Computational methods for NMR and MS for structure elucidation I: software for basic NMR

References

[1] Dobson CM. Chemical space and biology. Nature. 2004;432:824–8.10.1038/nature03192Search in Google Scholar PubMed

[2] Cragg GM, Newman DJ, Snader KM. Natural products in drug discovery and development. J Nat Prod. 1997;60:52–60.10.1021/np9604893Search in Google Scholar PubMed

[3] Harvey AL, Edrada-Ebel R, Quinn RJ. The re-emergence of natural products for drug discovery in the genomics era. Nat Rev Drug Discov. 2015;14:111–29.10.1038/nrd4510Search in Google Scholar PubMed

[4] Hubert J, Nuzillard JM, Renault JH. Dereplication strategies in natural product research: how many tools and methodologies behind the same concept? Phytochem Rev. 2017;16:55–95.10.1007/s11101-015-9448-7Search in Google Scholar

[5] Agilent VnmrJ. Software for nuclear magnetic resonance spectroscopy. https://www.agilent.com/cs/library/flyers/public/VnmrJ4_Core_Features.pdf.Search in Google Scholar

[6] Bruker. NMR software & Downloads. https://www.bruker.com/service/support-upgrades/software-downloads/nmr.html.Search in Google Scholar

[7] JEOL. Delta™ NMR data processing software. https://www.jeolusa.com/PRODUCTS/Nuclear-Magnetic-Resonance/Delta-NMR-Software.Search in Google Scholar

[8] Marat K. SpinWorks program. Nuclear magnetic resonance lab. https://home.cc.umanitoba.ca/~wolowiec/spinworks/.Search in Google Scholar

[9] Mestrelab Research. Mnova12. http://mestrelab.com/.Search in Google Scholar

[10] ACD/Labs. Platforms and products. https://www.acdlabs.com/products/.Search in Google Scholar

[11] Langley P. The computational support of scientific discovery. Int J Human-Comput Stud. 2000;53:393–410.10.1006/ijhc.2000.0396Search in Google Scholar

[12] Clerc JT, Sommerauer HA. A minicomputer program based on additivity rules for the estimation of 13c-nmr chemical shifts. Anal Chim Acta. 1977;95:33–40.10.1016/S0003-2670(00)84995-8Search in Google Scholar

[13] Fürst A, Retsch E. A computer program for the prediction of ¹³C-NMR chemical shifts of organic compounds. Anal Chim Acta. 1990;229:17–25.10.1016/S0003-2670(00)85105-3Search in Google Scholar

[14] Jurs PC, Ball JL, Anker LS, Friedman TL. Carbon-13 nuclear magnetic resonance spectrum simulation. J Chem Inf Comput Sci. 1992;32:272–8.10.1021/ci00008a002Search in Google Scholar

[15] Neudert R, Penk M. Enhanced structure elucidation. J Chem Inf Comput Sci. 1996;36:244–8.10.1021/ci9500997Search in Google Scholar

[16] Bremser W. Expectation ranges of 13C NMR chemical shifts. Magn Reson Chem. 1985;23:271–5.10.1002/mrc.1260230413Search in Google Scholar

[17] Chen L, Robien W. The CSEARCH-NMR data base approach to solve frequent questions concerning substituent effects on ¹³C NMR chemical shifts. Chemom Intell Lab Syst. 1993;19:217–23.10.1016/0169-7439(93)80105-QSearch in Google Scholar

[18] Gasteiger J, Zupan J. Neural networks in chemistry. AngewChem. 1993;32:503–27.10.1002/anie.199305031Search in Google Scholar

[19] Clouser DL, Jurs PC. Simulation of ¹³C nuclear magnetic resonance spectra of tetrahydropyrans using regression analysis and neural networks. Anal Chim Acta. 1994;295:221–31.10.1016/0003-2670(94)80227-0Search in Google Scholar

[20] Grant DM, Paul EG. Carbon-13 magnetic resonance. II. Chemical shift data for the alkanes. J Am Chem Soc. 1964;86:2984–90.10.1021/ja01069a004Search in Google Scholar

[21] Schweitzer RC, Small GW. Automated spectrum simulation methods for carbon-13 nuclear magnetic resonance spectroscopy based on database retrieval and model-building strategies. J Chem Inf Comput Sci. 1997;37:249–57.10.1021/ci9601731Search in Google Scholar

