Furosemide's one little hydrogen atom: NMR crystallography structure verification of powdered molecular organics

An NMR crystallographic characterisation of solid (+)-usnic acid

We use a combination of one- and two-dimensional solid-state nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) calculations to obtain a full assignment of the 1H and 13C signals for solid (+)-usnic acid, which contains two molecules in the asymmetric unit. By combining through-space 1H-1H correlation data with computation it is possible to assign signals not just to the same molecules (relative assignment) but to assign the signals to specific crystallographic molecules (absolute assignment). Variable-temperature measurements reveal that there is some variation in many of the 13C chemical shifts with temperature, likely arising from varying populations of different tautomeric forms of the molecule. The NMR spectrum of crystalline (+)-usnic acid is then compared with that of ground Usnea dasopoga lichen (the source material of the usnic acid). The abundance of usnic acid is so great in the lichen that this natural product can be observed directly in the NMR spectrum without further purification. This natural sample of usnic acid appears to have the same crystalline form as that in the pure commercial sample.

Polymorph Identification for Flexible Molecules: Linear Regression Analysis of Experimental and Calculated Solution- and Solid-State NMR Data

The Δδ regression approach of Blade et al. [ J. Phys. Chem. A 2020, 124(43), 8959-8977] for accurately discriminating between solid forms using a combination of experimental solution- and solid-state NMR data with density functional theory (DFT) calculation is here extended to molecules with multiple conformational degrees of freedom, using furosemide polymorphs as an exemplar. As before, the differences in measured 1H and 13C chemical shifts between solution-state NMR and solid-state magic-angle spinning (MAS) NMR (Δδexperimental) are compared to those determined by gauge-including projector augmented wave (GIPAW) calculations (Δδcalculated) by regression analysis and a t-test, allowing the correct furosemide polymorph to be precisely identified. Monte Carlo random sampling is used to calculate solution-state NMR chemical shifts, reducing computation times by avoiding the need to systematically sample the multidimensional conformational landscape that furosemide occupies in solution. The solvent conditions should be chosen to match the molecule's charge state between the solution and solid states. The Δδ regression approach indicates whether or not correlations between Δδexperimental and Δδcalculated are statistically significant; the approach is differently sensitive to the popular root mean squared error (RMSE) method, being shown to exhibit a much greater dynamic range. An alternative method for estimating solution-state NMR chemical shifts by approximating the measured solution-state dynamic 3D behavior with an ensemble of 54 furosemide crystal structures (polymorphs and cocrystals) from the Cambridge Structural Database (CSD) was also successful in this case, suggesting new avenues for this method that may overcome its current dependency on the prior determination of solution dynamic 3D structures.

Exploring the Potential of Multinuclear Solid-State 1 H, 13 C, and 35 Cl Magnetic Resonance To Characterize Static and Dynamic Disorder in Pharmaceutical Hydrochlorides

Crystallographic disorder, whether static or dynamic, can be detrimental to the physical and chemical stability, ease of crystallization and dissolution rate of an active pharmaceutical ingredient. Disorder can result in a loss of manufacturing control leading to batch-to-batch variability and can lengthen the process of structural characterization. The range of NMR active nuclei makes solid-state NMR a unique technique for gaining nucleus-specific information about crystallographic disorder. Here, we explore the use of high-field ³⁵ Cl solid-state NMR at 23.5 T to characterize both static and dynamic crystallographic disorder: specifically, dynamic disorder occurring in duloxetine hydrochloride (1), static disorder in promethazine hydrochloride (2), and trifluoperazine dihydrochloride (3). In all structures, the presence of crystallographic disorder was confirmed by ¹³ C cross-polarization magic-angle spinning (CPMAS) NMR and supported by GIPAW-DFT calculations, and in the case of 3, ¹ H solid-state NMR provided additional confirmation. Applying ³⁵ Cl solid-state NMR to these compounds, we show that higher magnetic fields are beneficial for resolving the crystallographic disorder in 1 and 3, while broad spectral features were observed in 2 even at higher fields. Combining the data obtained from ¹ H, ¹³ C, and ³⁵ Cl NMR, we show that 3 exhibits a unique case of disorder involving the ⁺ N-H hydrogen positions of the piperazinium ring, driving the chloride anions to occupy three distinct sites.

