Efficiently Computing NMR 1H and 13C Chemical Shifts of Saccharides in Aqueous Environment

Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networks

Carbohydrates, vital components of biological systems, are well-known for their structural diversity. Nuclear Magnetic Resonance (NMR) spectroscopy plays a crucial role in understanding their intricate molecular arrangements and is essential in assessing and verifying the molecular structure of organic molecules. An important part of this process is to predict the NMR chemical shift from the molecular structure. This work introduces a novel approach that leverages E(3) equivariant graph neural networks to predict carbohydrate NMR spectral data. Notably, our model achieves a substantial reduction in mean absolute error, up to threefold, compared to traditional models that rely solely on two-dimensional molecular structure. Even with limited data, the model excels, highlighting its robustness and generalization capabilities. The model is dubbed GeqShift (geometric equivariant shift) and uses equivariant graph self-attention layers to learn about NMR chemical shifts, in particular since stereochemical arrangements in carbohydrate molecules are characteristics of their structures.

Synthesis and unexpected binding of monofluorinated N,N'-diacetylchitobiose and LacdiNAc to wheat germ agglutinin

Fluorination of carbohydrate ligands of lectins is a useful approach to examine their binding profile, improve their metabolic stability and lipophilicity, and convert them into 19F NMR-active probes. However, monofluorination of monovalent carbohydrate ligands often leads to a decreased or completely lost affinity. By chemical glycosylation, we synthesized the full series of methyl β-glycosides of N,N'-diacetylchitobiose (GlcNAcβ(1-4)GlcNAcβ1-OMe) and LacdiNAc (GalNAcβ(1-4)GlcNAcβ1-OMe) systematically monofluorinated at all hydroxyl positions. A competitive enzyme-linked lectin assay revealed that the fluorination at the 6'-position of chitobioside resulted in an unprecedented increase in affinity to wheat germ agglutinin (WGA) by one order of magnitude. For the first time, we have characterized the binding profile of a previously underexplored WGA ligand LacdiNAc. Surprisingly, 4'-fluoro-LacdiNAc bound WGA even stronger than unmodified LacdiNAc. These observations were interpreted using molecular dynamic calculations along with STD and transferred NOESY NMR techniques, which gave evidence for the strengthening of CH/π interactions after deoxyfluorination of the side chain of the non-reducing GlcNAc. These results highlight the potential of fluorinated glycomimetics as high-affinity ligands of lectins and 19F NMR-active probes.

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling

In this work, we introduce the Solvate Suite, a comprehensive and modular command-line interface designed for molecular simulation and microsolvation modeling. The suite interfaces with widely used scientific software, streamlining computational experiments for liquid systems through the automated creation of simulation boxes and topology with adjustable simulation parameters. Furthermore, it has features for graphical and statistical analysis of simulated properties and extraction of trajectory configurations with various filters. Additionally, it introduces innovative strategies for microsolvation modeling with a multiscale approach, employing equilibrated dynamics to identify favorable solute-solvent interactions and enabling full cluster optimization for free-energy calculations without imaginary frequency contamination.

Deconvolution and Analysis of the 1H NMR Spectra of Crude Reaction Mixtures

Nuclear magnetic resonance (NMR) spectroscopy is an important analytical technique in synthetic organic chemistry, but its integration into high-throughput experimentation workflows has been limited by the necessity of manually analyzing the NMR spectra of new chemical entities. Current efforts to automate the analysis of NMR spectra rely on comparisons to databases of reported spectra for known compounds and, therefore, are incompatible with the exploration of new chemical space. By reframing the NMR spectrum of a reaction mixture as a joint probability distribution, we have used Hamiltonian Monte Carlo Markov Chain and density functional theory to fit the predicted NMR spectra to those of crude reaction mixtures. This approach enables the deconvolution and analysis of the spectra of mixtures of compounds without relying on reported spectra. The utility of our approach to analyze crude reaction mixtures is demonstrated with the experimental spectra of reactions that generate a mixture of isomers, such as Wittig olefination and C-H functionalization reactions. The correct identification of compounds in a reaction mixture and their relative concentrations is achieved with a mean absolute error as low as 1%.

Ligand 1 H NMR Chemical Shifts as Accurate Reporters for Protein-Ligand Binding Interfaces in Solution

The availability of high-resolution 3D structural information is crucial for investigating guest-host systems across a wide range of fields. In the context of drug discovery, the information is routinely used to establish and validate structure-activity relationships, grow initial hits from screening campaigns, and to guide molecular docking. For the generation of protein-ligand complex structural information, X-ray crystallography is the experimental method of choice, however, with limited information on protein flexibility. An experimentally verified structural model of the binding interface in the native solution-state would support medicinal chemists in their molecular design decisions. Here we demonstrate that protein-bound ligand 1 H NMR chemical shifts are highly sensitive and accurate probes for the immediate chemical environment of protein-ligand interfaces. By comparing the experimental ligand 1 H chemical shift values with those computed from the X-ray structure using quantum mechanics methodology, we identify significant disagreements for parts of the ligand between the two experimental techniques. We show that quantum mechanics/molecular mechanics (QM/MM) molecular dynamics (MD) ensembles can be used to refine initial X-ray co-crystal structures resulting in a better agreement with experimental 1 H ligand chemical shift values. Overall, our findings highlight the usefulness of ligand 1 H NMR chemical shift information in combination with a QM/MM MD workflow for generating protein-ligand ensembles that accurately reproduce solution structural data.

