13)C NMR
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作者 赵新 杜有如 叶朝辉 《Nuclear Science and Techniques》 SCIE CAS CSCD 1994年第3期184-187,共4页
C NMR spin-lattice relaxation times (T1), line widths, nuclear Overhauser effects (NOE) at room temperature have been measured for radiated ets 1,4-polybutadiene.With the increase of radiation dose T1 is almost invari... C NMR spin-lattice relaxation times (T1), line widths, nuclear Overhauser effects (NOE) at room temperature have been measured for radiated ets 1,4-polybutadiene.With the increase of radiation dose T1 is almost invariant, but line width of the methylene (-CH2-) carbon increases remarkably, and its NOE factor decreases sharply. This implies that the long-range segmental motion is hindered, and saturated tertiary carbon (-C H- ) is formed during crosslinking of ets 1,4-polybutadiene. 展开更多
关键词 Asdiation induced crosslinking Cis 1 4-polybutadiene Spin lattice relaxation time (T_1) Line width nuclear overhauser effect (NOE)
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Algorithmic challenges in structure-based drug design and NMR structural biology
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作者 Lincong WANG Shuxue ZOU Yao WANG 《Frontiers of Electrical and Electronic Engineering in China》 CSCD 2012年第1期69-84,共16页
The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly ... The three-dimensional structure of a biomolecule rather than its one-dimensionM sequence determines its biological function. At present, the most accurate structures are derived from experimental data measured mainly by two techniques: X-ray crystallog- raphy and nuclear magnetic resonance (NMR) spec- troscopy. Because neither X-ray crystallography nor NMR spectroscopy could directly measure the positions of atoms in a biomolecule, algorithms must be designed to compute atom coordinates from the data. One salient feature of most NMR structure computation algorithms is their reliance on stochastic search to find the lowest energy conformations that satisfy the experimentally- derived geometric restraints. However, neither the cor- rectness of the stochastic search has been established nor the errors in the output structures could be quantified. Though there exist exact algorithms to compute struc- tures from angular restraints, similar algorithms that use distance restraints remain to be developed. An important application of structures is rational drug design where protein-ligand docking plays a crit- ical role. In fact, various docking programs that place a compound into the binding site of a target protein have been used routinely by medicinal chemists for both lead identification and optimization. Unfortunately, de- spite ongoing methodological advances and some success stories, the performance of current docking algorithms is still data-dependent. These algorithms formulate the docking problem as a match of two sets of feature points. Both the selection of feature points and the search for the best poses with the minimum scores are accomplished through some stochastic search methods. Both the un- certainty in the scoring function and the limited sam- pling space attained by the stochastic search contribute to their failures. Recently, we have developed two novel docking algorithms: a data-driven docking algorithm and a general docking algorithm that does not rely on experimental data. Our algorithms search the pose space exhaustively with the pose space itself being limited to a set of hierarchical manifolds that represent, respectively, surfaces, curves and points with unique geometric and energetic properties. These algorithms promise to be es- pecially valuable for the docking of fragments and small compounds as well as for virtual screening. 展开更多
关键词 structure-based drug design (SBDD) vir- tual screening (VC) protein-ligand docking scoring function molecular dynamics (MD) Monte Carlo (MC) simulated annealing (SA) Markov chain Monte Carlo (MCMC) nuclear magnetic resonance (NMR) nuclear overhauser effect (NOE) residual dipolar couplings (RDCs) chemical shift (CS) inference structure deter- mination (ISD) Bayesian Gibbs sampling probabil- ity distribution functions (PDFs) degrees of freedom (DOF) van der Waals (VDW) root mean square devi- ation (RMSD) manifold Poisson-Boltzmann equation (PBE)
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