German JB, Hammock BD, Watkins SM (2005) Metabolomics: building on a century of biochemistry to guide human health. Metabolomics 1(1):3–9
Article
CAS
PubMed
PubMed Central
Google Scholar
Wishart DS (2007) Current progress in computational metabolomics. Brief Bioinform 8(5):279–293
Article
CAS
PubMed
Google Scholar
Shulaev V (2006) Metabolomics technology and bioinformatics. Brief Bioinform 7(2):128–139
Article
CAS
PubMed
Google Scholar
Kosmides AK et al (2013) Metabolomic fingerprinting: challenges and opportunities. Crit Rev Biomed Eng 41(3):205–221
Article
PubMed
PubMed Central
Google Scholar
Nicholson JK, Wilson ID (2003) Opinion: understanding “global” systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discov 2(8):668–676
Article
CAS
PubMed
Google Scholar
Winnike JH et al (2010) Use of pharmaco-metabonomics for early prediction of acetaminophen-induced hepatotoxicity in humans. Clin Pharmacol Ther 88(1):45–51
Article
CAS
PubMed
Google Scholar
Holmes E et al (2008) Human metabolic phenotype diversity and its association with diet and blood pressure. Nature 453(7193):396–400
Article
CAS
PubMed
PubMed Central
Google Scholar
Beckonert O et al (2007) Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts. Nat Protoc 2(11):2692–2703
Article
CAS
PubMed
Google Scholar
Nicholson JK, Lindon JC, Holmes E (1999) “Metabonomics”: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29(11):1181–1189
Article
CAS
PubMed
Google Scholar
Nicholson JK et al (1995) 750 MHz 1H and 1H–13C NMR spectroscopy of human blood plasma. Anal Chem 67(5):793–811
Article
CAS
PubMed
Google Scholar
Smith CA et al (2006) XCMS: Processing mass spectrometry data for metabolite profiling using Nonlinear peak alignment, matching, and identification. Anal Chem 78(3):779–787
Article
CAS
PubMed
Google Scholar
Dettmer K, Aronov PA, Hammock BD (2007) Mass spectrometry-based metabolomics. Mass Spectrom Rev 26(1):51–78
Article
CAS
PubMed
PubMed Central
Google Scholar
Want EJ, Cravatt BF, Siuzdak G (2005) The expanding role of mass spectrometry in metabolite profiling and characterization. ChemBioChem 6(11):1941–1951
Article
CAS
PubMed
Google Scholar
Dunn WB, Bailey NJ, Johnson HE (2005) Measuring the metabolome: current analytical technologies. Analyst 130(5):606–625
Article
CAS
PubMed
Google Scholar
Hollywood K, Brison DR, Goodacre R (2006) Metabolomics: Current technologies and future trends. Proteomics 6(17):4716–4723
Article
CAS
PubMed
Google Scholar
Moco S et al (2007) Metabolomics technologies and metabolite identification. Trac-Trends Anal Chem 26(9):855–866
Article
CAS
Google Scholar
Smith CA et al (2005) METLIN: a metabolite mass spectral database. Ther Drug Monit 27(6):747–751
Article
CAS
PubMed
Google Scholar
Wishart DS et al (2013) HMDB 3.0–the human metabolome database in 2013. Nucleic Acids Res 41(Database issue):D801–D807
CAS
PubMed
Google Scholar
Ulrich EL et al (2008) BioMagResBank. Nucleic Acids Res 36(Database):D402–D408
Article
CAS
PubMed
Google Scholar
Pence HE, Williams A (2010) ChemSpider: an online chemical information resource. J Chem Educ 87(11):1123–1124
Article
CAS
Google Scholar
Tautenhahn R et al (2012) XCMS online: a web-based platform to process untargeted metabolomic data. Anal Chem 84(11):5035–5039
Article
CAS
PubMed
PubMed Central
Google Scholar
Williams AJ (2008) A perspective of publicly accessible/open-access chemistry databases. Drug Discov Today 13(11–12):495–501
Article
CAS
PubMed
Google Scholar
