Identification and structure elucidation by NMR spectroscopyMikhail Elyashberg *Advanced Chemistry Development, Moscow Department, 6 Akademik Bakulev Street, Moscow 117513, Russian Federation

A R T I C L E I N F O

Keywords:CASEComputer-assisted structure elucidationDereplicationExpert systemHydrogen-deficient moleculeNMRNuclear magnetic resonanceStructure elucidationStructure identificationStructure verification

A B S T R A C T

The state of the art and recent developments in application of nuclear magnetic resonance (NMR) forstructure elucidation and identification of small organic molecules are discussed. The recently sug-gested new two-dimensional (2D)-NMR experiments combined with the advanced instrumentation allowstructure elucidation of new organic compounds at a sample amount of less than 10 μg. A pure shift ap-proach that provides 1H-decoupled proton spectra drastically simplified 1H and 2D NMR spectrainterpretation. The structure elucidation of extremely hydrogen-deficient compounds was dramaticallyfacilitated due to the methodology based on combination of new 2D-NMR experiments providing long-range heteronuclear correlations with computer-assisted structure elucidation (CASE). The capabilitiesof CASE systems are discussed. The role of NMR-spectrum prediction in structure verification and NMRapproaches for qualitative mixture analysis are considered.

© 2015 Elsevier B.V. All rights reserved.

Contents

1. Introduction ........................................................................................................................................................................................................................................................... 882. Common set of 1D- and 2D-NMR experiments ........................................................................................................................................................................................ 893. Development of NMR experiments and instrumentation ..................................................................................................................................................................... 894. CASE expert systems .......................................................................................................................................................................................................................................... 935. NMR chemical-shift prediction ...................................................................................................................................................................................................................... 946. Structure verification ......................................................................................................................................................................................................................................... 947. Structure identification and dereplication in mixtures .......................................................................................................................................................................... 948. Is it possible to avoid an erroneous structure elucidation? ................................................................................................................................................................. 959. Conclusions ............................................................................................................................................................................................................................................................ 95

Acknowledgements ............................................................................................................................................................................................................................................. 95References .............................................................................................................................................................................................................................................................. 95

1. Introduction

Molecular structure determination is a central theme of organicand analytical chemistry. Nuclear magnetic resonance (NMR) spec-troscopy in combination with high-resolution mass-spectrometry(HRMS) makes up a basic set of methods to solve this problem. Giventhe molecular formula of a complex organic molecule that has beendetermined using HRMS, two-dimensional (2D)-NMR plays a crucialrole in structure elucidation. In this review, we consider applica-tion of NMR to determine structures of small organic molecules. Theresults achieved in this area were discussed in monographs [1,2]and reviews [3–9], including two comprehensive reviews pub-lished recently [8,9].

To make clear the issues being discussed in this review, it is nec-essary to consider some basic concepts. The first step in the structuredetermination of an unknown is a spectral search against the rel-evant available databases using MS and NMR spectra. If the spectrumof the unknown fully coincides with a reference spectrum, it meansthat the structural formula of the unknown is identical to that ofthe reference. This is termed as structure identification. Otherwise,the problem of structure elucidation arises. Given the structure iselucidated, it is necessary to establish if the compound is new. Thestructural search against corresponding databases {see review [10]}to answer this question is called dereplication. This procedure is alsointerpreted in literature as a structural identification of a knownchemical entity based on previously reported analytical and spec-troscopic information [11].

Structure elucidation is obviously the most complicated task. Itis related to the class of inverse problems [12] for which solution am-biguity is a distinctive peculiarity. A single solution is selected byimposing additional constraints. On the whole, the problem of

* Tel.: +7 495 438 2153; Fax: +4954382874.E-mail address: elyas@acdlabs.ru

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Trends in Analytical Chemistry 69 (2015) 88–97

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structure elucidation from 2D-NMR data can be presented as a com-bination of two inverse problems, which should be solved inconsecutive order [2]. The first problem is to determine all (if pos-sible) pairs of atoms (nuclei) in the molecule for which there existcorrelations observed in 1D and available 2D-NMR spectra. Thisgoal is achieved as a result of interpretation of 1D- and 2D-NMRspectra, which may admit alternative solutions due to resonanceoverlap and other reasons. The second problem is to determine allstructures that meet the revealed set of coupled nuclei and then toselect the most probable structure by imposing additional con-straints coming from characteristic spectral features, NMR chemical-shift prediction and chemical knowledge. It is evident that thesolution of the second, main, problem strongly depends on thesolution of the first problem. If erroneous spin couplings leak intothe solution of the first problem, the possibility of a correct struc-ture becomes problematic.

Analysis of spectroscopists’ reasoning during structure elucida-tion led to the conclusion that initial NMR-based information usedfor this goal could be represented as a set of “axioms”, which makeup a partial axiomatic theory formulated specifically for a givenproblem [1,2,13]. Hence, the problem reduces to inferring all plau-sible structures from the set of axioms. The axioms can be readilyformalized, and provide a theoretical basis for creation of algo-rithms for computer-assisted structure elucidation (CASE).

