Concurrent combined verification: reducing false positives in automated NMR structure verification through the evaluation of multiple challenge control structures

Automated structure verification using ¹H NMR data or a combination of ¹H and heteronuclear single‐quantum correlation (HSQC) data is gaining more interest as a routine application for qualitative evaluation of large compound libraries produced by synthetic chemistry. The goal of this automated software method is to identify a manageable subset of compounds and data that require human review. In practice, the automated method will flag structure and data combinations that exhibit some inconsistency (i.e. strange chemical shifts, conflicts in multiplicity, or overestimated and underestimated integration values) and validate those that appear consistent. One drawback of this approach is that no automated system can guarantee that all passing structures are indeed correct structures. The major reason for this is that approaches using only ¹H or even ¹H and HSQC spectra often do not provide sufficient information to properly distinguish between similar structures. Therefore, current implementations of automated structure verification systems allow, in principle, false positive results. Presented in this work is a method that greatly reduces the probability of an automated validation system passing incorrect structures (i.e. false positives). This novel method was applied to automatically validate 127 non‐proprietary compounds from several commercial sources. Presented also is the impact of this approach on false positive and false negative results. Copyright © 2012 John Wiley & Sons, Ltd.     

Xylocarpins A and B, two new mexicanolides from the seeds of a Chinese mangrove Xylocarpus granatum: NMR investigation in mixture

Xylocarpins A and B, two new mexicanolides with a tiglate group at C-3, have been identified in the mixture using NMR spectroscopy. Both compounds were isolated in the mixture from the seeds of a Chinese mangrove Xylocarpus granatum. The first complete assignments of 1H and 13C NMR data for these mexicanolides were achieved by means of 2D NMR techniques, including 1H-1H COSY, HSQC, HMBC and NOESY spectra. In order to separate xylocarpins A (1) and B (2) by chemical method, the mixture of two compounds was reduced with sodium borohydride in anhydrous methanol. However, the reduction led to the opening of the delta-lactone ring in xylocarpin B and afforded compound 3 as the main product. The complete NMR assignments of compound 3 were also achieved by means of the above 2D NMR techniques. Moreover, xylocarpin A was easily transformed into xylocarpin B during our normal liquid column chromatography. From this point of view, xylocarpin A was deemed to be the genuine natural product and xylocarpin B might be an artifact.     

The development of an NMR chemical shift prediction application with the accuracy necessary to grade proton NMR spectra for identity

We have developed an NMR chemical shift prediction system that enables high throughput automatic grading of NMR spectra. In support of high throughput synthetic efforts for our drug discovery program, a rapid and accurate analysis for identity was needed. The system was designed and implemented to take advantage of the NMR assignments that had been tabulated on internally generated research compounds. The system has been operational for four years and has been used in conjunction with an internally written grading program to successfully analyze several hundred thousand samples based only on their 1D ¹H spectrum. A focused test of the system's accuracy on 1006 molecules demonstrated the ability to estimate the proton chemical shift with an average error of +/?0.16 ppm. This level of chemical shift accuracy allows for reliable structure confirmation by automated analysis using only proton NMR. Copyright © 2009 John Wiley & Sons, Ltd.     

1H and 13C NMR assignments of three nitrogen containing compounds from the mangrove endophytic fungus (ZZF08)

A new natural product, named phomopsin A, 1-(meta-hydroxyphenyl)-4-hydroxy-3-isoquinolone (1), together with two known compounds cytochalasin H (2) and glucosylceramide (3), was isolated from the mangrove endophytic fungus Phomopsis sp. (ZZF08) obtained from the South China Sea coast. The structures were elucidated by 1D and 2D NMR experiments including COSY, HMQC, and HMBC. According to NMR and single-crystal X-ray diffraction, it was found that some assignments about (1)H and (13)C NMR data for cytochalasin H (2) were probably uncorrected in the previous reports. In our cytotoxicity assays, compound 1 showed moderate cytotoxicity toward KB cells with IC(50) at 28.0 microg ml(-1) and KBv200 cells with IC(50) at 16.8 microg ml(-1), and compound 2 exhibited strong cytotoxicity toward KB cells and KBv200 cells with IC(50) less than 1.25 microg ml(-1).     

Targeting norovirus infection-multivalent entry inhibitor design based on NMR experiments

Noroviruses attach to their host cells through histo blood group antigens (HBGAs), and compounds that interfere with this interaction are likely to be of therapeutic or diagnostic interest. It is shown that NMR binding studies can simultaneously identify and differentiate the site for binding HBGA ligands and complementary ligands from a large compound library, thereby facilitating the design of potent heterobifunctional ligands. Saturation transfer difference (STD) NMR experiments, spin-lock filtered NMR experiments, and interligand NOE (ILOE) experiments in the presence of virus-like particles (VLPs), identified compounds that bind to the HBGA binding site of human norovirus. Based on these data two multivalent prototype entry-inhibitors against norovirus infection were synthesized. A surface plasmon resonance based inhibition assay showed avidity gains of 1000 and one million fold over a millimolar univalent ligand. This suggests that further rational design of multivalent inhibitors based on our strategy will identify potent entry-inhibitors against norovirus infections.     

