Using amino acid typing to improve the accuracy of NMR structure based assignments

Abstract

Nuclear Magnetic Resonance (NMR 1 ) spectroscopy is an important experimental technique that allows one to study protein structure in solution. An important challenge in NMR protein structure determination is the assignment of NMR peaks to corresponding nuclei. In structure-based assignment (SBA), the aim is to perform the assignments with the help of a homologous protein. NVR-BIP [1] is a tool that uses Nuclear Vector Replacement's (NVR) ([9], [10]) scoring function and binary integer programming to solve SBA problem. In this work, we introduce a method to improve NVR-BIP's assignment accuracy with amino acid typing. We use CRAACK that takes the chemical shifts of C, N and H atoms and returns the possible amino acids along with their confidence scores. We obtain improved assignment accuracies and our results show the effectiveness of integrating amino acid typing with NVR.

Incorporating H ADA M AC experiment into NMR Structure-based assignments

“…We incorporate the HADAMAC experiment into NVR-BIP's scoring function; and 3. We test our approach on NVR-BIP's dataset and compare our results with the previous works [1] and [4].…”

“…These chemical shifts could then be used with amino acid typing to help determine the type of the amino acids or reduce the possibilities, therefore act as a filter. With this motivation, in [4], we integrated {N,HN,HA,HB,CA,CB,CO} chemical shifts and used CRAACK [3], an amino acid typing software to modify NVR's scoring function and obtained improved assignment accuracies.…”

“…In [4], we incorporated additional chemical shifts into NVR and used amino acid typing software CRAACK to improve NVR's scoring function. CRAACK predicts a set containing amino acid names with corresponding probabilities for each peak.…”

Incorporating Amino Acid Typing Into Nuclear Magnetic Resonance Protein Structure-Based Assignments

“…This results in a matrix (Craack score) that has for each (peak, residue) pair the consensus score associated by Craack. We integrate this matrix with NVR's score matrix using two approaches [17].…”