title: Automating unambiguous NOE data usage in NVR for NMR protein structure-based assignments.
abstract: Nuclear Magnetic Resonance (NMR) Spectroscopy is an important technique that allows determining protein structure in solution. An important problem in protein structure determination using NMR spectroscopy is the mapping of peaks to corresponding amino acids, also known as the assignment problem. Structure-Based Assignment (SBA) is an approach to solve this problem using a template structure that is homologous to the target. Our previously developed approach Nuclear Vector Replacement-Binary Integer Programming (NVR-BIP) computed the optimal solution for small proteins, but was unable to solve the assignments of large proteins. NVR-Ant Colony Optimization (ACO) extended the applicability of the NVR approach for such proteins. One of the input data utilized in these approaches is the Nuclear Overhauser Effect (NOE) data. NOE is an interaction observed between two protons if the protons are located close in space. These protons could be amide protons, protons attached to the alpha-carbon atom in the backbone of the protein, or side chain protons. NVR only uses backbone protons. In this paper, we reformulate the NVR-BIP model to distinguish the type of proton in NOE data and use the corresponding proton coordinates in the extended formulation. In addition, the threshold value over interproton distances is set in a standard manner for all proteins by extracting the NOE upper bound distance information from the data. We also convert NOE intensities into distance thresholds. Our new approach thus handles the NOE data correctly and without manually determined parameters. We accordingly adapt NVR-ACO solution methodology to these changes. Computational results show that our approaches obtain optimal solutions for small proteins. For the large proteins our ant colony optimization-based approach obtains promising results.
authors.affiliation: * Dalle Molle Institute for Artificial Intelligence, Galleria 2, 6928 Manno-Lugano, Switzerland.
authors.forename: Murodzhon
authors.initials: M
authors.lastname: Akhmedov
authors.affiliation: † Sabanci University, Faculty of Engineering and Natural Sciences, 34956 Orhanlı, Istanbul, Turkey.
authors.forename: Bülent
authors.initials: B
authors.lastname: Çatay
authors.affiliation: ‡ Istanbul Şehir University, Altunizade Mahalle 27, 34662 Istanbul, Turkey.
authors.forename: Mehmet Serkan
authors.initials: MS
authors.lastname: Apaydın
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008958:Models, Molecular; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins
keywords: NMR protein structure-based assignments; NOE; ant colony optimization; combinatorial optimization