A Machine Learning Model of Chemical Shifts for Chemically and Structurally Diverse Molecular Solids

Nuclear magnetic resonance (NMR) chemical shifts are a direct probe of local atomic environments and can be used to determine the structure of solid materials. However, the substantial computational cost required to predict accurate chemical shifts is a key bottleneck for NMR crystallography. We recently introduced ShiftML, a machine-learning model of chemical shifts in molecular solids, trained on minimum-energy geometries of materials composed of C, H, N, O, and S that provides rapid chemical shift predictions with density functional theory (DFT) accuracy. Here, we extend the capabilities of ShiftML to predict chemical shifts for both finite temperature structures and more chemically diverse compounds, while retaining the same speed and accuracy. For a benchmark set of 13 molecular solids, we find a root-mean-squared error of 0.47 ppm with respect to experiment for ¹H shift predictions (compared to 0.35 ppm for explicit DFT calculations), while reducing the computational cost by over four orders of magnitude.

Narrowing down the conformational space with solid-state NMR in crystal structure prediction of linezolid cocrystals

Many solids crystallize as microcrystalline powders, thus precluding the application of single crystal X-Ray diffraction in structural elucidation. In such cases, a joint use of high-resolution solid-state NMR and crystal structure prediction (CSP) calculations can be successful. However, for molecules showing significant conformational freedom, the CSP-NMR protocol can meet serious obstacles, including ambiguities in NMR signal assignment and too wide conformational search space to be covered by computational methods in reasonable time. Here, we demonstrate a possible way of avoiding these obstacles and making as much use of the two methods as possible in difficult circumstances. In a simple case, our experiments led to crystal structure elucidation of a cocrystal of linezolid (LIN), a wide-range antibiotic, with 2,3-dihydroxybenzoic acid, while a significantly more challenging case of a cocrystal of LIN with 2,4-dihydroxybenzoic acid led to the identification of the most probable conformations of LIN inside the crystal. Having four rotatable bonds, some of which can assume many discreet values, LIN molecule poses a challenge in establishing its conformation in a solid phase. In our work, a set of 27 conformations were used in CSP calculations to yield model crystal structures to be examined against experimental solid-state NMR data, leading to a reliable identification of the most probable molecular arrangements.

Combining X-ray and NMR Crystallography to Explore the Crystallographic Disorder in Salbutamol Oxalate

Salbutamol is an active pharmaceutical ingredient commonly used to treat respiratory distress and is listed by the World Health Organization as an essential medicine. Here, we establish the crystal structure of its oxalate form, salbutamol oxalate, and explore the nature of its crystallographic disorder by combined X-ray crystallography and ¹³C cross-polarization (CP) magic-angle spinning (MAS) solid-state NMR. The *C-OH chiral center of salbutamol (note that the crystal structures are a racemic mixture of the two enantiomers of salbutamol) is disordered over two positions, and the tert-butyl group is rotating rapidly, as revealed by ¹³C solid-state NMR. The impact of crystallization conditions on the disorder was investigated, finding variations in the occupancy ratio of the *C-OH chiral center between single crystals and a consistency across samples in the bulk powder. Overall, this work highlights the contrast between investigating crystallographic disorder by X-ray diffraction and solid-state NMR experiment, and gauge-including projector-augmented-wave (GIPAW) density functional theory (DFT) calculations, with their combined use, yielding an improved understanding of the nature of the crystallographic disorder between the local (i.e., as viewed by NMR) and longer-range periodic (i.e., as viewed by diffraction) scale.

