Issue |
RAIRO-Oper. Res.
Volume 50, Number 2, April-June 2016
Special issue: Recent Advances in Operations Research in Computational Biology, Bioinformatics and Medicine
|
|
---|---|---|
Page(s) | 341 - 349 | |
DOI | https://doi.org/10.1051/ro/2015038 | |
Published online | 24 March 2016 |
Progress in Nuclear Vector Replacement for NMR Protein Structure-Based Assignments∗
1 Department of Graduate School of Natural and Applied
Sciences, İstanbulŞehir University, 34662 Üsküdar, Istanbul, Turkey.
seymacetinkaya@std.sehir.edu.tr; seymaekren@std.sehir.edu.tr
2 College of Engineering and Natural Sciences, İstanbulŞehir
University, 34662 Üsküdar, Istanbul, Turkey.
apaydin@sehir.edu.tr
Received:
8
September
2015
Accepted:
21
September
2015
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 15N and HN chemical shifts and unambiguous NOEs, as well as RDCs, HD-exchange and TOCSY data. NVR does not utilize 13C 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.Çatay and M.S. Apaydın, 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 13Cα 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) 43–57.] 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.
Mathematics Subject Classification: 90c27
Key words: NMR structure based protein assignment / NVR; score function / triple resonance experiments / reliability of assignments
© EDP Sciences, ROADEF, SMAI 2016
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