[22] Bremser W. Hose - a novel substructure code. Anal Chim Acta. 1978;103:355–65.10.1016/S0003-2670(01)83100-7Search in Google Scholar

[23] Elyashberg ME, Williams A, Blinov K. Contemporary computer-assisted approaches to molecular structure elucidation. Cambridge, U.K: Royal Society of Chemistry, 2012.10.1039/9781849734578-FP011Search in Google Scholar

[24] Aires-de-Souza J, Hemmer MC, Gasteiger J. Prediction of 1H NMR chemical shifts using neural networks. Anal Chem. 2002;74:80–90.10.1021/ac010737mSearch in Google Scholar PubMed

[25] Binev Y, Aires-de-Souza J. structure-based predictions of 1H NMR chemical shifts using feed-forward neural networks. J Chem Inf Model. 2004;44:940–5.10.1021/ci034228sSearch in Google Scholar PubMed

[26] Binev Y, Corvo M Aires-de-Souza J. The impact of available experimental data on the prediction of 1H NMR chemical shifts by neural networks. J Chem Inf Model. 2004;44:946–9.10.1021/ci034229kSearch in Google Scholar PubMed

[27] Lodewyk MW, Siebert MR, Tantillo DJ. Computational prediction of 1H and 13C chemical shifts: a useful tool for natural product, mechanistic, and synthetic organic chemistry. Chem Rev. 2012;112:1839–62.10.1021/cr200106vSearch in Google Scholar PubMed

[28] Simpson AJ, Lefebvre B, Moser A, Williams AJ, Larin N, Kvasha M, et al. Identifying residues in natural organic matter through spectral prediction and pattern matching of 2D NMR datasets. Magn Reson Chem. 2004;42:14–22.10.1002/mrc.1308Search in Google Scholar PubMed

[29] Will M, Fachinger W, Richert JR Fully automated structure elucidation - A spectroscopist’s dream comes true. J Chem Inf Comput Sci. 1996;36:221–7.10.1021/ci950092pSearch in Google Scholar

[30] Jaspars M. Computer assisted structure elucidation of natural products using two-dimensional NMR spectroscopy. Nat Prod Rep. 1999;16:241–8.10.1039/a804433cSearch in Google Scholar

[31] Shelley CA, Hays TR, Munk ME, Roman RV. An approach to automated partial structure expansion. Anal Chim Acta. 1978;103:121–32.10.1016/S0003-2670(01)84032-0Search in Google Scholar

[32] Carhart RE, Smith DH, Gray NA, Nourse JG, Djerassi C. Applications of artificial intelligence for chemical inference. 37. GENOA: a computer program for structure elucidation utilizing overlapping and alternative substructures. J Org Chem. 1981;46:1708–18.10.1021/jo00321a037Search in Google Scholar

[33] Kudo Y, Sasaki S. Principle for exhaustive enumeration of unique structures consistent with structural information. J Chem Inf Comput Sci. 1976;16:43–56.10.1021/ci60005a014Search in Google Scholar

[34] Munk ME, Velu VK, Madison MS, Robb EW, Baderstscher M, Christie BD, et al. Chemical Information Processing in Structure Elucidation. Recent advances in chemical information II. Cambridge, UK: Royal Society of Chemistry. In: Collier, H., editor 1993:247–63.Search in Google Scholar

[35] Bremser W, Fachinger W. Multidimensional spectroscopy. Magn Reson Chem. 1985;23:1056–71.10.1002/mrc.1260231208Search in Google Scholar

[36] Schutz V, Purtuc V, Felsinger S, Robien W. CSEARCH-STEREO: A new generation of NMR database systems allowing three-dimensional spectrum prediction. Fresenius’ J Anal Chem. 1997;359:33–41.10.1007/s002160050531Search in Google Scholar

[37] Carabedian M, Dagane I, Dubois J-E. Elucidation by progressive intersection of ordered substructures from carbon-13 nuclear magnetic resonance. Anal Chem. 1988;60:2186–92.10.1021/ac00171a005Search in Google Scholar

[38] Williamson RT, Buevich AV, Martin GE, Parella T. LR-HSQMBC: A sensitive NMR technique to probe very long-range heteronuclear coupling pathways. J Org Chem. 2014;79:3887–94.10.1021/jo500333uSearch in Google Scholar PubMed