From Powders to Single Crystals: A Crystallographer's Toolbox for Small-Molecule Structure Determination

Although the crystal structures of small-molecule compounds are often determined from single-crystal X-ray diffraction (scXRD), recent advances in three-dimensional electron diffraction (3DED) and crystal structure prediction (CSP) methods promise to expand the structure elucidation toolbox available to the crystallographer. Herein, a comparative assessment of scXRD, 3DED, and CSP in combination with powder X-ray diffraction is carried out on two former drug candidate compounds and a multicomponent crystal of a key building block in the synthesis of gefapixant citrate.

A toolbox for improving the workflow of NMR crystallography

NMR crystallography is a powerful tool with applications in structural characterization and crystal structure verification, to name two. However, applying this tool presents several challenges, especially for industrial users, in terms of consistency, workflow, time consumption, and the requirement for a high level of understanding of experimental solid-state NMR and GIPAW-DFT calculations. Here, we have developed a series of fully parameterized scripts for use in Materials Studio and TopSpin, based on the .magres file format, with a focus on organic molecules (e.g. pharmaceuticals), improving efficiency, robustness, and workflow. We separate these tools into three major categories: performing the DFT calculations, extracting & visualizing the results, and crystallographic modelling. These scripts will rapidly submit fully parameterized CASTEP jobs, extract data from the calculations, assist in visualizing the results, and expedite the process of structural modelling. Accompanied with these tools is a description on their functionality, documentation on how to get started and use the scripts, and links to video tutorials for guiding new users. Through the use of these tools, we hope to facilitate NMR crystallography and to harmonize the process across users.

Structural Refinement of Carbimazole by NMR Crystallography

The characterization of the three-dimensional structure of solids is of major importance, especially in the pharmaceutical field. In the present work, NMR crystallography methods are applied with the aim to refine the crystal structure of carbimazole, an active pharmaceutical ingredient used for the treatment of hyperthyroidism and Grave’s disease. Starting from previously reported X-ray diffraction data, two refined structures were obtained by geometry optimization methods. Experimental ¹H and ¹³C isotropic chemical shift measured by the suitable ¹H and ¹³C high-resolution solid state NMR techniques were compared with DFT-GIPAW calculated values, allowing the quality of the obtained structure to be experimentally checked. The refined structure was further validated through the analysis of ¹H-¹H and ¹H-¹³C 2D NMR correlation experiments. The final structure differs from that previously obtained from X-ray diffraction data mostly for the position of hydrogen atoms.

Analyzing Discrepancies in Chemical-Shift Predictions of Solid Pyridinium Fumarates

Highly accurate chemical-shift predictions in molecular solids are behind the success and rapid development of NMR crystallography. However, unusually large errors of predicted hydrogen and carbon chemical shifts are sometimes reported. An understanding of these deviations is crucial for the reliability of NMR crystallography. Here, recently reported large deviations of predicted hydrogen and carbon chemical shifts of a series of solid pyridinium fumarates are thoroughly analyzed. The influence of the geometry optimization protocol and of the computational level of NMR calculations on the accuracy of predicted chemical shifts is investigated. Periodic calculations with GGA, meta-GGA and hybrid functionals are employed. Furthermore, molecular corrections at the coupled-cluster singles-and-doubles (CCSD) level are calculated. The effect of nuclear delocalization on the structure and NMR shielding is also investigated. The geometry optimization with a computationally demanding hybrid functional leads to a substantial improvement in proton chemical-shift predictions.

Modeling Small Structural and Environmental Differences in Solids with 15 N NMR Chemical Shift Tensors

The ability to theoretically predict accurate NMR chemical shifts in solids is increasingly important due to the role such shifts play in selecting among proposed model structures. Herein, two theoretical methods are evaluated for their ability to assign ¹⁵ N shifts from guanosine dihydrate to one of the two independent molecules present in the lattice. The NMR data consist of ¹⁵ N shift tensors from 10 resonances. Analysis using periodic boundary or fragment methods consider a benchmark dataset to estimate errors and predict uncertainties of 5.6 and 6.2 ppm, respectively. Despite this high accuracy, only one of the five sites were confidently assigned to a specific molecule of the asymmetric unit. This limitation is not due to negligible differences in experimental data, as most sites exhibit differences of >6.0 ppm between pairs of resonances representing a given position. Instead, the theoretical methods are insufficiently accurate to make assignments at most positions.