Sitzmann M, Filippov IV, Nicklaus MC (2008) Internet resources integrating many small-molecule databases. SAR QSAR Environ Res 19(1–2):1–9
Article
CAS
PubMed
Google Scholar
Kutzler FW et al (1983) Charge-Density and bonding in (5,10,15,20-tetramethylporphyrinato)nickel(Ii)—a combined experimental and theoretical-study. J Am Chem Soc 105(10):2996–3004
Article
CAS
Google Scholar
Stimpson DI, Cann JR (1981) A combined theoretical and experimental-study of the interaction of metrizamide with proteins. Arch Biochem Biophys 211(1):403–412
Article
CAS
PubMed
Google Scholar
Cripps SC, Orton RS, Carroll JE (1974) Combined theoretical and experimental studies of a push-pull trapatt circuit. Int J Electron 37(1):1–21
Article
Google Scholar
Gaulton A et al (2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res 40(Database issue):D1100–D1107
Article
CAS
PubMed
Google Scholar
Izgi T et al (2007) FT-IR and NMR investigation of 2-(1-cyclohexenyl)ethylamine: a combined experimental and theoretical study. Spectrochimica Acta Part a Mol Biomol Spectrosc 68(1):55–62
Article
CAS
Google Scholar
de Matos P et al (2010) Chemical entities of biological interest: an update. Nucleic Acids Res 38:D249–D254
Article
PubMed
Google Scholar
Kwan EE, Liu RY (2015) Enhancing NMR prediction for organic compounds using molecular dynamics. J Chem Theory Comput 11(11):5083–5089
Article
CAS
PubMed
Google Scholar
Knox C et al (2011) DrugBank 3.0: a comprehensive resource for “Omics” research on drugs. Nucleic Acids Res 39:D1035–D1041
Article
CAS
PubMed
Google Scholar
Ulrich EL et al (2008) BioMagResBank. Nucleic Acids Res 36:D402–D408
Article
CAS
PubMed
Google Scholar
Wishart DS et al (2009) HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res 37(Database issue):D603–D610
Article
CAS
PubMed
Google Scholar
Blum LC, Reymond JL (2009) 970 million druglike small molecules for virtual screening in the chemical universe database GDB-13. J Am Chem Soc 131(25):8732–8733
Article
CAS
PubMed
Google Scholar
Jewison T et al (2014) SMPDB 2.0: big improvements to the small molecule pathway database. Nucleic Acids Res 42(Database issue):D478–D484
Article
CAS
PubMed
Google Scholar
Frolkis A et al (2010) SMPDB: the small molecule pathway database. Nucleic Acids Res 38(Database issue):D480–D487
Article
CAS
PubMed
Google Scholar
Richard AM, Williams CR (2002) Distributed structure-searchable toxicity (DSSTox) public database network: a proposal. Mutat Res 499(1):27–52
Article
CAS
PubMed
Google Scholar
Guo AC et al (2013) ECMDB: the E. coli metabolome database. Nucleic Acids Res 41(Database issue):D625–D630
CAS
PubMed
Google Scholar
Sajed T et al (2016) ECMDB 2.0: a richer resource for understanding the biochemistry of E. coli. Nucleic Acids Res 44(D1):D495-501
Article
CAS
PubMed
Google Scholar
Keseler IM et al (2017) The EcoCyc database: reflecting new knowledge about Escherichia coli K-12. Nucleic Acids Res 45(D1):D543–D550
Article
CAS
PubMed
Google Scholar
Scalbert A et al (2011) Databases on food phytochemicals and their health-promoting effects. J Agric Food Chem 59(9):4331–4348
Article
CAS
PubMed
Google Scholar
Fahy E et al (2009) Update of the LIPID MAPS comprehensive classification system for lipids. J Lipid Res 50:S9–S14
Article
PubMed
PubMed Central
Google Scholar
Caspi R et al (2018) The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Res 46(D1):D633–D639
Article
CAS
PubMed
Google Scholar
MolMall. [cited 2019 8/1]; http://www.molmall.net/.