[39] Uhrín D. Recent developments in liquid-state INADEQUATE studies. In Annual Reports on NMR Spectroscopy. [s.l.]. Cambridge, MA, US: Academic Press, 2010:1–34.10.1016/S0066-4103(10)70004-1Search in Google Scholar

[40] Buevich AV, Elyashberg ME. Synergistic combination of CASE algorithms and DFT chemical shift predictions: a powerful approach for structure elucidation, verification, and revision. J Nat Prod. 2016;79:3105–16.10.1021/acs.jnatprod.6b00799Search in Google Scholar PubMed

[41] Binev Y, Marques MM, Aires-de-Sousa J. Prediction of 1H NMR coupling constants with associative neural networks trained for chemical shifts. J Chem Inf Model. 2007;47:2089–97.10.1021/ci700172nSearch in Google Scholar PubMed

[42] Steinbeck C. Recent developments in automated structure elucidation of natural products. Nat Prod Rep. 2004;21:512–18.10.1039/b400678jSearch in Google Scholar PubMed

[43] Canzler D, Hellenbrandt M. SPECINFO - the spectroscopic information system on STN international. Fresen J Anal Chem. 1992;344:167–72.10.1007/BF00322704Search in Google Scholar

[44] Steinbeck C, Kuhn S, Krause S. NMRShiftDB constructing a free chemical information system with open-source components. J Chem Inf Comput Sci. 2003;43:1733–9.10.1021/ci0341363Search in Google Scholar PubMed

[45] Cobas JC, Sardina FJ. Nuclear magnetic resonance data processing. MestRe-C: Software Package Desktop Comput ConceptsMagnReson Part A. 2003;19A:80–96.10.1002/cmr.a.10089Search in Google Scholar

[46] Cobas C, Seoane F, Vaz E, Bernstein MA, Dominguez S, Péreza M, et al. Automatic assignment of 1H-NMR spectra of small molecules. Magn Reson Chem. 2013;51:649–54.10.1002/mrc.3995Search in Google Scholar PubMed

[47] Mestrelab Research NMR Predict. 2018. http://mestrelab.com/software/mnova/nmr-predict/.Search in Google Scholar

[48] Mestrelab Research Resources. 2018. http://resources.mestrelab.com/mestrecvsmnova.Search in Google Scholar

[49] Mestrelab Research Mnova Structure Elucidation. 2018. http://mestrelab.com/software/mnova/structure-elucidation/.Search in Google Scholar

[50] ACD/Structure Elucidator Suite. 2018. https://www.acdlabs.com/products/com_iden/elucidation/struc_eluc/.Search in Google Scholar

[51] Elyashberg M, Blinov K, Martirosian E. A new approach to computer-aided molecular structure elucidation: the expert system structure elucidator. Lab Autom Inform Manag. 1999;34:15–30.10.1016/S1381-141X(99)00002-7Search in Google Scholar

[52] Blinov KA, Elyashberg ME, Molodtsov SG, Williams AJ, Martirosian ER. An expert system for automated structure elucidation utilizing ¹H-¹H, ¹³C-¹H and ¹⁵N-¹H 2D NMR correlations. Fresen J Anal Chem. 2001;369:709–14.10.1007/s002160100757Search in Google Scholar

[53] Elyashberg ME, Blinov KA, Williams AJ, Martirosian ER, Molodtsov SG. Application of a new expert system for the structure elucidation of natural products from their 1D and 2D NMR data. J Nat Prod. 2002;65:693–703.10.1021/np0103315Search in Google Scholar PubMed

[54] Elyashberg ME, Blinov KA, Williams AJ, Molodtsov SG, Martin GE. Are deterministic expert systems for computer-assisted structure elucidation obsolete? J Chem Inf Model. 2006;46:1643–56.10.1021/ci050469jSearch in Google Scholar PubMed

[55] Elyashberg M, Williams AJ, Blinov K. Structural revisions of natural products by computer-assisted structure elucidation (CASE) systems. Nat Prod Rep. 2010;27:1296.10.1039/c002332aSearch in Google Scholar PubMed

[56] Li X-N, Ridge CD, Mazzola EP, Sun J, Gutierrez O, Moser A, et al. Application of a computer-assisted structure elucidation program for the structural determination of a new terpenoid aldehyde with an unusual skeleton. Magn Reson Chem. 2017;55:210–13.10.1002/mrc.4466Search in Google Scholar PubMed