Note that both a human expert and a CASE program commonlyuse the same set of axioms, but the program is not governed by thechemical “prejudices” of the human mind and delivers all (withoutany exception) structures satisfying the given set of axioms adoptedby the chemist. This task, as a rule, is impossible for a human expert.The program finds solution far more quickly and more reliably [13].

Generally speaking, progress in the reviewed area is going onin the following two directions:

• suggestion of new NMR experiments and instrumentation forreliably acquiring as much structural information as possible fromthe smallest amounts of sample [8,14,15] in the shortest time(provides solution to the first inverse problem); and,

• enhancing the performance of the existing CASE programs andcreating new ones (provides solution to the second inverseproblem).

This review discusses the state of progress in solving theseproblems.

2. Common set of 1D- and 2D-NMR experiments

1H- and 13C-NMR spectra carry information about the qualita-tive and quantitative composition of an unknown and they are usedfirst for the determination of the molecular formula. Along with 1D1H- and 13C (15N if available)-NMR spectra, many two-dimensionalNMR experiments were developed for structure elucidation [16,17].For molecules containing nitrogen atoms, resonances of 15N nucleiare determined from 1H-15N heteronuclear single-quantum corre-lation (HSQC) and 1H-15N heteronuclear multi-bond correlation(HMBC) 2D spectra (see below). The most frequently used set of 2D-NMR experiments is presented in Table 1.

The correlation spectroscopy (COSY) and HMBC correlationswhose lengths most frequently do not exceed three bonds are re-ferred to as standard correlations [1]. However, depending on thespatial configuration of a molecule, correlations longer than stan-dard correlations can also be observed. These correlations are referredto as non-standard correlations (NSCs). The presence of NSCs, theirnumber and lengths in HMBC and COSY spectra are difficult to detect,and this issue can make the initial information not only fuzzy butalso contradictory.

3. Development of NMR experiments and instrumentation

The latest advances in development and improvements of 2D-NMR experiments were extensively considered in recently publishedreviews [6,8,19–24]. Significant efforts of researchers were focusedon creating methods for detecting correlations whose lengths could(at least in principle) be unambiguously determined. For example,distinguishing between correlations of coupling constants 2JCH and3JCH in the HMBC spectrum leads to obtaining crisper 2D-NMR struc-tural information. Different methods were suggested to reduce thetime for spectral acquisition, to increase sensitivity and to simpli-fy post-acquisition processing of 2D-NMR data. Some 2D-NMRexperiments that complement those shown in Table 1 are enumer-ated in Table 2.

From the standpoint of a protocol for elucidating chemical struc-ture, a 1H spectrum is almost always recorded first. The next stepis the acquisition of 2D-NMR data, and it is recommended to startwith a multiplicity-edited HSQC (ME-HSQC) spectrum [5]. The HSQCdata may provide some insight into the numbers of possible het-eroatoms, as well as a partial carbon count. The next step is to acquirea COSY spectrum. Having in hand 1H, COSY and ME-HSQC, it is pos-sible to begin to assemble structural fragments comprising thecontiguous protonated carbon resonances.

Having the molecular formula from HRMS and HSQC, it is pos-sible to establish the expected number of signals of quaternarycarbons in 13C-NMR spectrum and the minimum number of het-eroatoms. Then, the HMBC spectrum is acquired, and in principle,allows one to complete assembly of the structure.

If the molecule contains nitrogen atoms, employing the 1H-15NHMBC spectrum gives valuable information that is crucial for the struc-ture elucidation in many cases {see reviews [30–34]}. Low sensitivityof the 1H-15N HMBC experiment is overcome using small-volume

Table 1The most frequently used set of 2D NMR experiments [16]

Experiment Characteristics

HSQC,HeteronuclearSingle QuantumCoherence

The HSQC spectrum shows resonances (heteronuclearcorrelations) which arise as a result of 1JCH couplingsbetween 13C nuclei and protons attached to thecorresponding atoms. This allows one to detect all CH, CH2

and CH3 groups with chemical shift assignment. ME-HSQC(Multiplicity Edited HSQC) alleviates distinguishingresponses from CH3, CH2 and CH groups in HSQC spectrumobviating the acquisition of DEPT data.

COSY, CorrelationSpectroscopy

The COSY spectrum usually reveals homonuclearcorrelations (spin couplings) between vicinal hydrogensseparated by three bonds (3JHH). This makes it possible toidentify the neighbor carbon atoms connected by achemical bond.

TOCSY, TotalCorrelationSpectroscopy

TOCSY allows one, in principle, to obtain sub-spectra fordifferent sequences of coupled protons in a molecule.In practice, investigators usually acquire only one of thespectra.