Banerjee P et al (2015) Super Natural II-a database of natural products. Nucleic Acids Res 43(D1):D935–D939
Article
CAS
PubMed
Google Scholar
Wishart D et al (2015) T3DB: the toxic exposome database. Nucleic Acids Res 43(Database issue):D928–D934
Article
CAS
PubMed
Google Scholar
Lim E et al (2010) T3DB: a comprehensively annotated database of common toxins and their targets. Nucleic Acids Res 38:D781–D786
Article
CAS
PubMed
Google Scholar
Richard AM et al (2016) ToxCast chemical landscape: paving the road to 21st century toxicology. Chem Res Toxicol 29(8):1225–1251
Article
CAS
PubMed
Google Scholar
Gu JY et al (2013) Use of natural products as chemical library for drug discovery and network pharmacology. PLoS ONE 8(4):e62839
Article
CAS
PubMed
PubMed Central
Google Scholar
Sterling T, Irwin JJ (2015) ZINC 15-ligand discovery for everyone. J Chem Inf Model 55(11):2324–2337
Article
CAS
PubMed
PubMed Central
Google Scholar
Wishart DS (2011) Advances in metabolite identification. Bioanalysis 3(15):1769–1782
Article
CAS
PubMed
Google Scholar
Xiao JF, Zhou B, Ressom HW (2012) Metabolite identification and quantitation in LC-MS/MS-based metabolomics. Trac-Trends Anal Chem 32:1–14
Article
Google Scholar
NIST 17 MS/MS Library. [cited 2019 05.01]. https://www.sisweb.com/software/nist-msms.htm.
The NIST 17 Mass Spectral Library. June 2017 [cited 2019 05.01]. https://www.sisweb.com/software/ms/nist.htm#stats.
The Human Metabolome Library (HML). [cited 2019 05.01]. http://www.hmdb.ca/hml.
Wishart DS et al (2018) HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res 46(D1):D608–D617
Article
CAS
PubMed
Google Scholar
Wishart DS et al (2007) HMDB: the human metabolome database. Nucleic Acids Res 35(Database issue):D521–D526
Article
CAS
PubMed
PubMed Central
Google Scholar
ZINC 15, a free database of commercially-available compounds. [cited 2019 05.01]. http://zinc15.docking.org/.
Sterling T, Irwin JJ (2015) ZINC 15–ligand discovery for everyone. J Chem Inf Model 55(11):2324–2337
Article
CAS
PubMed
PubMed Central
Google Scholar
Styczynski MP et al (2007) Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery. Anal Chem 79(3):966–973
Article
CAS
PubMed
Google Scholar
Staniek A, Woerdenbag HJ, Kayser O (2008) Endophytes: exploiting biodiversity for the improvement of natural product-based drug discovery. J Plant Interact 3(2):75–93
Article
CAS
Google Scholar
Tulp M, Bohlin L (2002) Functional versus chemical diversity: is biodiversity important for drug discovery? Trends Pharmacol Sci 23(5):225–231
Article
CAS
PubMed
Google Scholar
Sumner LW et al (2007) Proposed minimum reporting standards for chemical analysis. Metabolomics 3(3):211–221
Article
CAS
PubMed
PubMed Central
Google Scholar
DeHaven CD et al (2010) Organization of GC/MS and LC/MS metabolomics data into chemical libraries. J Cheminformatics 2:1–12
Article
Google Scholar
Dobson CM (2004) Chemical space and biology. Nature 432(7019):824–828
Article
CAS
PubMed
Google Scholar
Patti GJ et al (2013) A view from above: cloud plots to visualize global metabolomic data. Anal Chem 85(2):798–804
Article
CAS
PubMed
Google Scholar
Weckwerth W (2003) Metabolomics in systems biology. Annu Rev Plant Biol 54:669–689
Article
CAS
PubMed
Google Scholar
Salek RM et al (2013) The role of reporting standards for metabolite annotation and identification in metabolomic studies. Gigascience 2:2047–2217
Article
Google Scholar
Fiehn O et al (2007) The metabolomics standards initiative (MSI). Metabolomics 3(3):175–178
Article
CAS
Google Scholar
Beisken S, Eiden M, Salek RM (2015) Getting the right answers: understanding metabolomics challenges. Expert Rev Mol Diagn 15(1):97–109