A robust,general automatic phase correction algorithm for high‐resolution NMR data

The trends towards rapid NMR data acquisition, automated NMR spectrum analysis, and data processing and analysis by more naïve users combine to place a higher burden on data processing software to automatically process these data. Downstream data analysis is compromised by poor processing, and the automated processing algorithms must therefore be robust and accurate. We describe a new algorithm for automatic phase correction of frequency‐domain, high‐resolution NMR spectra. We show this to be reliable for data derived from a wide variety of typical NMR usages. We therefore conclude that the method will have wide‐spread applicability and a positive impact on automated spectral processing and analysis. Copyright © 2017 John Wiley & Sons, Ltd.     

1H and 13C NMR characterization of new cycloartane triterpenes from Mangifera indica

From the stem bark of Mangifera indica, seven cycloartane‐type secondary metabolites were isolated. Compound 1 has been isolated for the first time from M. indica, whereas compounds 2 (2a and 2b, as an epimeric mixture), 3, and 4 are new triterpenoid‐type cycloartanes. Unambiguous ¹³C and ¹H NMR assignments for these compounds and the known compounds mangiferonic acid (compound 5), isomangiferolic acid (compound 6), ambolic acid (compound 7), and friedelin (compound 8) are reported; the latter because full NMR data for these compounds are not available in the literature. Copyright © 2012 John Wiley & Sons, Ltd.     

NMR spectroscopy goes mobile: Using NMR as process analytical technology at the fume hood

Nuclear magnetic resonance (NMR) is potentially a very powerful process analytical technology (PAT) tool as it gives an atomic resolution picture of the reaction mixture without the need for chromatography. NMR is well suited for interrogating transient intermediates, providing kinetic information via NMR active nuclei, and most importantly provides universally quantitative information for all species in solution. This contrasts with commonly used PAT instruments, such as Raman or Flow-infrared (IR), which requires a separate calibration curve for every component of the reaction mixture. To date, the large footprint of high-field (≥400 MHz) NMR spectrometers and the immobility of superconducting magnets, coupled with strict requirements for the architecture for the room it is to be installed, have been a major obstacle to using this technology right next to fume hoods where chemists perform synthetic work. Here, we describe the use of a small, lightweight 60 MHz Benchtop NMR system (Nanalysis Pro-60) located on a mobile platform, that was used to monitor both small and intermediate scale Grignard formation and coupling reactions. We also show how low field NMR can provide a deceptively simple yes/no answer (for a system that would otherwise require laborious off-line testing) in the enrichment of one component versus another in a kilogram scale distillation. Benchtop NMR was also used to derive molecule specific information from Flow-IR, a technology found in most manufacturing sites, and compare the ease at which the concentrations of the reaction mixtures can be derived by NMR versus IR.     

Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures

Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.     

1H and 13C NMR spectral assignments of 2′‐hydroxychalcones

Chalcones are of interest to medicinal chemists because their structures can be easily modified with various functional groups. The syntheses and biological activities of chalcones from natural sources are well known. In this study, 24 2′‐hydroxychalcones bearing methoxy substituents were synthesized, among which five are new. The NMR data for all synthesized chalcones are described for the first time. The complete assignments of the ¹H and ¹³C NMR data can be used for the identification of newly discovered and widely isolated, synthesized chalcones. Copyright © 2013 John Wiley & Sons, Ltd.     

Direct-injection NMR (DI-NMR): a flow NMR technique for the analysis of combinatorial chemistry libraries

A new tool for analyzing compound libraries by NMR has been developed. Aliquots of solution-state samples (between 120 and 350 microL) are directly injected, using a standard liquids handler, into an NMR (LC-NMR) flow probe. Automated NMR software tracks--and suppresses--intense signals arising from the nondeuterated solvents used (if any) and acquires high-sensitivity one-dimensional 1H NMR spectra. An 88-member combinatorial library, dissolved in DMSO and stored in a 96-well microtiter plate, has been analyzed a number of ways using this technique. This nondestructive technique, which we call direct-injection NMR (DI-NMR) and which is embodied in our versatile automated sample changer (VAST) hardware, has proven to be both routine and robust. Our success in automatically acquiring the NMR data for entire plates of library compounds (within 4-8 h) has caused us to develop new ways to display and analyze the resulting NMR data, as will be shown here.     

