NVR-BIP: Nuclear vector replacement using binary integer programming for NMR structure-based assignments

Abstract

Nuclear magnetic resonance (NMR) spectroscopy is an important experimental technique that allows one to study protein structure in solution and to identify important sites in a protein. An important bottleneck in NMR protein structure determination is the assignment of NMR peaks to the corresponding nuclei. Structure-based assignment (SBA) aims to solve this problem with the help of a template protein which is homologous to the target and has applications in the study of structure-activity relationship, protein-protein and protein-ligand interactions. We formulate SBA as a linear assignment problem with additional Nuclear Overhauser Effect (NOE) constraints, which can be solved within Nuclear Vector Replacement's (NVR) framework. Our approach uses NVR's scoring function and data types, and also gives the option of using CH and NH RDCs, instead of NH RDCs which NVR requires. We test our technique on NVR's data set as well as on two new proteins. Our results are comparable to NVR's assignment accuracy on NVR's test set, but higher on novel proteins. Our approach allows partial assignments. It is also complete and can return the optimum as well as near-optimum assignments. Furthermore, it allows us to analyze the information content of each data type and is easily extendable to accept new forms of input data, such as additional RDCs.