[57] San Feliciano A, Medarde M, Del Corral JM, Aramburu A, Gordaliza M, Barrero AF. Aquatolide. A new type of humulane-related sesquiterpene lactone. Tetrahedron Lett. 1989;30:2851–4.10.1016/S0040-4039(00)99142-1Search in Google Scholar

[58] Lodewyk MW, Soldi C, Jones PB, Olmstead MM, Rita J, Shaw JT, et al. The correct structure of Aquatolide—experimental validation of a theoretically-predicted structural revision. J Am Chem Soc. 2012;134:18550–3.10.1021/ja3089394Search in Google Scholar PubMed

[59] Saya JM, Vos K, Kleinnijenhuis RA, van Maarseveen JH, Ingemann S, Hiemstra H. Total synthesis of Aquatolide. Org Lett. 2015;17:3892–4.10.1021/acs.orglett.5b01888Search in Google Scholar PubMed

[60] Hunt DF, Yates JR, Shabanowitz J, Winston S, Hauer CR. Protein sequencing by tandem mass spectrometry. Proc Nat Acad Sci USA. 1986;17:6233–7.10.1007/978-1-59259-480-1_10Search in Google Scholar

[61] Biemann K, Scoble HA. Characterization by tandem mass spectrometry of structural modifications in proteins. Science. 1987;237:992–8.10.1126/science.3303336Search in Google Scholar PubMed

[62] Dole M, Mack LL, Hines RL, Mobley RC, Ferguson LD, Alice MB. Molecular beams of macroions. J Chem Phys. 1968;49:2240–9.10.1063/1.1670391Search in Google Scholar

[63] Fenn JB, Mann M, Meng CK, Wong SF, Whitehouse CM. Electrospray ionization for mass spectrometry of large biomolecules. Science. 1989;246:64–71.10.1126/science.2675315Search in Google Scholar PubMed

[64] Hillenkamp F, Karas M, Beavis RC, Chait BT. Matrix-assisted laser desorption/ionization mass spectrometry of biopolymers. Anal Chem. 1991;15:1193–203.10.1021/ac00024a716Search in Google Scholar

[65] Dongre AR, Jones JL, Somogyi A, Wysocki VH. Influence of peptide composition, gas-phase basicity, and chemical modification on fragmentation efficiency:  evidence for the mobile proton model. J Am Chem Soc. 1996;118:8365–74.10.1021/ja9542193Search in Google Scholar

[66] Seidler J, Zinn N, Boehm ME, Lehmann WD. De novo sequencing of peptides by MS/MS Proteomics. 2010;10:634–49.10.1002/pmic.200900459Search in Google Scholar PubMed

[67] Steen H, Kuster B, Mann M. Quadrupole time-of-flight versus triple-quadrupole mass spectrometry for the determination of phosphopeptides by precursor ion scanning. J Mass Spectrom. 2001;36:782–90.10.1002/jms.174Search in Google Scholar PubMed

[68] Prentice BM, Xu W, Ouyang Z, Mcluckey SA. Dc potentials applied to an end-cap electrode of a 3-D ion trap for enhanced MS functionality. Int J Mass Spectrom Amsterdam. 2011;306:114–22.10.1016/j.ijms.2010.09.022Search in Google Scholar

[69] Tabb DL, Smith LL, Breci LA, Vysocki VH, Lin D, Yates JR Statistical characterization of ion trap tandem mass spectra from doubly charged tryptic peptides. Anal Chem. 2003;75:1155–63.10.1021/ac026122mSearch in Google Scholar PubMed

[70] Syka JE, Coon JJ, Schroeder MJ, Shabanowitz J, Hunt DF. Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc Nat Acad Sci USA. 2004;101:9528–33.10.1073/pnas.0402700101Search in Google Scholar

[71] Bauer MD, Sun Y, Keough T, Lacey MP. Sequencing of sulfonic acid derivatized peptides by electrospray mass spectrometry. Rapid Commun Mass Spectrom. 2000;14:924–9.10.1002/(SICI)1097-0231(20000530)14:10<924::AID-RCM967>3.0.CO;2-XSearch in Google Scholar PubMed