Rapid screening of binding constants by calibrated competitive 1H NMR spectroscopy

A calibrated competitive NMR method has been developed that is appropriate for the rapid screening of binding constants. This method involves the initial characterisation of a receptor-substrate binding event for which the (1)H NMR spectrum of a given receptor (calibrant) is modified by the substrate of interest at a range of concentrations. For all subsequent "unknown" receptors, K(a) values are then determined by using a competition assay (in the presence of the calibrant receptor) by measuring a single standard (1)H NMR spectrum. This enables a rapid assessment of the recognition properties of a library of potential receptors. Only the calibrant receptor needs to be NMR active, while the library of putative receptors, as well as the substrate, can be NMR silent. This method assumes the formation of complexes of 1:1 stoichiometry. To demonstrate this methodology, the binding of a number of crown ether type compounds with K+ ions has been studied. Comparison of the binding strengths obtained by using this approach with those in the literature shows excellent agreement. A range of new compounds that have recently been synthesised within our group has also been screened in order to illustrate how this approach can rapidly assess binding ability. This method has significance for chemists working in the fields of combinatorial receptor/substrate design and supramolecular chemistry as a means of rapid optimisation of binding strength.     

ACD/Structure Elucidator: 20 Years in the History of Development

The first methods associated with the Computer-Assisted Structure Elucidation (CASE) of small molecules were published over fifty years ago when spectroscopy and computer science were both in their infancy. The incredible leaps in both areas of technology could not have been envisaged at that time, but both have enabled CASE expert systems to achieve performance levels that in their present state can outperform many scientists in terms of speed to solution. The computer-assisted analysis of enormous matrices of data exemplified 1D and 2D high-resolution NMR spectroscopy datasets can easily solve what just a few years ago would have been deemed to be complex structures. While not a panacea, the application of such tools can provide support to even the most skilled spectroscopist. By this point the structures of a great number of molecular skeletons, including hundreds of complex natural products, have been elucidated using such programs. At this juncture, the expert system ACD/Structure Elucidator is likely the most advanced CASE system available and, being a commercial software product, is installed and used in many organizations. This article will provide an overview of the research and development required to pursue the lofty goals set almost two decades ago to facilitate highly automated approaches to solving complex structures from analytical spectroscopy data, using NMR as the primary data-type.     

Synthesis and NMR elucidation of novel penta-cycloundecane amine derivatives as potential antituberculosis agents

The synthesis and NMR elucidation of five novel penta-cycloundecane amine derivatives are reported. These compounds are potential antituberculosis agents. The (1)H and (13)C spectra showed major overlapping of methine signals of the cage skeleton making it extremely difficult to elucidate these compounds. The overlapping occurs as a result of the additions made to the carbonyl carbon (C-8/C-11) of the cage. The two-dimensional NMR technique proved to be a useful tool in overcoming this problem. All compounds reported are meso compounds thereby not only simplifying the NMR structure elucidation, but also making it indeed possible.     

Spectral deep learning for prediction and prospective validation of functional groups

State-of-the-art identification of the functional groups present in an unknown chemical entity requires the expertise of a skilled spectroscopist to analyse and interpret Fourier transform infra-red (FTIR), mass spectroscopy (MS) and/or nuclear magnetic resonance (NMR) data. This process can be time-consuming and error-prone, especially for complex chemical entities that are poorly characterised in the literature, or inefficient to use with synthetic robots producing molecules at an accelerated rate. Herein, we introduce a fast, multi-label deep neural network for accurately identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra. We do not use any database, pre-established rules, procedures, or peak-matching methods. Our trained neural network reveals patterns typically used by human chemists to identify standard groups. Finally, we experimentally validated our neural network, trained on single compounds, to predict functional groups in compound mixtures. Our methodology showcases practical utility for future use in autonomous analytical detection.

A new multi-label deep neural network architecture is used to combine Infrared and mass spectra, trained on single compounds to predict functional groups, and experimentally validated on complex mixtures.     

Synthesis and characterisation of medium-sized ring systems by oxidative cleavage. Part 2: Insights from the study of ring expanded analogues

Variable temperature NMR analysis and computational methods have been used to develop a detailed understanding of the ¹H NMR spectra of a family of medium-sized ring containing compounds. The family consists of analogues containing 10-, 11- and 12-membered rings and in all cases the NMR spectra at room temperature showed a series of diastereotopic methylene signals despite the lack of a stereogenic centre in these systems. On repeating the NMR analysis at higher temperatures, all the signals coalesced for the 12-membered ring system consistent with full interconversion of ring conformers. This was not observed in the analogous 10- and 11-membered ring systems with the interchange of conformers remaining slow on the NMR timescale. However, 1D gs-NOESY/EXSY NMR experiments showed that in the smaller ring systems interconversion of diastereotopic protons did occur. Computational studies suggest that the dynamic process observed by NMR for the 10- and 11-membered rings systems is different from that observed in the 12-membered ring containing compound.     