Refining crystal structures using 13C NMR chemical shift tensors as a target function

A two-step process is described for refining crystal structures from any source.

Towards Accurate Predictions of Proton NMR Spectroscopic Parameters in Molecular Solids

The factors contributing to the accuracy of quantum-chemical calculations for the prediction of proton NMR chemical shifts in molecular solids are systematically investigated. Proton chemical shifts of six solid amino acids with hydrogen atoms in various bonding environments (CH, CH₂ , CH₃ , OH, SH and NH₃ ) were determined experimentally using ultra-fast magic-angle spinning and proton-detected 2D NMR experiments. The standard DFT method commonly used for the calculations of NMR parameters of solids is shown to provide chemical shifts that deviate from experiment by up to 1.5 ppm. The effects of the computational level (hybrid DFT functional, coupled-cluster calculation, inclusion of relativistic spin-orbit coupling) are thoroughly discussed. The effect of molecular dynamics and nuclear quantum effects are investigated using path-integral molecular dynamics (PIMD) simulations. It is demonstrated that the accuracy of the calculated proton chemical shifts is significantly better when these effects are included in the calculations.

NMR crystallography of molecular organics

Developments of NMR methodology to characterise the structures of molecular organic structures are reviewed, concentrating on the previous decade of research in which density functional theory-based calculations of NMR parameters in periodic solids have become widespread. With a focus on demonstrating the new structural insights provided, it is shown how "NMR crystallography" has been used in a spectrum of applications from resolving ambiguities in diffraction-derived structures (such as hydrogen atom positioning) to deriving complete structures in the absence of diffraction data. As well as comprehensively reviewing applications, the different aspects of the experimental and computational techniques used in NMR crystallography are surveyed. NMR crystallography is seen to be a rapidly maturing subject area that is increasingly appreciated by the wider crystallographic community.

Resolving alternative organic crystal structures using density functional theory and NMR chemical shifts

Alternative (‘repeat’) determinations of organic crystal structures deposited in the Cambridge Structural Database are analysed to characterise the nature and magnitude of the differences between structure solutions obtained by diffraction methods. Of the 3132 structure pairs considered, over 20% exhibited local structural differences exceeding 0.25 Å. In most cases (about 83%), structural optimisation using density functional theory (DFT) resolved the differences. Many of the cases where distinct and chemically significant structural differences remained after optimisation involved differently positioned hydroxyl groups, with obvious implications for the correct description of hydrogen bonding. ¹H and ¹³C chemical shifts from solid-state NMR experiments are proposed as an independent methodology in cases where DFT optimisation fails to resolve discrepancies.

DFT optimisation often resolves conflicting crystal structure determinations, with NMR shifts helping in cases where optimisation diverges to different structures.

A Bayesian approach to NMR crystal structure determination

Nuclear Magnetic Resonance (NMR) spectroscopy is particularly well suited to determine the structure of molecules and materials in powdered form. Structure determination usually proceeds by finding the best match between experimentally observed NMR chemical shifts and those of candidate structures. Chemical shifts for the candidate configurations have traditionally been computed by electronic-structure methods, and more recently predicted by machine learning. However, the reliability of the determination depends on the errors in the predicted shifts. Here we propose a Bayesian framework for determining the confidence in the identification of the experimental crystal structure, based on knowledge of the typical errors in the electronic structure methods. We demonstrate the approach on the determination of the structures of six organic molecular crystals. We critically assess the reliability of the structure determinations, facilitated by the introduction of a visualization of the similarity between candidate configurations in terms of their chemical shifts and their structures. We also show that the commonly used values for the errors in calculated ¹³C shifts are underestimated, and that more accurate, self-consistently determined uncertainties make it possible to use ¹³C shifts to improve the accuracy of structure determinations. Finally, we extend the recently-developed ShiftML model to render it more efficient, accurate, and, most importantly, to evaluate the uncertainties in its predictions. By quantifying the confidence in structure determinations based on ShiftML predictions we further substantiate that it provides a valid replacement for first-principles calculations in NMR crystallography.