[72] Roepstorff P, Fohlman J. Proposal for a common nomenclature for sequence ions in mass spectra of peptides. Biomed Mass Spectrom. 1984;11:601.10.1002/bms.1200111109Search in Google Scholar PubMed

[73] Biemann K. Appendix 5. Nomenclature for peptide fragment ions (positive ions). Methods Enzymol. 1990;193:886–7.10.1016/0076-6879(90)93460-3Search in Google Scholar PubMed

[74] Adamczy KM, Gebler JC, Wu J. Charge derivatization of peptides to simplify their sequencing with an ion trap mass spectrometer. Rapid Commun Mass Spectrom. 1999;13:1413–22.10.1002/(SICI)1097-0231(19990730)13:14<1413::AID-RCM657>3.0.CO;2-4Search in Google Scholar PubMed

[75] Lehmann WD. Protein phosphorylation analysis by electrospray mass spectrometry: a guide to concepts and practice/Wolf D. Lehmann, vol. xiv. Cambridge: Royal Society of Chemistry, 2010:379.Search in Google Scholar

[76] Jia C, Hui L, Cao W, Lietz CB, Jiang X, Chen R, et al. High-definition de novo sequencing of crustacean hyperglycemic hormone (CHH)-family neuropeptides. Mol Cell Proteomics. 2012;11:1951–64.10.1074/mcp.M112.020537Search in Google Scholar PubMed

[77] Medzihradszky KF, Bohlen CJ. Partial de novo sequencing and unusual CID fragmentation of a 7 kDa, disulfide-bridged toxin. J Am Soc Mass Spectrom. 2012;23:923–34.10.1007/s13361-012-0350-xSearch in Google Scholar PubMed

[78] Samgina TY, Artemenko KA, Gorshkov VA, Ogourtsov SV, Zubarev RA, Lebedev AT. De novo sequencing of peptides secreted by the skin glands of the caucasian green frog rana ridibunda. Rapid Commun Mass Spectrom. 2008;22:3517–25.10.1002/rcm.3759Search in Google Scholar PubMed

[79] Falick AM, Hines WM, Medzihradszky KF, Baldwin MA, Gibson BW. Low-mass ions produced from peptides by high-energy collision-induced dissociation in tandem mass spectrometry. J Am Soc Mass Spectrom. 1993;4:882–93.10.1016/1044-0305(93)87006-XSearch in Google Scholar PubMed

[80] Hohmann LJ, Eng JK, Gemmill A, Klimek J, Vitek O, Reid GE, et al. Quantification of the compositional information provided by immonium ions on a quadrupole-time-of-flight mass spectrometer. Anal Chem. 2008;80:5596–606.10.1021/ac8006076Search in Google Scholar PubMed

[81] Mendes MA, De Souza BM, Santos LD, Palma MS. Structural characterization of novel chemotactic and mastoparan peptides from the venom of the social wasp Agelaia pallipes pallipes by high-performance liquid chromatography/electrospray ionization tandem mass spectrometry. Rapid Commun Mass Spectrom. 2004;18:636–42.10.1002/rcm.1382Search in Google Scholar PubMed

[82] Dias NB, De Souza BM, Gomes PC, Brigatte P, Palma MS. Peptidome profiling of venom from the social wasp Polybia paulista. Toxicon. 2015;107:290–303.10.1016/j.toxicon.2015.08.013Search in Google Scholar PubMed

[83] Molina H, Matthiesen R, Kandasamy K, Pandey A. Comprehensive comparison of collision induced dissociation and electron transfer dissociation. Anal Chem. 2008;80:4825–35.10.1021/ac8007785Search in Google Scholar PubMed PubMed Central

[84] Mikesh LM, Ueberheide B, Chi A, Coon JJ, Syka JE, Shabanowitz J, et al. The utility of ETD mass spectrometry in proteomic analysis. Biochim Biophys Acta. 2006;1764:1811–22.10.1016/j.bbapap.2006.10.003Search in Google Scholar PubMed PubMed Central

[85] Liu X, Shan B, Xin L, Ma B. Better score function for peptide identification with ETD MS/MS spectra. BMC Bioinformatics. 2010;11:S1–S4.10.1186/1471-2105-11-S1-S4Search in Google Scholar PubMed PubMed Central