HMBC,HeteronuclearMultiple-BondCoherence

The HMBC spectrum reveals heteronuclear correlationsbetween 1H and 13C (15N) nuclei separated by two or threechemical bonds, allowing users to detect ”fuzzy”fragments around a given C or N atom. There is no routineapproach that would allow determining which intervening1H-13C pairs are separated by two bonds and which – bythree. Therefore the information carried by HMBC is fuzzyby nature. 1H-13C HMBC data are made even more “fuzzy”by the occasional observation of 4JCH correlations. Incontrast, for conventional 1H -15N HMBC, 4JNH correlationsare almost never observed.

NOESY, NuclearOverhauserEnhancementSpectroscopy

ROESY, Rotatedframe NOESpectroscopy

The NOESY/ROESY [18] reveals couplings betweenhydrogen atoms separated in space by distance <5 Å, ,which is used for determining stereochemistry of anelucidated structure, as well as for clarifying positions ofsome substituents if HMBC and COSY data do not allow todo that. These spectra are usually not used duringstructure assembly.

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inverse probes and/or cryogenic NMR probes, which allow acquisi-tion of spectra on sub-micromole quantities of samples [35]. Thenumber of publications in which 1H-15N HMBC is utilized is con-stantly growing. The very recently reported new experiments on long-range heteronuclear single quantum multiple bond correlation(LR-HSQMBC) optimized for 1H-15N long-range heteronuclear cou-plings [36] and H-C-N multiple-bond correlation (HCNMBC) [37,38]produced data complementary to 1H-15N HMBC-type correlations. Itis expected that such experiments can facilitate the structure eluci-dation of nitrogen-containing molecules, particularly those belongingto heterocyclic compounds and alkaloids.

In comparison with MS and optical spectroscopy, NMR pos-sesses significantly less sensitivity, which becomes especially notableregarding the sample size and the acquisition time of 2D-NMR. Asa result of technical progress, cooled microprobes became available[39,40].

Hilton and Martin [35] investigated experimental performancelimits for an ensemble of 2D-NMR experiments using a 600 MHzspectrometer with 1.7 mm Bruker TCI MicroCryoProbe. A solutioncontaining 870 μg (2.6 μmol) of a model compound – strychninein 30 μL of CDCl3 – was used. The following acquisition times toobtain adequate signal-to-noise ratios were determined: COSY –7 min; rotating-frame Overhauser-effect spectroscopy (ROESY) –1 h 11 min; 13C reference – 25 min; ME-HSQC – 7 min; 1H-13CHMBC – 33 min; 1H-13C heteronuclear 2-bond correlation (H2BC)– 3 h 11 min; 1H-15N HMBC – 1 h 22 min; adequate sensitivitydouble-quantum spectroscopy (1,1-ADEQUATE) – 14 h 40 min.Further dilutions have shown that, with samples of 45 μg (150 nmol)even 1H-15N HMBC remains accessible experimentally over aweekend. The authors [35] concluded that, with a 1 mg sample ofstrychnine (~3 μmol), it is now possible to acquire the full set ofhomonuclear and heteronuclear 2D-NMR experiments in 4 h (in-cluding 1H -15N HMBC but not 1,1-ADEQUATE) that could, in principle,be used to establish the full chemical structure and stereochemis-try. Using the same equipment as in [35], high signal-to-noise pureshift (see below) HSQC data from a 7.4 μg metabolite sample wereacquired in just over 30 min [41].

Structure elucidation becomes especially challenging for mol-ecules for which a severe deficit of protons is inherent. Thesemolecules contain “silent” (deprived of hydrogen) fragments, whichprevent structure assembly using HMBC correlations. If the ratio ofthe number of protons in a molecule to the sum of the heavy atoms(e.g., C, N, O, and S) is <2, it may be difficult and, in some cases, im-possible to elucidate a structure unequivocally based solely on NMRdata and molecular formula information. This statement is knownas the “Crews rule” [42]. To circumvent this issue, several new ap-proaches were suggested.

Gross and co-workers were the first to employ atomic force mi-croscopy (AFM) [43] to determine a challenging structure of a smallmolecule by making an image of its skeleton visible. Then, AFM com-bined with 1D- and 2D-NMR, density functional theory (DFT) andCASE system ACD/Structure Elucidator [44] (see Section 4) was used[45] to determine the structure of natural product breitfussin A,Structure 1(a “silent” fragment is highlighted in bold).

A new, high-sensitivity experiment complementary to HMBC, LR-HSQMBC [46] extends the observation of long-range correlation datato 4-, 5-, and even 6-bond long-range nJCH heteronuclear cou-plings. The correlation lengths can be estimated from nJCH, for whichexperiments were optimized. These correlations can reach quater-nary carbons of “silent” fragments, allowing structure elucidation.Proton-deficient model compound cervinomycin A2, Structure 2,C29H21NO9, was used [27] to assess the benefits of including LR-HSQMBC data as input for ACD/Structure Elucidator. Fig. 1 showsthe observed LR-HSQMBC correlations (optimized at 2 Hz).

