PPM_One: a static protein structure based chemical shift predictor
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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.
KeywordProtein chemical shift prediction Physics-based predictor Backbone and side-chain chemical shifts Neural network Database analysis
This work was supported by the NSF (Grant MCB 1360966). R.B. is an Ohio Research Scholar.
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