[86] Sadygov RG, Good DM, Swaney DL, Coon JJ. A new probabilistic database search algorithm for ETD spectra. J Proteome Res. 2009;8:3198–205.10.1021/pr900153bSearch in Google Scholar PubMed PubMed Central

[87] Wysocki VH, Resing KA, Zhang Q, Cheng G. Mass spectrometry of peptides and proteins. Methods. 2005;35:211–22.10.1016/j.ymeth.2004.08.013Search in Google Scholar PubMed

[88] Szabo Z, Janaky T. Challenges and developments in protein identification using mass spectrometry. TrAC Trends Anal Chem. 2015;69:76–87.10.1016/j.trac.2015.03.007Search in Google Scholar

[89] Frank A, Pevzner P. PepNovo: de novo peptide sequencing via probabilistic network modeling. Anal Chem. 2005;77:964–73.10.1021/ac048788hSearch in Google Scholar PubMed

[90] Chi H, Chen H, He K. pNovoþ: de novo peptide sequencing using complementary HCD and ETD tandem mass spectra. J Proteome Res. 2013;12:615–25.10.1021/pr3006843Search in Google Scholar PubMed

[91] Ma B. Novor: real-time peptide de novo sequencing software. J Am Soc Mass Spectrom. 2015;26:1885–94.10.1007/s13361-015-1204-0Search in Google Scholar PubMed PubMed Central

[92] Fischer B, Roth V, Roos F, Grossmann J, Baginsky S, Widmayer P, et al. NovoHMM: A hidden Markov model for de novo peptide sequencing. Anal Chem. 2005;77:7265–73.10.1021/ac0508853Search in Google Scholar PubMed

[93] Taylor JA, Johnson RS. Sequence database searches via de novo peptide sequencing by tandem mass spectrometry. Rapid Commun Mass Spectrom. 1997;11:1067–75.10.1002/(SICI)1097-0231(19970615)11:9<1067::AID-RCM953>3.0.CO;2-LSearch in Google Scholar PubMed

[94] Ma B, Zhang K, Hendrie C, Liang C, Li M, Doherty-Kirby A, et al. PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry. Rapid Commun Mass Spectrom. 2003;17:2337–42.10.1002/rcm.1196Search in Google Scholar PubMed

[95] Zhang J, Xin L, Shan B, Chen W, Xie M, Yuen D, et al. PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification. Mol Cell Proteom. 2012;11:1–8.10.1074/mcp.M111.010587Search in Google Scholar

[96] Tanner S, Shu H, Frank A, Wang LC, Zandi E, Mumby M, et al. InsPecT: identification of post translationally modified peptides from tandem mass spectra. Anal Chem. 2005;77:4626–39.10.1021/ac050102dSearch in Google Scholar

[97] Liu C, Yan B, Song Y, Xu Y, Cai L. Peptide sequence tag-based blind identification of post-translational modifications with point process model. Bioinformatics. 2006;22:e307–13.10.1093/bioinformatics/btl226Search in Google Scholar PubMed

[98] Han X, He L, Xin L, Shan B, Ma B. Peaks PTM: mass spectrometry-based identification of peptides with unspecified modifications. J Proteome Res. 2011;10:2930–6.10.1021/pr200153kSearch in Google Scholar

[99] Washburn MP, Wolters D, Yates JR Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat Biotechnol. 2001;19:242–7.10.1038/85686Search in Google Scholar PubMed

[100] Keller A, Nesvizhskii AI, Kolker E, Aebersold R. Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem. 2002;74:5383–92.10.1021/ac025747hSearch in Google Scholar PubMed

[101] MacCoss MJ, Wu CC, Yates JR Probability-based validation of protein identifications using a modified SEQUEST algorithm. Anal Chem. 2002;74:5593–9.10.1021/ac025826tSearch in Google Scholar PubMed

[102] Nesvizhskii AI, Keller A, Kolker E, Aebersold R. A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem. 2003;75:4646–58.10.1021/ac0341261Search in Google Scholar PubMed

[103] Peng J, Elias JE, Thoreen CC, Licklider LJ, Gygi SP. Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome. J Proteome Res. 2003;2:43–50.10.1021/pr025556vSearch in Google Scholar PubMed

[104] Sadygov RG, Liu H, Yates JR Statistical models for protein validation using tandem mass spectral data and protein amino acid sequence databases. Anal Chem. 2004;76:1664–71.10.1021/ac035112ySearch in Google Scholar PubMed