Table 2Experiments complementing the most frequently used 2D NMR techniques

Method Characteristics

HSQC-TOCSY The 1H-13C HSQC-TOCSY experiment combines 1H-13C HSQCwith a 1H-TOCSY experiments to give through-bondcorrelations between a 13C-attached 1H to all other coupled1H. The resonances of coupled protons can be seen along aline at the same 13C chemical shift from the carbon atomattached to the primary 1H [16].

CIGAR-CHMBC Makes it much easier to interpret the spectrum, particularlyin the crowded regions. Is the best of the existing HMBCsequences in terms of information content and ease ofinterpretation [20].

2J,3J-HMBC Affords the means of unequivocally differentiating between2JCH from 3JCH correlations. Peaks of 2JCH have skewcharacteristics, while 2JCH signals for quaternary carbons aremissing. It also suffers from a severe lack of sensitivity(almost 10 times lower than for HMBC) [20]

1H-13C H2BC HMBC-type spectrum almost exclusively showing onlytwo-bond correlations and markedly also two-bondcorrelations that are absent in HMBC spectra. As a rule,correlations that are strong in an H2BC spectrum and weakin an HMBC spectrum indicate two-bond correlations. H2BCand HMBC are therefore quite complementary. Drawbacksare that H2BC spectra only show peaks involving protonated13C carbons, they cannot identify adjacent quaternarycarbon resonances. In addition there is no absoluteguarantee that a peak in an H2BC spectrum represents atwo-bond correlation [20].

ADEQUATE 1,1-ADEQUATE exploits 1JCH and 1JCC couplings to allow theidentification of adjacent neighbor carbons. Both protonatedand non-protonated adjacent carbons are observed.Correlations are equivalent to 2JCH correlations inHMBC-type experiments. Method suffers from sensitivityand sample limitations, which are overcome by employingsmall volume high sensitivity and cryogenic NMR probes[19].1,n- ADEQUATE [19,25] provides predominantly 3JCC long-range correlations that are analogous to 4JCH HMBCcorrelations. Though it is less sensitive than 1,1-ADEQUATEand 1JCC correlations “leak” into the spectrum, it has beenshown [26–28] that 1,n-ADEQUATE data acquired using1.7 mm cryoprobe technology are very helpful for structurecharacterization of proton-deficient molecules whosestructures are extremely difficult to elucidate byconventional HMBC. Advantages of ADEQUATE over HMBCwere demonstrated experimentally in combination withquantum-chemical coupling constant computations [28].

INADEQUATE A COSY-like experiment that yields 13C-13C correlations. It iscapable of establishing the identity of adjacent neighborcarbons via 1JCC couplings. Major drawbacks of theINADEQUATE experiment are extreme insensitivity andprodigious sample requirements (>10 mg). To an extent, thelimitations of the experiment have been overcome by thedevelopment of small volume high sensitivity and cryogenicNMR probes [29].

Structure 1. Natural product breitfussin A.

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The results of computational experiments (Table 3) clearly showthat complementing the standard 2D-NMR set by 1H-13C LR-HSQMBC data dramatically accelerates structure generation andreduces the size of the output file.

Blinov et al. [27] performed analogous computational experi-ments using staurosporine, C28H26N4O3, (a “Screw structure”), as amodel compound. In this case, the set of experiments shown inTable 3 was complemented by IDR-HSQC-total correlation spec-troscopy (TOCSY), 1H-15N HMBC, 1,1-ADEQUATE and 1,-n-ADEQUATE.The results obtained were very interesting and highlighted the con-tribution of the combination LR-HSQMBC and 1,-n-ADEQUATE.

It should be expected that the application of the described com-bination of 2D-NMR experiments within CASE systems would allowthe problem of “silent fragments” to be overcome to a consider-able degree. The methodology of the approach described should befurther developed on the basis of structure elucidation of other mol-ecules subjected to the Crews rule.

Kummerlöwe et al. [47] concluded that 2D-NMR data, includ-ing 1H -15N HMBC and 1,1-ADEQUATE, were insufficient to elucidatethe structure of an unusual proton-deficient molecule (3) manu-ally, due to extremely contradictory 1H-13C HMBC data (presenceof nine NSCs, two of which had five bond lengths and were ratherstrong).

Kummerlöwe et al. [47] were the first to utilize successfully theNMR spectrum of a residual dipolar coupling (RDC) [48] to eluci-date the structure of a small molecule.

Zangger and Sterk [49] developed a “pure shift” approach, pro-viding 1H-decoupled proton spectra (i.e., all multiplets are transformedinto singlets). In recent years, efforts of researchers were directedto overcome the major drawback of the approach – its low sensitivity[50–58]. As a result, very recently, a new and very general pure shiftmethod, Pure Shift Yielded by CHirp Excitation (PSYCHE), was in-troduced by Morris and co-workers [56]. PSYCHE has approximately10-fold better sensitivity than competing “pure shift” methods.Normal and PSYCHE spectra of estradiol in DMSO-d6 are shown inFig. 2as an example.

