title: PPM_One: a static protein structure based chemical shift predictor.
abstract: 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.
authors.affiliation: Campus Chemical Instrument Center, The Ohio State University, Columbus, OH, 43210, USA.
authors.forename: Dawei
authors.initials: D
authors.lastname: Li
authors.forename: Rafael
authors.initials: R
authors.lastname: Brüschweiler
mesh_terms: D030562:Databases, Protein; D015233:Models, Statistical; D016571:Neural Networks, Computer; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D012984:Software
chemical_list: D011506:Proteins