[105] Nesvizhskii AI, Aebersold R. Interpretation of shotgun proteomic data: the protein inference problem. Molecular & Cellular Proteomics. 2005;4:1419–40.10.1074/mcp.R500012-MCP200Search in Google Scholar

[106] Nesvizhskii AI. A survey of computational methods and error rate estimation procedures for peptide and protein identification in shotgun proteomics. J Proteomics. 2010;73:2092–123.10.1016/j.jprot.2010.08.009Search in Google Scholar PubMed

[107] Perkins DN, Pappin DJ, Creasy DM, Cottrell JS. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis. 1999;20:3551–67.10.1002/(SICI)1522-2683(19991201)20:18<3551::AID-ELPS3551>3.0.CO;2-2Search in Google Scholar PubMed

[108] Eng J, McCormack AL, Yates JR An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectrom. 1994;5:976–89.10.1016/1044-0305(94)80016-2Search in Google Scholar

[109] Craig R, Beavis RC. TANDEM: matching proteins with tandem mass spectra. Bioinformatics. 2004;20:1466–7.10.1093/bioinformatics/bth092Search in Google Scholar PubMed

[110] Geer LY, Markey SP, Kowalak JA, Wagner L, Xu M, Maynard DM, et al. Open mass spectrometry search algorithm. J Proteome Res. 2004;3:958–64.10.1021/pr0499491Search in Google Scholar PubMed

[111] Chalkley RJ, Baker PR, Huang L, Hansen KC, Allen NP, Rexach M, et al. Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting quadrupole collision cell, time-of-flight mass spectrometer: II. New developments in protein prospector allow for reliable and comprehensive automatic analysis of large datasets. Mol Cell Proteomics. 2005;4:1194–204.10.1074/mcp.D500002-MCP200Search in Google Scholar PubMed

[112] Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26:1367–72.10.1038/nbt.1511Search in Google Scholar PubMed

[113] Kim S, Mischerikow N, Bandeira N, Navarro JD, Wich L, Mohammed S, et al. The generating function of CID, ETD and CID/ETD pairs of tandem mass spectra: applications to database search. Mol Cell Proteomics. 2010;9:2840–52.10.1074/mcp.M110.003731Search in Google Scholar PubMed

[114] Cantú MD, Carrilho E, Wulff NA, Palma MS Sequenciamento de peptídeos usando espectrometria de massas: um guia prático. Quim Nova. 2008;31:669–75.10.1590/S0100-40422008000300034Search in Google Scholar

[115] Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43:D447–52.10.1093/nar/gku1003Search in Google Scholar PubMed

[116] von Mering C, Jensen LJ, Snel B, Hooper SD, Krupp M, Foglierini M, et al. STRING: known and predicted protein–protein associations, integrated and transferred across organisms. Nucleic Acids Res. 2005;33:D433–7.10.1093/nar/gki005Search in Google Scholar PubMed

[117] Kohlhoff KJ, Robustelli P, Cavalli A, Salvatella X, Vendruscolo M. Fast and accurate predictions of protein NMR chemical shifts from interatomic distances. J Am Chem Soc. 2009;7:13894–5.10.1021/ja903772tSearch in Google Scholar

[118] Wuthrich K. NMR spectra of proteins and nucleic acids in solution. In: Wuthrich K, editor. NMR of proteins and nucleic acids. New York: Wiley, 1986:1–320.Search in Google Scholar

[119] Redfield C. The Application of 1H Nuclear Magnetic Resonance Spectroscopy to the Study of Enzymes. In: Cooper A, Houben J, Chien L, editor(s). The Enzyme Catalysis Process: Energetics, Mechanism and Dynamic. Boston, MA: Springer, 1989:141–58.10.1007/978-1-4757-1607-8_11Search in Google Scholar

[120] Williamson MP, Havel TF, Wüthrich K. Solution confor-mation of proteinase inhibitor IIA from bull seminal plasma by 1H nuclear magnetic resonance and distance geometry. J Mol Biol. 1985;182:295–315.10.1016/0022-2836(85)90347-XSearch in Google Scholar