The same group applied PSYCHE to the TOCSY experiment [57].In combination with covariance processing (see below), the resultis a high-quality, high-resolution TOCSY spectrum with singlets inboth dimensions (see Fig. 3). It is evident that the suggested ap-proach dramatically facilitates interpretation of 1D- and 2D-NMRspectrum and will significantly simplify spectroscopic data inputinto CASE programs.

Analytical applications of the ultra-fast (UF) 2D-NMR tech-nique were extensively discussed in a review [21]. This techniqueacquires a 2D spectrum in a few seconds, but it suffers from lowsensitivity. For example, to use a single-scan HSQC spectra for re-action monitoring, a 0.44 M solution was necessary [59]. Anotherpossibility to accelerate acquiring a spectrum appeared when NMRspectrometers equipped with two or more independent receiversbecame available, which allowed different types of 2D spectra tobe obtained simultaneously [60]. For example, the parallel-acquisitionNMR all-in-one combination of experimental applications (PANACEA)

Structure 2. Proton-deficient model compound cervinomycin A2.

Structure 3. An unusual proton-deficient molecule.

Fig. 1. Long-range heteronuclear single quantum multiple bond correlations (LR-HSQMBCs) observed for cervinomycin A2. Note that numerous long-range correlationsreach carbon atoms of the “silent fragment” [27].

Table 3Results obtained for cervinomycin A2 (2) with various 2D NMR aspects used as input.Data that were provided as program input are denoted by (+), nJCH for which ex-periments were optimized (in Hz), gt – time of structure generation, and k – numberof generated structures

COSY, HSQC 1H-13CHMBC

1H-13CLR-HSQMBC

gt k

8 Hz 4 Hz 4 Hz 2 Hz

+ + + 49 h 314+ + + + 37 h 4+ + + + 2 m 30 s 7+ + + + + 1m 44 s 1

Fig. 2. Spectra of estradiol obtained by (a) normal proton nuclear magnetic reso-nance (1H-NMR) spectroscopy and (b) Pure Shift Yielded by CHirp Excitation (PSYCHE)[56].

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[61] technique can in principle obtain all data [including indirectADEQUATE (INADEQUATE)] needed for small molecule structure elu-cidation in a single experiment, but low sensitivity prevents its wideapplication. More sensitive timeshared (TS) versions of 2D-NMR ex-periments (TS-HMBC, TS-HSQC, TS-HSQC-TOCSY, and TS-HSQMBC)were suggested by Parella and Nollis [62] who demonstrated uti-lization of this approach for simultaneous acquisition of 1H/13C and1H/15N-NMR spectra.

New methods for 2D-NMR data processing, which facilitate spec-trum interpretation, were developed and reviewed [8]. Covarianceprocessing involves reprocessing 2D data sets, singly or in pairs, toimprove resolution or to present the existing information in a dif-ferent, clearer fashion. Unsymmetric Covariance Processing (UCP),developed by Martin and co-workers [63], and the closely-relatedGeneralized Covariance Processing (GCP), suggested by Snyder andBruschweiler [64], are the most useful. These methods allow one

Fig. 3. Spectra of (a) normal Total Correlation Spectroscopy (TOCSY), (b) F1-Pure Shift Yielded by CHirp Excitation (PSYCHE)-TOCSY, and (c) double pure shift TOCSY usingPSYCHE in F1 and covariance processing in F2 of a sample of estradiol in DMSO-d6 [57].

92 M. Elyashberg/Trends in Analytical Chemistry 69 (2015) 88–97

to combine data from two kinds of 2D spectra that have a commonaxis (usually 1H). The resultant spectrum does not include any newinformation that was not present in the two original 2D spectra. Nev-ertheless, the data are presented in a clearer manner, which is easierto interpret {see review [65]}. The software for covariance process-ing is available from Bruker, ACD Labs and Mestranova.

4. CASE expert systems

CASE expert systems mimic the reasoning of a hum-an expert during the process of structure elucidation. Thefollowing main advantages of CASE systems should be noted[1]:

1) all statements about interrelation between a spectrum anda structure (“axioms”) are expressed explicitly;

2) all logical consequences (structures) following from the systemof “axioms” are deduced completely, without any exclusions;

3) if the initial data are complete and consistent, the process ofcomputer-based structure elucidation is usually fast, signifi-cantly saving time and labor of the scientist; and,

4) if the chemist has several sets of axioms related to a givenstructural problem, an expert system allows rapid genera-tion of all consequences from each of the sets and identifiesthe most probable structure by comparing the solutionsobtained.

The state of the art in this area was extensively reviewed[1,5,66,67]. The contemporary CASE programs include SESAMI [68],LSD [69], COCON [70], ACD/Structure Elucidator [1,2], and BrukerCMC-se, which are based on 2D-NMR, and CAST\CNMR StructureElucidator [71], based on 13C spectra.

