Automated analysis of NMR assignments and structures for proteins

Current Opinion in Structural Biology

Volumn 9, Issue 5, 1999, Pages 635-642

  Moseley, Hunter Nb ^a   Montelione, Gaetano T ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOANALYZER; BIOTECHNOLOGY; COMPUTER PROGRAM; INFORMATION PROCESSING; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PRIORITY JOURNAL; PROTEIN STRUCTURE; REVIEW;

EID: 0032857781     PISSN: 0959440X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-440X(99)00019-6     Document Type: Review

References (42)

1. Koradi R, Billeter M, Engeli M, Güntert P, Wüthrich K Automated peak picking and peak integration in macromolecular NMR spectra using AUTOPSY. J Magn Reson. 135:1998;288-297. An excellent description of the problems associated with automating peak picking and some methods for their solution.
2. Schulte A-C, Görler A, Antz C, Neidig K-P, Kalbitzer HR Use of global symmetries in automated signal class recognition by a Bayesian method. J Magn Reson. 129:1997;165-172.
3. Bartels C, Güntert P, Billeter M, Wüthrich K GARANT - a general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra. J Comput Chem. 18:1997;139-149. A powerful approach using genetic algorithms for the automatic analysis of resonance and NOESY cross-peak assignments is described.
4. Buchler NEG, Zuiderweg ERP, Wang H, Goldstein RA Protein heteronuclear NMR assignments using mean-field simulated annealing. J Magn Reson. 125:1997;34-42. A powerful resonance assignment program using optimization methods is described. The paper provides a detailed description of the problems associated with the rough pseudo-energy functions used in simulated annealing methods for mapping. It also describes the mean-field method for smoothing pseudo-energy functions.
5. Li K-B, Sanctuary BC Automated resonance assignment of proteins using heteronuclear 3D NMR. J Chem Inform Comput Sci. 37:1997;467-477. This paper describes different experimental strategies for sidechain assignments and linking them to the backbone. It also describes a constraint-partitioning algorithm applied to the mapping.
6. 15N)-labeled proteins. J Biomol NMR. 9:1997;151-166. The authors present a powerful resonance assignment strategy using Bayesian statistics methods for both referencing between spectra and amino acid typing.
7. Zimmerman DE, Kulikowski CA, Huang Y, Feng W, Tashiro M, Shimotakahara S, Chien C-Y, Powers R, Montelione GT Automated analysis of protein NMR assignments using methods from artificial intelligence. J Mol Biol. 269:1997;592-610. This paper describes the algorithms and methodology of the AutoAssign program for determining backbone resonance assignments. This includes a description of a Bayesian statistics method for amino acid typing, a constraint-propagation algorithm for mapping and test results on several real protein data sets.
8. Leutner M, Gschwind RM, Liermann J, Schwarz C, Gemmecker G, Kessler H Automated backbone assignment of labeled proteins using the threshold accepting algorithm. J Biomol NMR. 11:1998;31-43. A description of the PASTA program for resonance assignment and a threshold-accepting algorithm for improving simulated annealing as applied to mapping.
9. Montelione GT, Rios CB, Swapna GVT, Zimmerman DE NMR pulse sequences and computational approaches for automated analysis of sequence-specific backbone resonance assignments of proteins. Krishna R, Berliner L Biological Magnetic Resonance, Volume 17: Structure Computation and Dynamics in Protein NMR. 1999;81-130 Plenum, New York. A summary of practical considerations in collecting triple-resonance NMR data suitable for automated analysis of resonance assignments.
10. Croft D, Kemmink J, Neidig K-P, Oschkinat H Tools for the automated assignment of high-resolution three-dimensional protein NMR spectra based on pattern recognition techniques. J Biomol NMR. 10:1997;207-219.
11. Gronwald W, Wilard L, Jellard T, Boyko RF, Rajarathnam K, Wishart DS, Sönnichsen FD, Sykes BD CAMRA: chemical shift based computer aided protein NMR assignments. J Biomol NMR. 12:1998;395-405.
12. 15N) NMR spectra: application to HU protein from Bacillus stearothermophilus. Biopolymers. 39:1996;691-701.
13. 15N NMR data. J Biomol NMR. 10:1997;45-52.
14. 13C-labeled proteins with projected 4D triple resonance NMR experiments. J Biomol NMR. 11:1998;387-405. A novel and very powerful approach using reduced-dimensionality triple-resonance experiments for determining resonance assignments and software for the automated analysis of these spectra. This approach has the potential to reduce the time required for collecting data for resonance assignments.
15. Malliavin TE, Pons JL, Delsuc MA An NMR assignment module implemented in the Gifa NMR processing program. Bioinformatics. 14:1998;624-631.
16. Bartels C, Billeter M, Güntert P, Wüthrich K Automated sequence-specific NMR assignment of homologous proteins using the program GARANT. J Biomol NMR. 7:1996;207-213.