Article
CAS
PubMed
Google Scholar
Di Stefano V et al (2012) Applications of liquid chromatography-mass spectrometry for food analysis. J Chromatogr A 1259:74–85
Article
PubMed
Google Scholar
Garcia A, Barbas C (2011) Gas chromatography-mass spectrometry (GC-MS)-based metabolomics. Methods Mol Biol 708:191–204
Article
CAS
PubMed
Google Scholar
Schymanski EL et al (2014) Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol 48(4):2097–2098
Article
CAS
PubMed
Google Scholar
Tang HR et al (2004) Use of relaxation-edited one-dimensional and two dimensional nuclear magnetic resonance spectroscopy to improve detection of small metabolites in blood plasma. Anal Biochem 325(2):260–272
Article
CAS
PubMed
Google Scholar
Nicholson JK, Wilson ID (2003) Understanding “global” systems biology: metabonomics and the continuum of metabolism. Nat Rev Drug Discovery 2(8):668–676
Article
CAS
PubMed
Google Scholar
Kangas LJ et al (2012) In silico identification software (ISIS): a machine learning approach to tandem mass spectral identification of lipids. Bioinformatics 28(13):1705–1713
Article
CAS
PubMed
PubMed Central
Google Scholar
Allen F, Greiner R, Wishart D (2015) Competitive fragmentation modeling of ESI-MS/MS spectra for putative metabolite identification. Metabolomics 11(1):98–110
Article
CAS
Google Scholar
Wolf S et al (2010) In silico fragmentation for computer assisted identification of metabolite mass spectra. BMC Bioinformatics 11:1–12
Article
Google Scholar
Bouteiller Y et al (2008) Transferable specific scaling factors for interpretation of infrared spectra of biomolecules from density functional theory. J Phys Chem A 112(46):11656–11660
Article
CAS
PubMed
Google Scholar
Colby SM et al (2019) ISiCLE: a quantum chemistry pipeline for establishing in silico collision cross section libraries. Anal Chem 91(7):4346–4356
Article
CAS
PubMed
PubMed Central
Google Scholar
Nuñez JR, et al (2018) Advancing Standards-Free Methods for the Identification of Small Molecules in Complex Samples. arXiv preprint arXiv:1810.07367.
Casabianca LB, De Dios AC (2008) Ab initio calculations of NMR chemical shifts. J Chem Phys 128(5):052201
Article
PubMed
Google Scholar
Lodewyk MW, Siebert MR, Tantillo DJ (2012) Computational prediction of 1H and 13C chemical shifts: a useful tool for natural product, mechanistic, and synthetic organic chemistry. Chem Rev 112(3):1839–1862
Article
CAS
PubMed
Google Scholar
Hill DE, Vasdev N, Holland JP (2015) Evaluating the accuracy of density functional theory for calculating H-1 and C-13 NMR chemical shifts in drug molecules. Comput Theor Chem 1051:161–172
Article
CAS
Google Scholar
Lomas JS (2016) H-1 NMR spectra of alcohols in hydrogen bonding solvents: DFT/GIAO calculations of chemical shifts. Magn Reson Chem 54(1):28–38
Article
CAS
PubMed
Google Scholar
Zheng XY et al (2017) Structural elucidation of cis/trans dicaffeoylquinic acid photoisomerization using ion mobility spectrometry-mass spectrometry. J Phys Chem Lett 8(7):1381–1388
Article
CAS
PubMed
PubMed Central
Google Scholar
Zheng XY et al (2017) Enhancing glycan isomer separations with metal ions and positive and negative polarity ion mobility spectrometry-mass spectrometry analyses. Anal Bioanal Chem 409(2):467–476
Article
CAS
PubMed
Google Scholar
Nunez JR et al (2019) Evaluation of in silico multi-feature libraries for providing evidence for the presence of small molecules in synthetic blinded samples. J Chem Inf Model 59(9):4052–4060
Article
CAS
PubMed
PubMed Central
Google Scholar
