Analysis of a systematic search-based algorithm for determining protein backbone structure from a minimum number of residual dipolar couplings

• Published in: Proceedings / IEEE Computational Systems Bioinformatics Conference pp. 319 - 330
• Main Authors: Lincong Wang, Donald, B.R.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 2004
• Subjects: Algorithm design and analysis; Algorithms; Amino Acid Sequence; Computer Simulation; Couplings; Equations; Hydrogen Bonding; Magnetic Resonance Spectroscopy - methods; Minimization methods; Models, Chemical; Models, Molecular; Molecular Sequence Data; Nuclear magnetic resonance; Nuclear measurements; Protein Conformation; Protein engineering; Sequence Alignment - methods; Sequence Analysis, Protein - methods; Spectroscopy; Spine; Vectors
• ISBN: 9780769521947; 0769521940
• ISSN: 1551-7497
• DOI: 10.1109/CSB.2004.1332445

We have developed an ab initio algorithm for determining a protein backbone structure using global orientational restraints on internuclear vectors derived from residual dipolar couplings (RDCs) measured in one or two different aligning media by solution nuclear magnetic resonance (NMR) spectroscopy. Specifically, the conformation and global orientations of individual secondary structure elements are computed, independently, by an exact solution, systematic search-based minimization algorithm using only 2 RDCs per residue. The systematic search is built upon a quartic equation for computing, exactly and in constant time, the directions of an internuclear vector from RDCs, and linear or quadratic equations for computing the sines and cosines of backbone dihedral (/spl phi/, /spl psi/) angles from two vectors in consecutive peptide planes. In contrast to heuristic search such as simulated annealing (SA) or Monte-Carlo (MC) used by other NMR structure determination algorithms, our minimization algorithm can be analyzed rigorously in terms of expected algorithmic complexity and the coordinate precision of the protein structure as a function of error in the input data. The algorithm has been successfully applied to compute the backbone structures of three proteins using real NMR data.