Enhancing Crystal-Structure Prediction with NMR Tensor Data
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  • 作者:James K. Harper ; David M. Grant
  • 刊名:Crystal Growth & Design
  • 出版年:2006
  • 出版时间:October 2006
  • 年:2006
  • 卷:6
  • 期:10
  • 页码:2315 - 2321
  • 全文大小:209K
  • 年卷期:v.6,no.10(October 2006)
  • ISSN:1528-7505
文摘
A method for selecting high-probability structures from numerous computer-generated crystal structures is described.This procedure evaluates structures by comparing computed NMR shifts for each predicted structure to experimental solid-stateNMR data. Four carbohydrates are evaluated: methyl -D-galactopyranoside, methyl -D-glucopyranoside, methyl -D-mannopyranoside, and methyl -D-xylopyranoside. In these cases, 81.8% of the structures retained as probable fits by lattice energycomparisons are eliminated by the NMR criterion using tensor principal values. This analysis also ranks the correct structure as thebest-fit for methyl -D-glucopyranoside and usually places the correct structure among the top five in other cases. Isotropic shiftcomparisons are less successful in selecting structure. The NMR analysis is sufficiently sensitive to identify a 30 error in onetorsion angle of the purported correct structure of methyl -D-galactopyranoside. In this case, it is found that none of the 164computer-generated structures match experimental data. The substances investigated experience only weak electrostatic fields; therefore,the NMR analysis chooses primarily by molecular conformation rather than lattice structure. NMR data thus provide a valuableindependent selection criterion. The presence of strong electrostatic fields in polar samples can alter the results given here, andlikely changes in the selection process are discussed.

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