PROGRESS IN NUCLEAR VECTOR REPLACEMENT FOR NMR PROTEIN STRUCTURE-BASED ASSIGNMENTS

摘要

Nuclear Magnetic Resonance (NMR) Spectroscopy is an important technique to obtain structural information of a protein. In this technique, an essential step is the backbone resonance assignment and Structure Based Assignment (SBA) aims to solve this problem with the help of a template structure. Nuclear Vector Replacement (NVR) is an NMR protein SBA program, that takes as input N-15 and H-N chemical shifts and unambiguous NOEs, as well as RDCs, HD-exchange and TOCSY data. NVR does not utilize C-13 chemical shifts although this data is widely available for many proteins. In addition, NVR is a proof-of-principle approach and has been run with specific and manually set parameters for some proteins. NA-NVR-ACO [M. Akhmedov, B. Catay and M.S. Apaydin, J. Bioinform. Comput. Biol. 13 (2015) 1550020.] remedies this problem for the NOE data and standardizes NOE usage, while using an ant colony optimization based algorithm. In this paper, we standardize NA-NVR-ACO's scoring function by using the same parameters for all the proteins and incorporating C-13 alpha chemical shifts. We also use a larger protein database and state-of-the-art chemical shift prediction tools, SHIFTX2 [B. Han, Y. Liu, S.W. Ginzinger and D.S. Wishart, J. Biomol. NMR 50 (2011) 4357.] and SPARTA+ [Y. Shen and A. Bax, J. Biomol. NMR 48 (2010) 13-22], to extract the chemical shift statistics. Other practical improvements include automatizing data file preparation and obtaining a degree of reliability for individual peak-amino acid assignments. Our results show that our improvements bring NA-NVR-ACO closer to a practical tool, able to handle a variety of different data types.