Crystal Structure and NMR of an α,δ-Peptide Foldamer Helix Shows Side-Chains are Well Placed for Bifunctional Catalysis: Application as a Minimalist Aldolase Mimic.

We report the first NMR and X-ray diffraction (XRD) structures of an unusual 13/11-helix (alternating i, i+1 {NH-O=C} and i, i+3 {C=O-H-N} H-bonds) formed by a heteromeric 1 : 1 sequence of α- and δ-amino acids, and demonstrate the application of this framework towards catalysis. Whilst intramolecular hydrogen bonds (IMHBs) are the clear driver of helix formation in this system, we also observe an apolar interaction between the ethyl residue of one δ-amino acid and the cyclohexyl group of the next δ-residue in the sequence that seems to stabilize one type of helix over another. To the best of our knowledge this type of additional stabilization leading to a specific helical preference has not been observed before. Critically, the helix type realized places the α-residue functionalities in positions proximal enough to engage in bifunctional catalysis as demonstrated in the application of our system as a minimalist aldolase mimic.

Conformationally Controlled sp3 -Hydrocarbon-Based α-Helix Mimetics.

With over 60 % of protein-protein interfaces featuring an α-helix, the use of α-helix mimetics as inhibitors of these interactions is a prevalent therapeutic strategy. However, methods to control the conformation of mimetics, thus enabling maximum efficacy, can be restrictive. Alternatively, conformation can be controlled through the introduction of destabilizing syn-pentane interactions. This tactic, which is often adopted by Nature, is not a common feature of lead optimization owing to the significant synthetic effort required. Through assembly-line synthesis with NMR and computational analysis, we have shown that alternating syn-anti configured contiguously substituted hydrocarbons, by avoiding syn-pentane interactions, adopt well-defined conformations that present functional groups in an arrangement that mimics the α-helix. The design of a p53 mimetic that binds to Mdm2 with moderate to good affinity, demonstrates the therapeutic promise of these scaffolds.

Crystal Structure and NMR of an α,δ-Peptide Foldamer Helix Shows Side-Chains are Well Placed for Bifunctional Catalysis: Application as a Minimalist Aldolase Mimic.

We report the first NMR and X-ray diffraction (XRD) structures of an unusual 13/11-helix (alternating i, i+1 {NH-O=C} and i, i+3 {C=O-H-N} H-bonds) formed by a heteromeric 1 : 1 sequence of α- and δ-amino acids, and demonstrate the application of this framework towards catalysis. Whilst intramolecular hydrogen bonds (IMHBs) are the clear driver of helix formation in this system, we also observe an apolar interaction between the ethyl residue of one δ-amino acid and the cyclohexyl group of the next δ-residue in the sequence that seems to stabilize one type of helix over another. To the best of our knowledge this type of additional stabilization leading to a specific helical preference has not been observed before. Critically, the helix type realized places the α-residue functionalities in positions proximal enough to engage in bifunctional catalysis as demonstrated in the application of our system as a minimalist aldolase mimic.

Accelerating quantitative 13C NMR spectra using an EXtended ACquisition Time (EXACT) method.

Accurate quantitative 13C NMR spectra can be accelerated by using EXACT (EXtended ACquisition Time) NMR methods which reduce Nuclear Overhauser Enhancement (NOE) during the FID. This allows 30-50% shorter experiment times to be used when achieving a given level of quantitative accuracy.

Monitoring off-resonance signals with SHARPER NMR - the MR-SHARPER experiment.

We demonstrate an extension to the SHARPER (Sensitive Homogenous and Refocussed Peaks in Real Time) NMR experiment which allows more than one signal to be monitored simultaneously, while still giving ultra-sharp, homo- and hetero-decoupled NMR signals. This is especially valuable in situations where magnetic field inhomogeneity would normally make NMR a problematic tool, for example when gas evolution is occurring during reaction monitoring. The originally reported SHARPER experiment only works for a single, on-resonance NMR signal, but here we demonstrate the Multiple Resonance SHARPER approach can be developed, which in principle can acquire multiple on-/off-resonance signals simultaneously while retaining the desirable properties of the parent sequence. In practice, the case of two resonances, e.g. those of a reactant and a product, will most of the time be considered for MR-SHARPER, as illustrated here.