ACD\Structure Elucidator (StrucEluc) [1,2,44,72] is the most ad-vanced expert system. The 1D- and 2D-NMR spectra can be importedto the program from a spectrometer or input manually from a tableprepared by the user. The imported data must be thoroughly checkedand edited by the spectroscopist. The strategy of the system restsupon a series of databases containing factual and axiomatic knowl-edge. All axioms are explicitly presented on the Molecular ConnectivityDiagram (MCD) for visual analysis (e.g., Fig. 4).

This easily allows users to investigate the dependence of thestructural problem solution on any change in the initial set of axioms.The system is capable of inferring all plausible structures from a com-bination of a molecular formula and 1D- and 2D-NMR data (e.g.,HSQC, HMBC, and COSY), even in those cases when the spectrum-structural information is very fuzzy, incomplete and contradictory.Selection of the most probable structure is performed on the basisof the 13C chemical-shift prediction using three algorithms imple-mented into the system – HOSE code based [73], neural networksand additivity rules [1,5]. The program is capable of elucidating astructure of an unknown in the presence of an unknown numberof non-standard correlations of unknown length. The software iscommercially available and was used for solving many complex an-alytical problems. For example, with its aid, the structure of complexalkaloid quindolinocryptotackieine was determined [74] in an in-teractive mode, allowing for step-by-step resolution of manyambiguous correlations, which took a spectroscopist a week of work.It was the first time that the program solved the structure that hadbeen unsolvable by experienced spectroscopists. Structure 3 (seeSection 3) declared as manually unsolvable from the full set of 2D-NMR data was unambiguously elucidated by StrucEluc in a fractionof a second [75]. The software was recently applied for structureelucidation of armeniaspirols A–C [76] . Fig. 5illustrates a typicalrepresentation of the most probable structures suggested by theprogram.

System performance can be illustrated by the following example:with its assistance, 1500 unknown molecules were elucidated bytwo spectroscopists in 6 months [77]. More than 50 examples ofstructure elucidation for natural products with unprecedented orunique skeletons were described [2].

Significant improvements [78] were introduced in the LSDprogram [69], which is now capable of treating 2D-NMR data con-taining NSCs, and selection of the most probable structure isperformed by NMR spectrum prediction. LSD is the first version ofCASE program freely available from the Internet [79].

The SESAMI system [68] was combined with a 13C-NMR inter-pretive library-search system (INFERCNMR) [80], capable of searchingsubstructures in a database containing assigned 13C-NMR spectra.The search resulted in a set of substructures predicted to be presentin the unknown, each of which is assigned an estimated predic-tion accuracy. Involving the best substructures in the structure-generation procedure allows a significant reduction in the generationtime and the size of the output file. The suggested approach is prom-ising for the further development of CASE methodology, as it doesnot require application of the fragment database incorporated intothe program.

As for the Bruker CMC-se program, the absence of any publica-tions utilizing the program does not allow a comparative evaluationto be made.

New expert system CAST/CNMR Structure Elucidator is based on13C-NMR and a database containing structures with chemical-shift assignment [71]. A series of advanced graph-theory algorithms

Fig. 4. The molecular connectivity diagram created from 1H, 13C, heteronuclear single-quantum correlation (HSQC), heteronuclear multi-bond correlation (HMBC) andcorrelation spectroscopy (COSY) spectra of gymnopalyne (upper segment of the figure).Atom properties are adjusted to the structure of gymnopalyne to illustrate differ-ent conventional signs: atom hybridization (sp3 – blue, sp2 – violet, sp – green, notsp – light blue, not defined – black), connectivities (COSY – blue, HMBC – green),and labels (ob – obligatory neighbor heteroatom, fb – forbidden neighbor heteroa-tom). Information about 1H chemical shifts can also be visualized [2].

93M. Elyashberg/Trends in Analytical Chemistry 69 (2015) 88–97

are used for selecting appropriate substructures, then the most prob-able structures are formed by merging the substructures that havecommon parts. The program produces a correct structure if all thefragments are included in the database. As only one exampleillustrates the suggested approach, no conclusions regarding its ef-ficacy can be made.

It should be noted that the first open source structure genera-tor, OMG [81], recently became available. It can be used for solvingstructural problems as a stand-alone program and as a block of aCASE system. The CASE program COCON is also freely accessible fromthe WEBCOCON server [70].

As discussed in Section 3, utilization of new 2D-NMR experi-ments within the CASE systems leads to rapid structure elucidationof complex proton-deficient molecules.