[121] Ikura M, Kay LE, Bax A. A novel approach for sequential assignment of proton, carbon-13, and nitrogen-15 spectra of larger proteins: heteronuclear triple-resonance three-dimensional NMR spectroscopy. Application to calmodulin. Biochemistry. 1990;29:4659–67.10.1021/bi00471a022Search in Google Scholar PubMed

[122] Clayden J, Greeves N, Warren S, Wothers P. Organic chemistry. New York: Oxford University Press Inc., 2001:1133.Search in Google Scholar

[123] Pomilio AB, Battista ME, Vitale AA. Naturally-occurring cyclopeptides: structures and bioactivity. Curr Org Chem. 2006;10:2075–121.10.2174/138527206778742669Search in Google Scholar

[124] Kaas Q, Craik DJ. NMR of plant proteins. Prog Nucl Magn Reson Spectrosc. 2013;71:1–34.10.1016/j.pnmrs.2013.01.003Search in Google Scholar PubMed

[125] Machado A, Liria CW, Proti PB, Remuzgo C, Miranda MT Chemical and enzymatic peptide synthesis: basic aspects and applications. Quim Nova. 2004;27:781–9.10.1590/S0100-40422004000500018Search in Google Scholar

[126] Bax A. Two-dimensional NMR and protein structures. Annu Rev Biochem. 1989;58:223–56.10.1146/annurev.bi.58.070189.001255Search in Google Scholar

[127] Beck JG, Frank AO, Kessler H. NMR of peptides. In: Bertini I, McGreevy KS, Parigi G, editors. NMR of biomolecules. Weinheim: Wiley-VCH Verlag GmbH & Co. KGaA, 2012:328–44.10.1002/9783527644506.ch19Search in Google Scholar

[128] Bax A. Multidimensional nuclear magnetic resonance methods for protein studies. Curr Opin Struc Biol. 1994;4:738–44.10.1016/S0959-440X(94)90173-2Search in Google Scholar

[129] Cavanagh J, Fairbrother WJ, Palmer AG, Skelton NJ. Protein NMR spectroscopy. Principles and practice, 2nd ed. USA: Academic Press, 2006: 912 pp.Search in Google Scholar

[130] Marion D. An introduction to biological NMR spectroscopy. Mol Cell Proteomics. 2013; 12:3006–25.10.1074/mcp.O113.030239Search in Google Scholar PubMed

[131] Delaglio F, Grzesiek S, Vuister GW, Zhu G, Pfeifer J. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J Biomol NMR. 1995;6:277.10.1007/BF00197809Search in Google Scholar PubMed

[132] Vranken WF, Boucher W, Stevens TJ, Fogh RH, Pajon A, Llinas M, et al. The CCPN Data Model for NMR Spectroscopy: development of a Software Pipeline. Proteins. 2005;59:687–96.10.1002/prot.20449Search in Google Scholar PubMed

[133] Lee W, Tonelli M, Markley JL. NMRFAM-SPARKY: enhanced software for biomolecular NMR spectroscopy. Bioinformatics. 2015;31:1325–7.10.1093/bioinformatics/btu830Search in Google Scholar PubMed

[134] Zimmerman DE, Kulikowski CA, Huang Y, Feng W, Tashiro M, Shimotakahara S, et al. Automated analysis of protein NMR assignments using methods from artificial intelligence. J Mol Biol. 1997;269:592–610.10.1006/jmbi.1997.1052Search in Google Scholar PubMed

[135] DeLano WL. ThePyMOL molecular graphics system. San Carlos, CA: DeLano Scientific, 2002.Search in Google Scholar

[136] Sayle R, Milner-White EJ. RasMol: biomolecular graphics for all. Trends Biochem Sci (TIBS). 1995;20:374.10.1016/S0968-0004(00)89080-5Search in Google Scholar

[137] Humphrey W, Dalke A, Schulten K. VMD - visual molecular dynamics. J Molec Graphics. 1996;14:33–8.10.1016/0263-7855(96)00018-5Search in Google Scholar

[138] Guex N, Peitsch MC. SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis. 1997;18:2714–23.10.1002/elps.1150181505Search in Google Scholar PubMed

[139] NMRipe. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. 2018. https://www.ibbr.umd.edu/nmrpipe/index.html.Search in Google Scholar

[140] CcpNMR. Collaborative computing project for NMR. 2018. https://www.ccpn.ac.uk/about.Search in Google Scholar