Prediction of 15 N chemical shifts by machine learning.

We demonstrate the potential for machine learning systems to predict three-dimensional (3D)-relevant NMR properties beyond traditional 1 H- and 13 C-based data, with comparable accuracy to density functional theory (DFT) (but orders of magnitude faster). Predictions of DFT-calculated 15 N chemical shifts for 3D molecular structures can be achieved using a machine learning system-IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar information Of Nuclei), with an accuracy of 6.12-ppm mean absolute error (∼1% of the δ15 N chemical shift range) and an error of less than 20 ppm for 95% of the chemical shifts. It provides less accurate raw predictions of experimental chemical shifts, due to the limited size and chemical space diversity of the training dataset used in its creation, coupled with the limitations of the underlying DFT methodology in reproducing experiment.

Synthesis and pharmacological characterisation of arctigenin analogues as antagonists of AMPA and kainate receptors.

(-)-Arctigenin and a series of new analogues have been synthesised and then tested for their potential as AMPA and kainate receptor antagonists of human homomeric GluA1 and GluK2 receptors expressed in HEK293 cells using a Ca2+ influx assay. In general, these compounds showed antagonist activity at both receptors with greater activity evident at AMPARs. Schild analysis indicates that a spirocyclic analogue 6c acts as a non-competitive antagonist. Molecular docking studies in which 6c was docked into the X-ray crystal structure of the GluA2 tetramer suggest that (-)-arctigenin and its analogues bind in the transmembrane domain in a similar manner to the known AMPA receptor non-competitive antagonists GYKI53655 and the antiepileptic drug perampanel. The arctigenin derivatives described herein may serve as novel leads for the development of drugs for the treatment of epilepsy.

3× Axial vs 3× Equatorial: The ΔGGA Value Is a Robust Computational Measure of Substituent Steric Effects.

We define ΔGGA as the free energy change for the formal equilibrium: [13]G-H + 1-X-adamantane → [13]G-X + adamantane, where [13]G-H is the C13H22 fragment of all-trans graphane with 3-fold symmetry. This compares with a situation where the group X is equatorial to three cyclohexane rings with one where it is axial to three rings. ΔGGA values vary from 2.9 (CN) to 145.7 kJ mol-1 (CCl3), and this wide range means that ΔG can be calculated with confidence. ΔGGA values for Me, Et, i-Pr, and t-Bu form a regular series, 34.9, 63.3, 101.6, and 142.0, and clearly reflect the steric size of the groups. We propose a model where the six axial hydrogens surrounding X on [13]G-X provide a nearly circular constriction on the substituent close to its point of attachment but which does not extend far above this. We compare these results with A values and with calculations on 2- and 7-substituted [1(2,3)4]pentamantanes. We show that electronic effects on ΔGGA values are negligible but that they correlate well with computed cone and solid angles subtended by the substituent.

Conformationally Controlled Linear and Helical Hydrocarbons Bearing Extended Side Chains.

Conformationally controlled flexible molecules are ideal for applications in medicine and materials, where shape matters but an ability to adapt to multiple and changing environments is often required. The conformation of flexible hydrocarbon chains bearing contiguous methyl substituents is controlled through the avoidance of syn-pentane interactions: alternating syn-anti isomers adopt a linear conformation while all-syn isomers adopt a helical conformation. From a simple diamond lattice analysis, larger substituents, which would be required for most potential applications, result in significant and unavoidable syn-pentane interactions, suggesting substantially reduced conformational control. Through a combination of computation, synthesis, and NMR analysis, we have identified a selection of substitution patterns that allow large groups to be incorporated on conformationally controlled linear and helical hydrocarbon chains. Surprisingly, when the methyl substituents of alternating syn-anti hydrocarbons are replaced with acetoxyethyl groups, the main chain of almost 95% of the population of molecules adopt a linear conformation. Here, the side chains adopt nonideal eclipsed conformations with the main chain, thus minimizing syn-pentane interactions. In the case of all-syn hydrocarbons, concurrent removal of some methyl groups on the main chain adjacent to the large substituents is required to maintain a high population of molecules adopting a helical conformation. This information can now be used to design flexible hydrocarbon chains displaying functional groups in a defined relative orientation for multivalent binding or cooperative reactivity, for example, in targeting the interfaces defined by disease-relevant protein-protein interactions.