Line narrowing in 1H NMR of powdered organic solids with TOP-CT-MAS experiments at ultra-fast MAS

The residual broadening observed in ¹H spectra of rigid organic solids at natural abundance under 111 kHz magic angle spinning (MAS) is typically a few hundred Hertz. Here we show that refocusable and non-refocusable interactions contribute roughly equally to this residual at high-fields (21.14 T), and suggest that the removal of the non-refocusable part will produce significant increase in spectral resolution. To this end, we demonstrate an experiment for the indirect acquisition of constant-time experiments at ultra-fast MAS (CT-MAS) which verifies this hypothesis. The combination of this experiment with the two-dimensional one pulse (TOP) transformation reduces the experimental time to a fraction of the original cost while retaining the narrowing effects. Results obtained with TOP-CT-MAS at 111 kHz MAS on a sample of β-AspAla yield up to 30% higher resolution spectra than the equivalent one-pulse experiment, in less than 10 min.

Rapid Structure Determination of Molecular Solids Using Chemical Shifts Directed by Unambiguous Prior Constraints

NMR-based crystallography approaches involving the combination of crystal structure prediction methods, ab initio calculated chemical shifts and solid-state NMR experiments are powerful methods for crystal structure determination of microcrystalline powders. However, currently structural information obtained from solid-state NMR is usually included only after a set of candidate crystal structures has already been independently generated, starting from a set of single-molecule conformations. Here, we show with the case of ampicillin that this can lead to failure of structure determination. We propose a crystal structure determination method that includes experimental constraints during conformer selection. In order to overcome the problem that experimental measurements on the crystalline samples are not obviously translatable to restrict the single-molecule conformational space, we propose constraints based on the analysis of absent cross-peaks in solid-state NMR correlation experiments. We show that these absences provide unambiguous structural constraints on both the crystal structure and the gas-phase conformations, and therefore can be used for unambiguous selection. The approach is parametrized on the crystal structure determination of flutamide, flufenamic acid, and cocaine, where we reduce the computational cost by around 50%. Most importantly, the method is then shown to correctly determine the crystal structure of ampicillin, which would have failed using current methods because it adopts a high-energy conformer in its crystal structure. The average positional RMSE on the NMR powder structure is ⟨r_av⟩ = 0.176 Å, which corresponds to an average equivalent displacement parameter U_eq = 0.0103 Ų.

An NMR crystallography investigation of furosemide

This paper presents an NMR crystallography study of three polymorphs of furosemide. Experimental magic-angle spinning (MAS) solid-state NMR spectra are reported for form I of furosemide, and these are assigned using density-functional theory (DFT)-based gauge-including projector augmented wave (GIPAW) calculations. Focusing on the three known polymorphs, we examine the changes to the NMR parameters due to crystal packing effects. We use a recently developed formalism to visualise which regions are responsible for the chemical shielding of particular sites and hence understand the variation in NMR parameters between the three polymorphs.

14N NQR spectroscopy reveals the proton position in N–H⋯N bonds: a case study with proton sponges

The position of the proton in intramolecular N–H⋯N hydrogen bonds has been determined to a high accuracy with ¹⁴N Nuclear Quadrupole Resonance (NQR) spectroscopy.