5. NMR chemical-shift prediction

As mentioned above, NMR chemical-shift prediction plays an in-valuable role in the estimation of suggested structures [1,2,5].Chemical shifts of 13C, 1H, 15N, 19F and 31P nuclei can be calculatedusing empirical and quantum-mechanical (QM) methods. NMR spec-trum predictors based on HOSE codes [73], neural nets, and anincremental approach are used most frequently and were re-viewed [1,5]. The predictors can be incorporated in expert systems(as described for ACD/Structure Elucidator and LSD) or used sep-arately as commercial programs [82–85] or free [86]. The programsprovide an accuracy of 13C chemical-shift prediction about1.5–1.8 ppm, which almost always allows for selecting the most prob-able structure(s) among candidates. The prediction is very fast. Forexample, the incremental program incorporated into ACD/StructureElucidator calculates ~10, 000 shifts per second on a standard PC.

A new program, NMRscape [87] for 13C chemical-shift calcula-tion based on new principles {OptiChem theory [88]} was recentlydeveloped and tested on several families of structures. The resultsseem rather promising, as the accuracy provided by this approachis expected to be higher than that inherent to existing empiricalmethods.

A common drawback of all empirical methods is that predic-tion accuracy depends on the composition of the databases usedfor program training. In contrast, the DFT GIAO quantum-chemicalmethod does not suffer from this limitation, but it is very time-consuming and there is the problem of selecting appropriatefunctional and basic sets for calculations {see reviews [89,90]}. Thefollowing optimal strategy of jointly utilizing empirical and QMmethods for structure elucidation was suggested [91]: all candidate

structures must be ranked first by empirical 13C spectrum predic-tion, and, if the average deviations between the experimental andpredicted spectra calculated for two to three top-ranked struc-tures are large or very close, only then should QM predictions beperformed for those questionable structures. The possibility wasdemonstrated of successful application of JHH, JHC, and JCC coupling-constant calculations by QM methods for distinguishing isomershaving very similar structures [92].

6. Structure verification

Structure verification based on 13C chemical-shift predictionallows selection of the correct structure among thousands of plau-sible hypotheses produced by expert systems [1,2]. For verificationof structures suggested for large sets of synthesized molecules, 1Hchemical-shift prediction is frequently used due to the possibilityof quickly acquiring a spectrum with a small sample size. Protonchemical-shift dependence on, e.g., solvent, temperature, and pH,limits the utility of this approach. Utilization of PSYCHE 1H-NMRcoupled with pure shift ME-HSQC acquired using the 1.7-mmMicroCryoProbe would make the approach more robust.

Verification and identification of organic molecules from a struc-ture database using both 1H and 13C-NMR spectra were reported [93].Keyes et al. [93] examined a method of structure validation usinga set of 500 compounds supplied with 1H, HSQC, LC-MS and HPLCdata. 1H and HSQC spectra were predicted using the ACD/NMR Pre-dictor [82] and compared with experimental spectra. It wasconcluded that the approach was very practical for application ina pharmaceutical company. As current implementations of auto-mated structure-verification systems allow false-positive results, anapproach based on 1H and HSQC spectra was suggested [94] thatgreatly reduces the probability of an automated validation systempassing incorrect structures (i.e., false positives). The novel methodwas examined by automatic validation of 127 compounds, whichshowed a reduction in the false-positive rate from 20% to 5%.Plainchont and Nuzillard [95] proposed to verify a molecular struc-ture using a combination of 1D and 2D HSQC, COSY and HMBC-NMR spectra. This approach is not suitable for rapid structureverification, but it rather fits analysis of doubtful structures passedfor verification.

7. Structure identification and dereplication in mixtures

Dereplication of organic compounds (identification in a mixture)is a challenging problem for NMR spectroscopy [96]. If the sample

Fig. 5. The three top-ranked structures according to the dA deviation. dA(13C), dI(13C) and dN(13C) – average deviations calculated by Hierarchical Organization of SphericalEnvironments (HOSE) code-based algorithm, incremental approach and neural networks correspondingly. The correct structure #1 (armeniaspirol B) is reliably selected asthe most probable [76] in accordance with the criteria suggested [1].

94 M. Elyashberg/Trends in Analytical Chemistry 69 (2015) 88–97

amount is enough for separation of individual components, they canbe determined by a spectral search against an NMR database [97],or structures of unknowns are elucidated using MS and a commonset of 1D- and 2D-NMR spectra. For example, Thummala et al. [98]isolated an unknown impurity of ambroxol using preparative HPLCand established its structure by combined application of 2D-NMR,FTIR and LC-MS/MS.

Codina et al. [99] isolated five impurities from a pharmaceuti-cal matrix (samples of 20–40 μg) and identified them from MS and2D-NMR spectra with the aid of the ACD/Structure Elucidator. Aneffective dereplication strategy for identification of natural me-tabolites directly within mixtures was suggested [100,101]. Amultigram quantity of a crude extract was rapidly fractionated bycentrifugal partition extraction (CPE). The fractions of simplifiedchemical composition were subsequently analyzed by 13C-NMR, andhierarchical clustering analysis (HCA) suggested by the authors forpattern recognition. A locally-built 13C-NMR chemical-shift data-base was used for identification. This methodology resulted in thedirect identification (without time-consuming isolation proce-dures) of seven major compounds of a bark extract [100] and sixout of eight prominent constituents of the crude extract of lichen[101].