A community-powered search of machine learning strategy space to find NMR property prediction models.

The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in advance what strategy to adopt within a vast space of possibilities. Here we outline the results of an online community-powered effort to swarm search the space of ML strategies and develop algorithms for predicting atomic-pairwise nuclear magnetic resonance (NMR) properties in molecules. Using an open-source dataset, we worked with Kaggle to design and host a 3-month competition which received 47,800 ML model predictions from 2,700 teams in 84 countries. Within 3 weeks, the Kaggle community produced models with comparable accuracy to our best previously published 'in-house' efforts. A meta-ensemble model constructed as a linear combination of the top predictions has a prediction accuracy which exceeds that of any individual model, 7-19x better than our previous state-of-the-art. The results highlight the potential of transformer architectures for predicting quantum mechanical (QM) molecular properties.

Carbonylative C-C Bond Activation of Aminocyclopropanes Using a Temporary Directing Group Strategy.

Temporary directing groups (TDGs) underpin a range of C-C bond activation methodologies; however, the use of TDGs for the regiocontrolled activation of cyclopropane C-C bonds is underdeveloped. In this report, we show how an unusual ring contraction process can be harnessed for TDG-based carbonylative C-C bond activations of cyclopropanes. The method involves the transient installation of an isocyanate-derived TDG, rather than relying on carbonyl condensation events as used in previous TDG-enabled C-C bond activations.

How Big is the Pinacol Boronic Ester as a Substituent?

The synthetically versatile pinacol boronic ester group (Bpin) is generally thought of as a bulky moiety because of the two adjacent quaternary sp3 -hydribized carbon atoms in its diol backbone. However, recent diastereoselective reactions reported in the literature have cast doubt on this perception. Reported herein is a detailed experimental and computational analysis of Bpin and structurally related boronic esters which allows determination of three different steric parameters for the Bpin group: the A-value, ligand cone angle, and percent buried volume. All three parameters suggest that the Bpin moiety is remarkably small, with the planarity of the oxygen-boron-oxygen motif playing an important role in minimising steric interactions. Of the three steric parameters, percent buried volume provides the best correlation between steric size and diastereoselectivity in a Diels-Alder reaction.

IMPRESSION - prediction of NMR parameters for 3-dimensional chemical structures using machine learning with near quantum chemical accuracy.

The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar information Of Nuclei) machine learning system provides an efficient and accurate method for the prediction of NMR parameters from 3-dimensional molecular structures. Here we demonstrate that machine learning predictions of NMR parameters, trained on quantum chemical computed values, can be as accurate as, but computationally much more efficient (tens of milliseconds per molecular structure) than, quantum chemical calculations (hours/days per molecular structure) starting from the same 3-dimensional structure. Training the machine learning system on quantum chemical predictions, rather than experimental data, circumvents the need for the existence of large, structurally diverse, error-free experimental databases and makes IMPRESSION applicable to solving 3-dimensional problems such as molecular conformation and stereoisomerism.

Odd-even alternations in helical propensity of a homologous series of hydrocarbons.

Odd and even homologues of some n-alkane-based systems are known to exhibit notably different trends in solid-state properties; a well-known illustration is the zigzag plot of their melting point versus chain length. Odd-even effects in the solid state often arise from intermolecular interactions that involve fully extended molecules. These effects have also been observed in less condensed phases, such as self-assembled monolayers; however, the origins of these effects in such systems can be difficult to determine. Here we combined NMR and computational analysis to show that all-syn contiguously methyl-substituted hydrocarbons, with chain lengths from C6 to C11, exhibit a dramatic odd-even effect in helical propensity. The even- and odd-numbered hydrocarbons populate regular and less-controlled helical conformations, respectively. This knowledge will guide the design of helical hydrocarbons as rigid scaffolds or as hydrophobic components in soft materials.