Chemical shifts in molecular solids by machine learning

Due to their strong dependence on local atonic environments, NMR chemical shifts are among the most powerful tools for strucutre elucidation of powdered solids or amorphous materials. Unfortunately, using them for structure determination depends on the ability to calculate them, which  comes at the cost of high accuracy first-principles calculations. Machine learning has recently emerged as a way to overcome the need for quantum chemical calculations, but for chemical shifts in solids it is hindered by the chemical and combinatorial space spanned by molecular solids, the strong dependency of chemical shifts on their environment, and the lack of an experimental database of shifts. We propose a machine learning method based on local environments to accurately predict chemical shifts of molecular solids and their polymorphs to within DFT accuracy. We also demonstrate that the trained model is able to determine, based on the match between experimentally measured and ML-predicted shifts, the structures of cocaine and the drug 4-[4-(2-adamantylcarbamoyl)-5-tert-butylpyrazol-1-yl]benzoic acid.

Solid-state nuclear magnetic resonance combined with quantum chemical shift predictions is limited by high computational cost. Here, the authors use machine learning based on local atomic environments to predict experimental chemical shifts in molecular solids with accuracy similar to density functional theory.

DNP-enhanced solid-state NMR spectroscopy of active pharmaceutical ingredients

Solid-state NMR spectroscopy has become a valuable tool for the characterization of both pure and formulated active pharmaceutical ingredients (APIs). However, NMR generally suffers from poor sensitivity that often restricts NMR experiments to nuclei with favorable properties, concentrated samples, and acquisition of one-dimensional (1D) NMR spectra. Here, we review how dynamic nuclear polarization (DNP) can be applied to routinely enhance the sensitivity of solid-state NMR experiments by one to two orders of magnitude for both pure and formulated APIs. Sample preparation protocols for relayed DNP experiments and experiments on directly doped APIs are detailed. Numerical spin diffusion models illustrate the dependence of relayed DNP enhancements on the relaxation properties and particle size of the solids and can be used for particle size determination when the other factors are known. We then describe the advanced solid-state NMR experiments that have been enabled by DNP and how they provide unique insight into the molecular and macroscopic structure of APIs. For example, with large sensitivity gains provided by DNP, natural isotopic abundance, ¹³ C-¹³ C double-quantum single-quantum homonuclear correlation NMR spectra of pure APIs can be routinely acquired. DNP also enables solid-state NMR experiments with unreceptive quadrupolar nuclei such as ² H, ¹⁴ N, and ³⁵ Cl that are commonly found in APIs. Applications of DNP-enhanced solid-state NMR spectroscopy for the molecular level characterization of low API load formulations such as commercial tablets and amorphous solid dispersions are described. Future perspectives for DNP-enhanced solid-state NMR experiments on APIs are briefly discussed.

Recent Advances in Solid-State Nuclear Magnetic Resonance Spectroscopy

The sensitivity of nuclear magnetic resonance (NMR) spectroscopy to the local atomic-scale environment offers great potential for the characterization of a diverse range of solid materials. Despite offering more information than its solution-state counterpart, solid-state NMR has not yet achieved a similar level of recognition, owing to the anisotropic interactions that broaden the spectral lines and hinder the extraction of structural information. Here, we describe the methods available to improve the resolution of solid-state NMR spectra and the continuing research in this area. We also highlight areas of exciting new and future development, including recent interest in combining experiment with theoretical calculations, the rise of a range of polarization transfer techniques that provide significant sensitivity enhancements, and the progress of in situ measurements. We demonstrate the detailed information available when studying dynamic and disordered solids and discuss the future applications of solid-state NMR spectroscopy across the chemical sciences.