17. 13C frequency labeling. J Biomol NMR. 6:1995;211-216.
18. Feng W, Rios CB, Montelione GT Phase labeling of C-H and C-C spin system topologies: application in PFG-HACANH and PFG-HACA(CO)NH triple resonance experiments for determining backbone resonance assignments in proteins. J Biomol NMR. 8:1996;98-104.
19. Rios CB, Feng W, Tashiro M, Shang Z, Montelione GT Phase labeling of C-H and C-C spin-system topologies: application in constant-time PFG-CBCA(CO)NH experiments for discriminating amino acid spin-system types. J Biomol NMR. 8:1996;345-350.
20. Dötsch V, Matsuo K, Wagner G Amino-acid-type identification for deuterated proteins with a β-carbon-edited HNCOCACB experiment. J Magn Reson B. 112:1996;95-100.
21. 13Cγ coupling. J Magn Reson B. 111:1996;310-313.
22. β carbon-13 chemical shifts in proteins from an empirical database. J Biomol NMR. 13:1999;199-211.
23. O'Connell JF, Pryor KAD, Grant SK, Leiting B A high quality nuclear magnetic resonance solution structure of peptide deformylase from Escherichia coli: application of an automated assignment strategy using GARANT. J Biomol NMR. 13:1999;311-324. This paper describes a largely automated structure determination using automated analysis of resonance assignments and some NOESY cross-peak assignments using GARANT.
24. Gippert GP, Wright PE, Case DA Distributed torsion angle grid search in high dimensions: a systematic approach to NMR structure determination. J Biomol NMR. 11:1998;241-263. The authors describe very general and efficient approaches for the automatic analysis of dihedral-angle constraints from NMR data.
25. Cornilescu G, Delaglio F, Bax A Protein backbone angle restraints from searching a database for chemical shift and sequence homology. J Biomol NMR. 13:1999;289-302. This paper describes the TALOS program for the automatic analysis of dihedral-angle constraints. The program is based on a database of chemical shift data for proteins with high-resolution crystal structures.
26. Beger RD, Bolton PH Protein φ and ψ dihedral restraints determined from multidimensional hypersurface correlations of backbone chemical shifts and their use in the determination of protein tertiary structures. J Biomol NMR. 10:1997;129-142.
27. ••], this represents one of the most successful approaches to automated analysis of NOESY data described in the literature to date.
28. Mumenthaler C, Braun W Automated assignment of simulated and experimental NOESY spectra of proteins by feedback filtering and self-correcting distance geometry. J Mol Biol. 254:1995;465-480.
29. Güntert P, Mumenthaler C, Wüthrich K Torsion angle dynamics for NMR structure calculation with the new program DYANA. J Mol Biol. 273:1997;283-298.
30. •], this represents one of the most successful approaches to automated analysis of NOESY data described in the literature to date.
31. Nilges M, Macias MJ, O'Donoghue SI, Oschkinat H Automated NOESY interpretation with ambiguous distance restraints: the refined NMR solution structure of the Pleckstrin homology domain from β-spectrin. J Mol Biol. 269:1997;408-422. This paper provides a description of the ARIA approach for using ambiguous constraints in structure calculations with the X-PLOR program, together with tests and applications to real data. ARIA has been used successfully in several experimental NMR structure determinations.
32. Brünger AT X-PLOR, version 3.1: a System for X-ray Crystallography and NMR. 1992;Yale University Press, New Haven, CT.
33. Badger J, Kumar RA, Szalma S New features and enhancements in the X-PLOR computer program. Proteins. 35:1999;25-33.
34. Fraternali F, Amodeo P, Musco G, Nilges M, Pastore A Exploring protein interiors: the role of a buried histidine in the KH module fold. Proteins. 34:1999;484-496.
35. 3CR1. Biochemistry. 38:1999;1402-1414.
36. Luh FY, Archer SJ, Domaille PJ, Smith BO, Owen D, Brotherton DH, Raine AR, Xu X, Brizuela L, Brenner SL, Laue ED Structure of the cyclin-dependent kinase inhibitor p19Ink4d. Nature. 389:1997;999-1003.
37. Bassolino-Klimas D, Tejero R, Krystek SR, Metzler WJ, Montelione GT, Bruccoleri RE Simulated annealing with restrained molecular dynamics using a flexible restraint potential: theory and evaluation with simulated NMR constraints. Protein Sci. 5:1996;593-603.
38. 15N edited 3D-NOESY - HSQC spectra using back calculated and experimental spectra. J Magn Reson. 137:1999;39-45.
39. Prestegard JH New techniques in structural NMR-anisotropic interactions. Nat Struct Biol. 5( ):1998;517-522.
40. 13C couplings in the structure determination of magnetically oriented macromolecules in solution. Nat Struct Biol. 4:1997;732-738.
41. Montelione GT, Anderson S Structural genomics: a keystone for a human proteome project. Nat Struct Biol. 6:1999;11-12.
42. Moy FJ, Seddon AP, Böhlen P, Powers R High-resolution solution structure of basic fibroblast growth factor determined by multidimensional heteronuclear magnetic resonance spectroscopy. Biochemistry. 35:1996;13551-13561.