Forsyth DA, Sebag AB (1997) Computed C-13 NMR chemical shifts via empirically scaled GIAO shieldings and molecular mechanics geometries. Conformation and configuration from C-13 shifts. J Am Chem Soc 119(40):9483–9494
Article
CAS
Google Scholar
Auer AA, Gauss J, Stanton JF (2003) Quantitative prediction of gas-phase C-13 nuclear magnetic shielding constants. J Chem Phys 118(23):10407–10417
Article
CAS
Google Scholar
Mothana B, Ban FQ, Boyd RJ (2005) Validation of a computational scheme to study N-15 and C-13 nuclear shielding constants. Chem Phys Lett 401(1–3):7–12
Article
CAS
Google Scholar
Saito H (1986) Conformation-dependent C-13 chemical-shifts—a new means of conformational characterization as obtained by high-resolution solid-state C-13 Nmr. Magn Reson Chem 24(10):835–852
Article
CAS
Google Scholar
Jaime C et al (1991) C-13 Nmr chemical-shifts—a single rule to determine the conformation of Calix[4]Arenes. J Org Chem 56(10):3372–3376
Article
CAS
Google Scholar
Yannoni CS et al (1991) C-13 Nmr-study of the C60 cluster in the solid-state—molecular-motion and carbon chemical-shift anisotropy. J Phys Chem 95(1):9–10
Article
CAS
Google Scholar
Malkin VG et al (1996) Solvent effect on the NMR chemical shieldings in water calculated by a combination of molecular dynamics and density functional theory. Chem Eur J 2(4):452–457
Article
CAS
Google Scholar
Casanovas J et al (2001) Calculated and experimental NMR chemical shifts of p-menthane-3,9-diols. A combination of molecular dynamics and quantum mechanics to determine the structure and the solvent effects. J Org Chem 66(11):3775–3782
Article
CAS
PubMed
Google Scholar
Benzi C et al (2004) Reliable NMR chemical shifts for molecules in solution by methods rooted in density functional theory. Magn Reson Chem 42:S57–S67
Article
CAS
PubMed
Google Scholar
Kiamco MM et al (2018) Structural and metabolic responses of Staphylococcus aureus biofilms to hyperosmotic and antibiotic stress. Biotechnol Bioeng 115(6):1594–1603
Article
CAS
PubMed
PubMed Central
Google Scholar
Dreyer DR et al (2012) Elucidating the structure of poly(dopamine). Langmuir 28(15):6428–6435
Article
CAS
PubMed
Google Scholar
Xin DY et al (2017) Development of a C-13 NMR chemical shift prediction procedure using B3LYP/cc-pVDZ and empirically derived systematic error correction terms: a computational small molecule structure elucidation method. J Org Chem 82(10):5135–5145
Article
CAS
PubMed
Google Scholar
Garcellano RC et al (2018) Isolation of tryptanthrin and reassessment of evidence for its isobaric isostere wrightiadione in plants of the wrightia genus. J Nat Prod 82(3):440–448
Article
PubMed
Google Scholar
Kutateladze AG, Reddy DS (2017) High-throughput in silico structure validation and revision of halogenated natural products is enabled by parametric corrections to DFT-computed 13C NMR chemical shifts and spin-spin coupling constants. J Org Chem 82(7):3368–3381
Article
CAS
PubMed
Google Scholar
Kutateladze AG, Krenske EH, Williams CM (2019) Reassignments and corroborations of oxo-bridged natural products directed by OSE and DU8+ NMR computation. Angew Chem Int Ed Engl 58(21):7107–7112
Article
CAS
PubMed
Google Scholar
Jain R, Bally T, Rablen PR (2009) Calculating accurate proton chemical shifts of organic molecules with density functional methods and modest basis sets. J Org Chem 74(11):4017–4023
Article
CAS
PubMed
Google Scholar
Perez M et al (2006) Accuracy vs time dilemma on the prediction of NMR chemical shifts: a case study (chloropyrimidines). J Org Chem 71(8):3103–3110
Article
CAS
PubMed
Google Scholar