Pauli and co-workers [11] comprehensively investigated the pre-cision necessary for measuring spectral parameters of 1H-NMRspectra for their tabulation to be used for structure dereplicationand identification. It was shown that δ and J values of 1H-NMR shouldbe routinely reported with Δδ = 0.1–1 ppb and ΔJ = 10 mHz preci-sion, respectively.

As a manual 1H spectrum assignment is a time consuming,tedious and error-prone procedure, an expert system for the auto-matic atom-to-peak or multiplet assignment of 1H-NMR spectra ofsmall molecules has been developed [102]. It was found with thetest set of 90 compounds that 94% of assignments were correct, soconfirming the efficiency of the program.

Different NMR experimental approaches were developed for qual-itative analysis of mixtures without any preliminary fractionationor separation. The NMR diffusion-ordered spectroscopy (DOSY) ex-periment is based on molecules of different sizes and shapesfrequently having different diffusion coefficients [8]. DOSY is verypowerful for studying complex mixtures, but its applicability is stilllimited, particularly when dynamic or unstable systems are studied.A UF version of DOSY was recently described as overcoming thisdrawback [21]. Morris and co-workers [58] developed a pure shiftDOSY experiment, which greatly extended the range of applicabil-ity of DOSY. Simplified (pure shift) PSYCHE 1H-NMR [56] spectra (seeFig. 2) are obviously very promising for analyzing complex mix-tures by 1H-NMR. A method of mixture analysis based on 13C-NMR [100,101] can probably be extended to PSYCHE 1H-NMR spectraof mixtures.

Although the sensitivity of NMR is significantly lower than MS,LC-NMR is now available as a coupled method for mixture analy-sis [8,103–105]. Only 1H spectra can usually be obtained incontinuous flow mode. The low sensitivity of the approach pre-vents its wide application. However, very recently, Foley and co-workers [106,107] described application of on-line reactionmonitoring using continuous flow NMR. A standard 5 mm NMRprobe enables the researcher to conduct experiments on flowingreaction mixtures using a range of spectrometers of varying mag-netic field strengths [107]. It was reported [59] that UF COSY spectrawere utilized for reaction monitoring using a commercial HPLC-NMR set-up.

A combination of LC with solid-phase extraction (SPE) car-tridges led to the possibility of obtaining MS and NMR spectra ofcomponents from a single experiment [108]. After LC separation,the sample was split, and a small portion sent for MS analysis, whilethe remainder was directed to SPE cartridges for collection.

Application of a cryogenically-cooled probe reduced the time andthe sample amount necessary for structure identification (elucida-tion) [8].

8. Is it possible to avoid an erroneous structure elucidation?

As spectroscopic structure elucidation is a complex logical-combinatorial process, it is not surprising that different scientistsmay come to different structures from the same initial data. A seriesof reviews [13,109–112] discussed many structural misassignments.The following most typical reasons of obtaining erroneous struc-tures can be noted:

a) severe resonance overlap in NMR spectra;b) erroneous user suggestions (”axioms”);c) mistaken logical conclusions inferred from the presence or

the absence of characteristic spectral features in 1D-NMR and2D-NMR spectra;

d) complexity, inconsistency and entanglement of initial infor-mation {see [75]}.

Expert system-based analysis of many cases, when erroneousstructures were inferred, shows [1,13,75,113] that application of CASEallows the determination of the correct structure and causes of thehuman error to be detected. Figuratively speaking, a CASE systemcan be used as a “polygraph detector”. To avoid upsetting errors, itis recommended to predict 13C-NMR and 1H-NMR chemical shiftsfor any structural hypothesis in the process of chemical research.

9. Conclusions

Contemporary NMR spectroscopy is the most powerful routineanalytical tool for molecular structure elucidation and identifica-tion, given that the molecular formula is determined using HRMSand all available spectroscopic data. 2D-NMR plays a crucial role inestablishing structures of new organic molecules, and, to date, aplethora of different kinds of 2D-NMR experiments has been elabo-rated. These methods are extensively developed to provide thepossibility of acquiring as much as possible structural informationfrom a minimum amount of sample (<10 μg [41]) in the shortestinstrument time. NMR is successfully used for structure dereplicationand analysis of mixtures, including usage of LC-NMR. Many studieshave shown that CASE is a powerful amplifier of human intelli-gence. It should be expected that application of pure shift spectraas input to artificial intelligence programs developed ad hoc for dataimport to CASE systems will automate this procedure signifi-cantly, so facilitating and accelerating the stage of data preparation.

The author believes that, in the near future, CASE will becomea routine analytical tool, which will serve as an integral part of anyNMR spectrometer similar to the software used in X-raycrystallography.

Acknowledgements

The author thanks Gary Martin for constructive comments andpieces of valuable advice.

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