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Automated NMR Structure Calculation With CYANA
"... This chapter gives an introduction to automated nuclear magnetic resonance (NMR) structure calculation with the program CYANA. Given a sufficiently complete list of assigned chemical shifts and one or several lists of crosspeak positions and columes from two, three, or fourdimensional nuclear Ov ..."
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This chapter gives an introduction to automated nuclear magnetic resonance (NMR) structure calculation with the program CYANA. Given a sufficiently complete list of assigned chemical shifts and one or several lists of crosspeak positions and columes from two, three, or fourdimensional nuclear Overhauser effect spectroscopy (NOESY) spectra, the assignment of the NOESY crosspeaks and the threedimensional structure of the protein in solution can be calculated automatically with CYANA.
ARIA2: Automated NOE assignment and data integration in NMR structure calculation
, 2006
"... Summary: Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhan ..."
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Summary: Modern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the objectoriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages. Availability: A distribution with the source code of ARIA 2.1 is freely available at
ARIA: Automated NOE assignment and NMR structure calculation
 Bioinformatics
"... Motivation: In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due ..."
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Cited by 33 (2 self)
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Motivation: In the light of several ongoing structural genomics projects, faster and more reliable methods for structure calculation from NMR data are in great demand. The major bottleneck in the determination of solution NMR structures is the assignment of NOE peaks (nuclear Overhauser effect). Due to the high complexity of the assignment problem, most NOEs cannot be directly converted into unambiguous interproton distance restraints. Results: We present version 1.2 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of NOE data and NMR structure calculation. We summarize recent progress in correcting for spin diffusion with a relaxation matrix approach, representing nonbonded interactions in the force field and refining final structures in explicit solvent. We also discuss bookkeeping, data exchange with spectra assignment programs and deposition of the analysed experimental data to the databases. Availability: ARIA 1.2 is available from:
An Efficient and Accurate Algorithm for Assigning Nuclear Overhauser Effect Restraints Using a Rotamer Library Ensemble and Residual Dipolar Couplings. The
 IEEE Computational Systems Bioinformatics Conference (CSB
, 2005
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Automated NMR assignment and protein structure determination using sparse dipolar coupling constraints
 Progress in NMR Spectroscopy
"... The introduction of residual dipolar couplings (RDCs) for protein structure determination over 10 years ago has energized development of NMR methods. Robust automation of the complete NMR structure determination procedure has been a longstanding goal, and RDCbased algorithms may increase the consi ..."
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The introduction of residual dipolar couplings (RDCs) for protein structure determination over 10 years ago has energized development of NMR methods. Robust automation of the complete NMR structure determination procedure has been a longstanding goal, and RDCbased algorithms may increase the consistency and reliability of NMR structural studies. It has also
Structural genomics of the severe acute respiratory syndrome coronavirus: nuclear magnetic resonance structure of the protein nsP7
 J. Virol
, 2005
"... Here, we report the threedimensional structure of severe acute respiratory syndrome coronavirus (SARSCoV) nsP7, a component of the SARSCoV replicase polyprotein. The coronavirus replicase carries out regulatory tasks involved in the maintenance, transcription, and replication of the coronavirus g ..."
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Here, we report the threedimensional structure of severe acute respiratory syndrome coronavirus (SARSCoV) nsP7, a component of the SARSCoV replicase polyprotein. The coronavirus replicase carries out regulatory tasks involved in the maintenance, transcription, and replication of the coronavirus genome. nsP7 was found to assume a compact architecture in solution, which is comprised primarily of helical secondary structures. Three helices (2 to 4) form a flat updownup antiparallel helix sheet. The Nterminal segment of residues 1 to 22, containing two turns of helix and one turn of 310helix, is packed across the surface of 2 and 3 in the helix sheet, with the helical region oriented at a 60 ° angle relative to 2 and 3. The surface charge distribution is pronouncedly asymmetrical, with the flat surface of the helical sheet showing a large negatively charged region adjacent to a large hydrophobic patch and the opposite side containing a positively charged groove that extends along the helix 1. Each of these three areas is thus implicated as a potential site for proteinprotein interactions. The severe acute respiratory syndrome coronavirus (SARSCoV) most closely resembles the group II coronaviruses, which infect mice, rats, pigs, and humans (34). Upon viral entry, the 30kb SARSCoV genome is translated to produce a pre
PICKY: a novel SVDbased NMR spectra peak picking method
 Bioinformatics
, 2009
"... Vol. 25 ISMB 2009, pages i268–i275 doi:10.1093/bioinformatics/btp225 ..."