Barone G et al (2002) Determination of the relative stereochemistry of flexible organic compounds by ab initio methods: conformational analysis and Boltzmann-averaged GIAO C-13 NMR chemical shifts. Chem Eur J 8(14):3240–3245
Article
CAS
PubMed
Google Scholar
Barone G et al (2002) Structure validation of natural products by quantum-mechanical GIAO calculations of C-13 NMR chemical shifts. Chem Eur J 8(14):3233–3239
Article
CAS
PubMed
Google Scholar
Remya K, Suresh CH (2013) Which density functional is close to CCSD accuracy to describe geometry and interaction energy of small non-covalent dimers? A benchmark study using gaussian09. J Comput Chem 34(15):1341–1353
Article
CAS
PubMed
Google Scholar
Zhao Y, Truhlar DG (2008) Improved description of nuclear magnetic resonance chemical shielding constants using the M06-L meta-generalized-gradient-approximation density functional. J Phys Chem A 112(30):6794–6799
Article
CAS
PubMed
Google Scholar
Magyarfalvi G, Pulay P (2003) Assessment of density functional methods for nuclear magnetic resonance shielding calculations. J Chem Phys 119(3):1350–1357
Article
CAS
Google Scholar
Cimino P et al (2004) Comparison of different theory models and basis sets in the calculation of C-13 NMR chemical shifts of natural products. Magn Reson Chem 42:S26–S33
Article
CAS
PubMed
Google Scholar
Tormena CF, da Silva GVJ (2004) Chemical shifts calculations on aromatic systems: a comparison of models and basis sets. Chem Phys Lett 398(4–6):466–470
Article
CAS
Google Scholar
Cramer CJ, Truhlar DG (1999) Implicit solvation models: equilibria, structure, spectra, and dynamics. Chem Rev 99(8):2161–2200
Article
CAS
PubMed
Google Scholar
Wiitala KW, Hoye TR, Cramer CJ (2006) Hybrid density functional methods empirically optimized for the computation of C-13 and H-1 chemical shifts in chloroform solution. J Chem Theory Comput 2(4):1085–1092
Article
CAS
PubMed
Google Scholar
Reddy G, Yethiraj A (2006) Implicit and explicit solvent models for the simulation of dilute polymer solutions. Macromolecules 39(24):8536–8542
Article
CAS
Google Scholar
Smirnov SN et al (1996) Hydrogen deuterium isotope effects on the NMR chemical shifts and geometries of intermolecular low-barrier hydrogen-bonded complexes. J Am Chem Soc 118(17):4094–4101
Article
CAS
Google Scholar
Benedict H et al (1996) Hydrogen/deuterium isotope effects on the N-15 NMR chemical shifts and geometries of low-barrier hydrogen bonds in the solid state. J Mol Struct 378(1):11–16
Article
CAS
Google Scholar
Gidley MJ, Bociek SM (1988) C-13 Cp/Mas Nmr-studies of amylose inclusion complexes, cyclodextrins, and the amorphous phase of starch granules—relationships between glycosidic linkage conformation and solid-state C-13 chemical-shifts. J Am Chem Soc 110(12):3820–3829
Article
CAS
Google Scholar
Buckingham AD (1960) Chemical shifts in the nuclear magnetic resonance spectra of molecules containing polar groups. Can J Chem Revue Canadienne De Chimie 38(2):300–307
Article
CAS
Google Scholar
Osmialowski B, Kolehmainen E, Gawinecki R (2001) GIAO/DFT calculated chemical shifts of tautomeric species 2-Phenacylpyridines and (Z)-2-(2-hydroxy-2-phenylvinyl)pyridines. Magnet Reson Chem 39(6):334–340
Article
CAS
Google Scholar
Gauss J (1993) Effects of electron correlation in the calculation of nuclear-magnetic-resonance chemical-shifts. J Chem Phys 99(5):3629–3643
Article
CAS
Google Scholar
Gao HW et al (2010) Comparison of different theory models and basis sets in the calculations of structures and C-13 NMR spectra of [Pt(en)(CBDCA-O, O’)], an analogue of the antitumor drug carboplatin. J Phys Chem B 114(11):4056–4062
Article
CAS
PubMed
Google Scholar
