PPM_One: a static protein structure based chemical shift predictor

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• 作者：Dawei Li ; Rafael Brüschweiler
• 关键词：Protein chemical shift prediction ; Physics ; based predictor ; Backbone and side ; chain chemical shifts ; Neural network ; Database analysis
• 刊名：Journal of Biomolecular NMR
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：62
• 期：3
• 页码：403-409
• 全文大小：749 KB
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• 作者单位：Dawei Li (1)
  Rafael Brüschweiler (1) (2)
  
  1. Campus Chemical Instrument Center, The Ohio State University, Columbus, OH, 43210, USA
  2. Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH, 43210, USA
  
• 刊物类别：Physics and Astronomy
• 刊物主题：Physics
  Biophysics and Biomedical Physics
  Polymer Sciences
  Biochemistry
  
• 出版者：Springer Netherlands
• ISSN：1573-5001

文摘

We mined the most recent editions of the BioMagResDataBank and the protein data bank to parametrize a new empirical knowledge-based chemical shift predictor of protein backbone atoms using either a linear or an artificial neural network model. The resulting chemical shift predictor PPM_One accepts a single static 3D structure as input and emulates the effect of local protein dynamics via interatomic steric contacts. Furthermore, the chemical shift prediction was extended to most side-chain protons and it is found that the prediction accuracy is at a level allowing an independent assessment of stereospecific assignments. For a previously established set of test proteins some overall improvement was achieved over current top-performing chemical shift prediction programs.