Identification and quantification of myo-inositol hexakisphosphate in complex environmental matrices using ion chromatography and high-resolution mass spectrometry in comparison to 31P NMR spectroscopy.

Myo-inositol hexakisphosphate, or phytic acid, (myo-IP6) is a key organic phosphorus (P) compound in soils and manures. Determinations of myo-IP6 in soils and manure extracts are frequently performed by 31P NMR spectroscopy. This approach is time-consuming in terms of both sample preparation and instrument time, with uncertainties existing in relation to accuracy of identification and quantification due to potentially interfering resonances from co-extracted P species. In contrast, ion chromatography (IC) in combination with high-resolution mass spectrometry (HRMS) negative ion, electrospray ionisation (ESI) has been shown to enable highly specific identifications of myo-IP6 isolated from complex mixtures. In this paper, IC and ESI-HRMS were applied to the identification and the quantification of myo-IP6 isolated from soils and manures using NaOH-EDTA extraction, and quantifications based on IC. ESI-HRMS analysis of eluate trapped from IC unequivocally confirmed identification of myo-IP6 from a soil extract. The ion suppression cell of the IC instrument provides isolates of the analyte free of ionic components that would interfere with ESI. The myo-IP6 was identified in the NMR by comparing spectra of extracts of soils with and without authentic myo-IP6 "spiked" prior to extraction. Comparison of quantification via standard addition in IC and NMR analysis gave good correlation (r = 0.955). IC with ESI-HRMS was found to be more sensitive, rapid and reliable for the identification and quantification of myo-IP6 with a limit of detection (LOD) of 0.7 mg kg-1 and limit of quantification (LOQ) of 2.1 mg kg-1 using IC versus > 10 mg kg-1 LOD using 31P NMR.

Accelerated acquisition in pure-shift spectra based on prior knowledge from 1H NMR.

Pure-shift NMR enhances spectral resolution, but the optimal resolution can only be obtained at the cost of acquisition time. We propose to accelerate pure-shift acquisition using optimised 'burst' non-uniform sampling schemes [I. E. Ndukwe, A. Shchukina, K. Kazimierczuk and C. P. Butts, Chem. Commun., 2016, 52, 12769] and then reconstruct the undersampled signal mathematically. Here, we focus on the reliability of this reconstruction depending on the sampling scheme and present a workflow for the sampling optimization. It is ready to be implemented in routine measurements and yields a great improvement in reconstruction of challenging cases.

High Resolution for Chemical Shifts and Scalar Coupling Constants: The 2D Real-Time J-Upscaled PSYCHE-DIAG.

The facile determination of chemical shift and scalar coupling constants in NMR spectra is often prevented by spectral overlap and limited resolution. Here, we present a high-resolution NMR experiment for the simultaneous detection of both resonance frequencies and coupling patterns even with small J-values. A PSYCHE-decoupled DIAG (Pure Shift Yielded by Chirp Excitation- DIAGonal) experiment, which resolves chemical shift in the indirect dimension of a 2D experiment is combined with real-time J-upscaling in order to visualize small coupling constants that would otherwise be hidden in the linewidth of a regular proton or DIAG spectrum.

Improved NOE fitting for flexible molecules based on molecular mechanics data - a case study with S-adenosylmethionine.

The use of molecular dynamics (MD) calculations to derive relative populations of conformers is highly sensitive to both timescale and parameterisation of the MD. Where these calculations are coupled with NOE data to determine the dynamics of a molecular system, this can present issues if these populations are thus relied upon. We present an approach that refines the highly accurate PANIC NMR methodology combined with clustering approaches to generate conformers, but without restraining the simulations or considering the relative population distributions generated by MD. Combining this structural sampling with NOE fitting, we demonstrate, for S-adenosylmethionine (aqueous solution at pH 7.0), significant improvements are made to the fit of populations to the experimental data, revealing a strong overall preference for the syn conformation of the adenosyl group relative to the ribose ring, but with less discrimination for the conformation of the ribose ring itself.