Distinguishing the type of NOE for NMR protein Structure-Based Assignments

Abstract

The key bottleneck of Nuclear Magnetic Resonance (NMR) studies is to map the NMR peaks to corresponding nuclei, also known as the assignment problem. Structure Based Assignment (SBA) is an approach to solve this computationally challenging problem by using prior information about the protein obtained from a homologous structure. NVR-BIP uses the Nuclear Vector Replacement (NVR) framework to model SBA as a binary integer programming problem. NVR-TS is a tabu search (TS) based approach equipped with a guided perturbation mechanism to handle the proteins with larger amino acid numbers. One of the principal data sources used by these programs is the Nuclear Overhauser effect (NOE). NOE is an effect measured between any pair of protons closer than 6 Ȧ. In these previous approaches the proton type was not distinguished in NOEs and only HN coordinates were used to incorporate the NOEs into the computation. In this study, we fix this problem and use both HA and HN coordinates and the corresponding distances in computation. We update the problem formulation of NVR-BIP accordingly and formulate the modified NVR-BIP. We also adapt the tabu search algorithm (NVR-TS) to utilize HA and HN coordinates. Our results indicate that the new approach improves the assignment accuracies significantly.