On the origin of the electronic and magnetic circular dichroism of naphthyl C-glycosides: Anomeric configuration

Aryl C-glycosides, in which the glycosidic bond is changed to a carbon-carbon bond, are an important family of biologically-active compounds. They often serve as secondary metabolites or exhibit antibiotic and cytostatic activities. Their stability to hydrolysis has made them attractive targets for new drugs. Their conformational behavior often strongly influences the resulting function. Their detailed structural and conformational description is thus highly desirable. This work studies the structure of three different naphthyl C-glycosides using UV-vis absorption as well as electronic and magnetic circular dichroism. It also describes their conformational preferences using a combination of molecular dynamics and DFT calculations. The reliability of these preferences has been verified by simulations of spectral properties and a comparison with their measured spectra. In particular, ECD spectroscopy has been shown to distinguish easily between α- and β-pseudoanomers of aryl C-glycosides. Computer simulations and spectral decomposition have revealed how the resulting ECD patterns of the naphthyl glycosides studied are influenced by different conformer populations. In conclusion, reliable ECD patterns cannot be calculated by separating the naphthyl rotation from other conformational motions. MCD patterns have been similar for all the naphthyl C-glycosides studied. No clear diagnostic features have been found for either the pseudoanomeric configuration or the preferred hydroxymethyl rotamer. Nevertheless, the work has demonstrated the potential of MCD for the study of aryl glycosides interacting with proteins.

Experimental and Computational Investigation of the Oxime Bond Stereochemistry in c-Jun N-terminal Kinase 3 Inhibitors 11H-Indeno[1,2-b]quinoxalin-11-one Oxime and Tryptanthrin-6-oxime

11H-Indeno[1,2-b]quinoxalin-11-one oxime (IQ-1) and tryptanthrin-6-oxime are potent c-Jun N-terminal kinase 3 (JNK-3) inhibitors demonstrating neuroprotective, anti-inflammatory and anti-arthritic activity. However, the stereochemical configuration of the oxime carbon-nitrogen double bond (E- or Z-) in these compounds was so far unknown. In this contribution, we report the results of the determination of the double bond configuration in the solid state by single crystal X-ray diffraction and in solution by 1D and 2D NMR techniques and DFT calculations. It was found that both in the solid state and in solution, IQ-1 adopts the E-configuration stabilized by intermolecular hydrogen bonds, in contrast to previously assumed Z-configuration that could be stabilized only by an intramolecular hydrogen bond.

DELTA50: A Highly Accurate Database of Experimental 1H and 13C NMR Chemical Shifts Applied to DFT Benchmarking

Density functional theory (DFT) benchmark studies of ¹H and ¹³C NMR chemical shifts often yield differing conclusions, likely due to non-optimal test molecules and non-standardized data acquisition. To address this issue, we carefully selected and measured ¹H and ¹³C NMR chemical shifts for 50 structurally diverse small organic molecules containing atoms from only the first two rows of the periodic table. Our NMR dataset, DELTA50, was used to calculate linear scaling factors and to evaluate the accuracy of 73 density functionals, 40 basis sets, 3 solvent models, and 3 gauge-referencing schemes. The best performing DFT methodologies for ¹H and ¹³C NMR chemical shift predictions were WP04/6-311++G(2d,p) and ωB97X-D/def2-SVP, respectively, when combined with the polarizable continuum solvent model (PCM) and gauge-independent atomic orbital (GIAO) method. Geometries should be optimized at the B3LYP-D3/6-311G(d,p) level including the PCM solvent model for the best accuracy. Predictions of 20 organic compounds and natural products from a separate probe set had root-mean-square deviations (RMSD) of 0.07 to 0.19 for ¹H and 0.5 to 2.9 for ¹³C. Maximum deviations were less than 0.5 and 6.5 ppm for ¹H and ¹³C, respectively.

Reference interaction site model self-consistent field with constrained spatial electron density approach for nuclear magnetic shielding in solution

We propose a new hybrid approach combining quantum chemistry and statistical mechanics of liquids for calculating the nuclear magnetic resonance (NMR) chemical shifts of solvated molecules. Based on the reference interaction site model self-consistent field with constrained spatial electron density distribution (RISM–SCF–cSED) method, the electronic structure of molecules in solution is obtained, and the expression for the nuclear magnetic shielding tensor is derived as the second-order derivative of the Helmholtz energy of the solution system. We implemented a method for calculating chemical shifts and applied it to an adenine molecule in water, where hydrogen bonding plays a crucial role in electronic and solvation structures. We also performed the calculations of 17O chemical shifts, which showed remarkable solvent dependence. While converged results could not be sometimes obtained using the conventional method, in the present framework with RISM–SCF–cSED, an adequate representation of electron density is guaranteed, making it possible to obtain an NMR shielding constant stably. This introduction of cSED is key to extending the method’s applicability to obtain the chemical shift of various chemical species. The present demonstration illustrates our approach’s superiority in terms of numerical robustness and accuracy.