Wu A et al (2007) Systematic studies on the computation of nuclear magnetic resonance shielding constants and chemical shifts: the density functional models. J Comput Chem 28(15):2431–2442
Article
CAS
PubMed
Google Scholar
Giesen DJ, Zumbulyadis N (2002) A hybrid quantum mechanical and empirical model for the prediction of isotropic C-13 shielding constants of organic molecules. Phys Chem Chem Phys 4(22):5498–5507
Article
CAS
Google Scholar
Hoffmann F et al (2017) Improved quantum chemical NMR chemical shift prediction of metabolites in aqueous solution toward the validation of unknowns. J Phys Chem A 121(16):3071–3078
Article
CAS
PubMed
PubMed Central
Google Scholar
Aliev AE, Courtier-Murias D, Zhou S (2009) Scaling factors for carbon NMR chemical shifts obtained from DFF B3LYP calculations. J Mol Struct Theochem 893(1–3):1–5
Article
CAS
Google Scholar
Willoughby PH, Jansma MJ, Hoye TR (2014) A guide to small-molecule structure assignment through computation of (H-1 and C-13) NMR chemical shifts. Nat Protoc 9(3):643–660
Article
CAS
PubMed
Google Scholar
Pierens GK (2014) H-1 and C-13 NMR scaling factors for the calculation of chemical shifts in commonly used solvents using density functional theory. J Comput Chem 35(18):1388–1394
Article
CAS
PubMed
Google Scholar
Caputo MC, Provasi PF, Sauer SPA (2018) The role of explicit solvent molecules in the calculation of NMR chemical shifts of glycine in water. Theor Chem Accounts 137(7):1–8
Article
CAS
Google Scholar
Feunang YD et al (2016) ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J Cheminformatics 8:1–20
Google Scholar
Yesiltepe Y et al (2018) An automated framework for NMR chemical shift calculations of small organic molecules. J Cheminformatics 10:1–16
Article
Google Scholar
Koster J, Rahmann S (2012) Snakemake-a scalable bioinformatics workflow engine. Bioinformatics 28(19):2520–2522
Article
PubMed
Google Scholar
Weininger D (1988) Smiles, a chemical language and information-system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 28(1):31–36
Article
CAS
Google Scholar
Valiev M et al (2010) NWChem: a comprehensive and scalable open-source solution for large scale molecular simulations. Comput Phys Commun 181(9):1477–1489
Article
CAS
Google Scholar
Lee CT, Yang WT, Parr RG (1988) Development of the colle-salvetti correlation-energy formula into a functional of the electron-density. Phys Rev B 37(2):785–789
Article
CAS
Google Scholar
Becke AD (1993) A new mixing of hartree-fock and local density-functional theories. J Chem Phys 98(2):1372–1377
Article
CAS
Google Scholar
Binkley JS, Pople JA, Hehre WJ (1980) Self-consistent molecular-orbital methods. 21. Small split-valence basis-sets for 1st-row elements. J Am Chem Soc 102(3):939–947
Article
CAS
Google Scholar
Gordon MS et al (1982) Self-consistent molecular-orbital methods. 22. Small split-valence basis-sets for 2nd-row elements. J Am Chem Soc 104(10):2797–2803
Article
CAS
Google Scholar
Schuchardt KL et al (2007) Basis set exchange: a community database for computational sciences. J Chem Inf Model 47(3):1045–1052
Article
CAS
PubMed
Google Scholar
Saielli G et al (2011) Addressing the stereochemistry of complex organic molecules by density functional theory-NMR: vannusal B in retrospective. J Am Chem Soc 133(15):6072–6077
Article
CAS
PubMed
PubMed Central
Google Scholar
Tantillo DJ (2013) Walking in the woods with quantum chemistry—applications of quantum chemical calculations in natural products research. Nat Prod Rep 30(8):1079–1086
Article
CAS
PubMed
Google Scholar