Development of a method for evaluating drug-likeness and ease of synthesis using a data set in which compounds are assigned scores based on chemists' intuition

The concept of drug-likeness, an important characteristic for any compound in a screening library, is nevertheless difficult to pin down. Based on our belief that this concept is implicit within the collective experience of working chemists, we devised a data set to capture an intuitive human understanding of both this characteristic and ease of synthesis, a second key characteristic. Five chemists assigned a pair of scores to each of 3980 diverse compounds, with the component scores of each pair corresponding to drug-likeness and ease of synthesis, respectively. Using this data set, we devised binary classifiers with an artificial neural network and a support vector machine. These models were found to efficiently eliminate compounds that are not drug-like and/or hard-to-synthesize derivatives, demonstrating the suitability of these models for use as compound acquisition filters.     

Quantitative data on the effects of alkyl substituents and Li-O and Li-N chelation on the stability of secondary alpha-oxy-organolithium compounds

A DeltaG(eq) stability scale of secondary alpha-oxy-organolithium compounds was established from measurements of tin-lithium exchange equilibria in THF, and the quantitative effects of substituents at the anionic center on carbanion stability are presented. A new lead-lithium exchange equilibrium reaction was also investigated and shown to be a very useful alternative for the determination of the relative stability of the more sterically hindered organolithium compounds. Alkyl groups adversely affect the stability of organolithium compounds when attached to the carbon bearing the negative charge, but the extent of this effect is highly dependent on the nature of the rest of the substituents attached to the anionic center. Quantitative data on the stabilization imparted to organolithium compounds by Li-O and Li-N chelation have been determined for a variety of systems. The formation of four- and five-membered chelate rings leads to a considerable stabilization of the organolithium compound, while chelation through the formation of six-membered rings affords no extra stabilization to this type of organometallics. Multinuclear NMR experiments carried out on several alpha-oxy-organolithium compounds to determine their aggregation state are supportive of these species being monomers in THF solution.     

Solution- and bound-state conformational study of N,N',N"-triacetyl chitotriose and other analogous potential inhibitors of hevamine: application of trNOESY and STD NMR spectroscopy

The solution-state conformations of N,N',N"-triacetyl chitotriose (1) and other potential chitinase inhibitors 2-4 were studied using a combination of NMR spectroscopy (NOESY) and molecular mechanics calculations. Determination solely of the global energy minimum conformation was found to be insufficient for an agreement with the NMR results. An appropriate consistency between the NMR experimental data and theoretical calculations was only reached by assessing the structures as population-weighted average conformers based on Boltzmann distributions derived from the calculated relative energies. Analogies, but also particular differences, between the synthetic compounds 2-4 and the naturally-occurring N,N',N"-triacetyl chitotriose were found. Furthermore, the conformation of compounds 1 and 2 when bound to hevamine was also studied using transferred NOESY experiments and the binding process was found to impart a level of conformational restriction on the ligands. The preferred conformation as determined for 1 in the bound state to hevamine belonged to one of the conformational families found for the compound when free in solution, although full characterisation of the bound-state conformations was impeded due to severe signal overlap. Saturation transfer difference NMR experiments were also employed to analyse the binding epitopes of the bound compounds. We thus determined that it is mainly the acetyl amido groups of the trisaccharide and the heterocyclic moiety which are in close contact with hevamine.     

Monitoring daily routine performance in quantitative NMR (qNMR) spectroscopy: Is the system suitability test necessary?

Nuclear magnetic resonance spectrometry (NMR) finds numerous applications in pharmacy, cosmetic, and food control as well as in developing tools for “big data” analysis. However, there remains a need for automated tools to assess instrument system suitability in real time for each particular routine sample. An automated procedure has been introduced to monitor a number of characteristics (resolution, symmetry, and half width) in real time after the measurement of two samples distributed by the vendor (0.3% CHCl₃ in acetone-d₆ with tetramethylsilane and 2 mM sucrose in H₂O-D₂O). The results over 11 months were discussed in terms of average values, standard deviations, and spectrometer variability. Moreover, multivariate statistical procedure was implemented to evaluate metrics generated from three NMR spectrometers. Performance of three NMR spectrometers (500 MHz with BBO Prodigy Cryoprobe, 500 MHz with BBFO^PLUS SmartProbe, and 600 MHz with BBO Cryoprobe) differed significantly. The developed routine was also applied to calculate the performance characteristics during routine quantitative NMR experiments. The procedure was evaluated for NMR spectra of 659 active pharmaceutical ingredients dissolved in CDCl₃, DMSO, and CH₃OD. This test is more preferable than the routine procedure using standard solutions because the performance is estimated separately for each matrix at the specific time point of measurements. Our automated routine is the ideal tool for any NMR laboratory. In full automation, the NMR data are validated directly for each sample, making unnecessary daily measurements of standard solutions and manual evaluation to their NMR spectra.