Incorporating amino acid typing into Nuclear Magnetic Resonance protein structure-based assignments

摘要

Protein structure determination is crucial to understand a protein's function and to develop drugs against diseases. Nuclear Magnetic Resonance (NMR) spectroscopy is an experimental technique that allows one to study protein structure in solution. In NMR Structure-Based Assignment (SBA) problem, the aim is to assign experimentally observed peaks to the specific nuclei of the target molecule by using a template protein and it is an important computational challenge. NVR is an NMR SBA framework in which multiple types of NMR data are combined to compute the assignments. In this paper, we studied the effect of incorporating additional sources of data into NVR. We added two types of data, chemical shifts for atoms other than 15N and HN, or HADAMAC experiment. We utilized an amino acid typing software Craack, that takes the chemical shifts of C, N and H atoms and returns the possible amino acids along with their confidence scores. This approach resulted in improved assignment accuracies. HADAMAC experiment which helps to predict an amino acid class for each peak was also incorporated into NVR, with improved assignment accuracies