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Vol. 25 ISMB 2009, pages i268–i275 doi:10.1093/bioinformatics/btp225
A PolynomialTime Algorithm for De Novo Protein Backbone Structure Determination from Nuclear Magnetic Resonance Data
"... We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is ..."
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We describe an efficient algorithm for protein backbone structure determination from solution Nuclear Magnetic Resonance (NMR) data. A key feature of our algorithm is that it finds the conformation and orientation of secondary structure elements as well as the global fold in polynomial time. This is the first polynomialtime algorithm for de novo highresolution biomacromolecular structure determination using experimentally recorded data from either NMR spectroscopy or Xray crystallography. Previous algorithmic formulations of this problem focused on using local distance restraints from NMR (e.g., nuclear Overhauser effect [NOE] restraints) to determine protein structure. This approach has been shown to be NPhard, essentially due to the local nature of the constraints. In practice, approaches such as molecular dynamics and simulated annealing, which lack both combinatorial precision and guarantees on running time and solution quality, are used routinely for structure determination. We show that residual dipolar coupling (RDC) data, which gives global restraints on the orientation of internuclear bond vectors, can be used in conjunction with very sparse NOE data to obtain a polynomialtime algorithm for structure determination. Furthermore, an implementation of our algorithm has been applied to six different real biological NMR data sets recorded for three proteins. Our algorithm is combinatorially precise, polynomialtime, and uses much less NMR data to produce results that are as good or better than previous approaches in terms of accuracy of the computed structure as well as running time.
AutoLink: automated sequential resonance assignment of biopolymers from NMR data by relativehypothesisprioritizationbased simulated logic
 J Magn Reson
"... We have developed a new computer algorithm for determining the backbone resonance assignments for biopolymers. The approach we have taken, relative hypothesis prioritization, is implemented as a Lua program interfaced to the recently developed computeraided resonance assignment (CARA) program. Our ..."
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We have developed a new computer algorithm for determining the backbone resonance assignments for biopolymers. The approach we have taken, relative hypothesis prioritization, is implemented as a Lua program interfaced to the recently developed computeraided resonance assignment (CARA) program. Our program can work with virtually any spectrum type, and is especially good with NOESY data. The results of the program are displayed in an easytoread, colorcoded, graphic representation, allowing users to assess the quality of the results in minutes. Here we report the application of the program to two RNA recognition motifs of Apobec1 Complementation Factor. The assignment of these domains demonstrates AutoLinkÕs ability to deliver accurate resonance assignments from very minimal data and with minimal user intervention.
A TopologyConstrained Distance Network Algorithm for Protein Structure Determination From NOESY Data
"... ABSTRACT This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottomup, topologyconstrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. Auto ..."
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ABSTRACT This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottomup, topologyconstrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topologyconstrained distance network analysis algorithm and iteratively generates structures using the threedimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4DNOESY cross peaks. AutoStructure can also analyze homodimeric proteins when Xfiltered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and Fmeasure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which highquality structures have previously been solved by an expert, and yields comparable highquality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published. Proteins 2006;62:587–603. © 2005 WileyLiss, Inc. Key words: AutoStructure; RPF; constraint network analysis; automated NMR structure determination; graph theory; fold topology constraints