Klamt A, Schüürmann G (1993) COSMO: a new approach to dielectric screening in solvents with explicit expressions for the screening energy and its gradient. J Chem Soc Perkin Trans 2(5):799–805
Article
Google Scholar
Feller D (1996) The role of databases in support of computational chemistry calculations. J Comput Chem 17(13):1571–1586
Article
CAS
Google Scholar
Xin D et al (2017) Development of a (13)C NMR chemical shift prediction procedure using B3LYP/cc-pVDZ and empirically derived systematic error correction terms: a computational small molecule structure elucidation method. J Org Chem 82(10):5135–5145
Article
CAS
PubMed
Google Scholar
Ditchfield R (1974) Self-consistent perturbation-theory of diamagnetism. 1. Gauge-invariant Lcao method for Nmr chemical-shifts. Mol Phys 27(4):789–807
Article
CAS
Google Scholar
Oliveira FM et al (2016) Evaluation of some density functional methods for the estimation of hydrogen and carbon chemical shifts of phosphoramidates. Comput Theor Chem 1090:218–224
Article
CAS
Google Scholar
Smith SG, Goodman JM (2010) Assigning stereochemistry to single diastereoisomers by GIAO NMR calculation: the DP4 probability. J Am Chem Soc 132(37):12946–12959
Article
CAS
PubMed
Google Scholar
Grimblat N, Zanardi MM, Sarotti AM (2015) Beyond DP4: an Improved probability for the stereochemical assignment of isomeric compounds using quantum chemical calculations of NMR shifts. J Org Chem 80(24):12526–12534
Article
CAS
PubMed
Google Scholar
Navarro-Vazquez A (2017) State of the art and perspectives in the application of quantum chemical prediction of H-1 and C-13 chemical shifts and scalar couplings for structural elucidation of organic compounds. Magn Reson Chem 55(1):29–32
Article
CAS
PubMed
Google Scholar
Ermanis K et al (2017) Doubling the power of DP4 for computational structure elucidation. Org Biomol Chem 15(42):8998–9007
Article
CAS
PubMed
Google Scholar
Renslow RS et al (2014) A biofilm microreactor system for simultaneous electrochemical and nuclear magnetic resonance techniques. Water Sci Technol 69(5):966–973
Article
CAS
PubMed
Google Scholar
Sutovich KJ et al (1999) Simultaneous quantification of Bronsted- and Lewis-acid sites in a USY zeolite. J Catal 183(1):155–158
Article
CAS
Google Scholar
Mueller LJ (1997) Chemical exchange in nuclear magnetic resonance. California Institute of Technology
Google Scholar
Munkres J (1957) Algorithms for the assignment and transportation problems. J Soc Ind Appl Math 5(1):32–38
Article
Google Scholar
Kuhn HW (1955) The Hungarian method for the assignment problem. Naval Res Logist Q 2(1):83–97
Article
Google Scholar
Kuhn HW (1956) Variants of the Hungarian method for assignment problems. Naval Res Logist Q 3(4):253–258
Article
Google Scholar
Cui H, et al (2016) Solving large-scale assignment problems by Kuhn-Munkres algorithm. In: Proceedings of the 2nd international conference on advances in mechanical engineering and industrial informatics (Ameii 2016), vol 73, pp 822–827.
NaganaGowda GA, Raftery D (2017) Recent advances in NMR-based metabolomics. Anal Chem 89(1):490–510
Article
CAS
Google Scholar
Bingol K (2018) Recent advances in targeted and untargeted metabolomics by NMR and MS/NMR methods. High Throughput 7(2):9
Article
CAS
PubMed Central
Google Scholar
Hogben HJ et al (2011) Spinach–a software library for simulation of spin dynamics in large spin systems. J Magn Reson 208(2):179–194
Article
CAS
PubMed
Google Scholar
Bingol K et al (2015) Metabolomics beyond spectroscopic databases: a combined MS/NMR strategy for the rapid identification of new metabolites in complex mixtures. Anal Chem 87(7):3864–3870
Article
CAS
PubMed
PubMed Central
Google Scholar