Elucidating an Amorphous Form Stabilization Mechanism for Tenapanor Hydrochloride: Crystal Structure Analysis Using X-ray Diffraction, NMR Crystallography, and Molecular Modeling

By the combined use of powder and single-crystal X-ray diffraction, solid-state NMR, and molecular modeling, the crystal structures of two systems containing the unusually large tenapanor drug molecule have been determined: the free form, ANHY, and a dihydrochloride salt form, 2HCl. Dynamic nuclear polarization (DNP) assisted solid-state NMR (SSNMR) crystallography investigations were found essential for the final assignment and were used to validate the crystal structure of ANHY. From a structural informatics analysis of ANHY and 2HCl, conformational ring differences in one part of the molecule were observed which influence the relative orientation of a methyl group on a ring nitrogen and thereby impact the crystallizability of the dihydrochloride salt. From quantum chemistry calculations, the dynamics between different ring conformations in tenapanor is predicted to be fast. Addition of HCl to tenapanor results in general in a mixture of protonated ring conformers and hence a statistical mix of diastereoisomers which builds up the amorphous form, a-2HCl. This was qualitatively verified by ¹³C CP/MAS NMR investigations of the amorphous form. Thus, to form any significant amount of the crystalline material 2HCl, which originates from the minor (i.e., energetically less stable) ring conformations, one needs to involve nitrogen deprotonation to allow exchange between the minor and major conformations of ANHY in solution. Thus, by controlling the solution pH value to well below the p K_a of ANHY, the equilibrium between ANHY and 2HCl can be controlled and by this mechanism the crystallization of 2HCl can be avoided and the amorphous form of the dichloride salt can therefore be stabilized.

Does Z' equal 1 or 2? Enhanced powder NMR crystallography verification of a disordered room temperature crystal structure of a p38 inhibitor for chronic obstructive pulmonary disease

The crystal structure of the Form A polymorph of N-cyclopropyl-3-fluoro-4-methyl-5-[3-[[1-[2-[2-(methylamino)ethoxy]phenyl]cyclopropyl]amino]-2-oxo-pyrazin-1-yl]benzamide (i.e., AZD7624), determined using single-crystal X-ray diffraction (scXRD) at 100 K, contains two molecules in the asymmetric unit (Z' = 2) and has regions of local static disorder. This substance has been in phase IIa drug development trials for the treatment of chronic obstructive pulmonary disease, a disease which affects over 300 million people and contributes to nearly 3 million deaths annually. While attempting to verify the crystal structure using nuclear magnetic resonance crystallography (NMRX), we measured ¹³C solid-state NMR (SSNMR) spectra at 295 K that appeared consistent with Z' = 1 rather than Z' = 2. To understand this surprising observation, we used multinuclear SSNMR (¹H, ¹³C, ¹⁵N), gauge-including projector augmented-wave density functional theory (GIPAW DFT) calculations, crystal structure prediction (CSP), and powder XRD (pXRD) to determine the room temperature crystal structure. Due to the large size of AZD7624 (ca. 500 amu, 54 distinct ¹³C environments for Z' = 2), static disorder at 100 K, and (as we show) dynamic disorder at ambient temperatures, NMR spectral assignment was a challenge. We introduce a method to enhance confidence in NMR assignments by comparing experimental ¹³C isotropic chemical shifts against site-specific DFT-calculated shift distributions established using CSP-generated crystal structures. The assignment and room temperature NMRX structure determination process also included measurements of ¹³C shift tensors and the observation of residual dipolar coupling between ¹³C and ¹⁴N. CSP generated ca. 90 reasonable candidate structures (Z' = 1 and Z' = 2), which when coupled with GIPAW DFT results, room temperature pXRD, and the assigned SSNMR data, establish Z' = 2 at room temperature. We find that the polymorphic Form A of AZD7624 is maintained at room temperature, although dynamic disorder is present on the NMR timescale. Of the CSP-generated structures, 2 are found to be fully consistent with the SSNMR and pXRD data; within this pair, they are found to be structurally very similar (RMSD₁₆ = 0.30 Å). We establish that the CSP structure in best agreement with the NMR data possesses the highest degree of structural similarity with the scXRD-determined structure (RMSD₁₆ = 0.17 Å), and has the lowest DFT-calculated energy amongst all CSP-generated structures with Z' = 2.

Recent progress of structural study of polymorphic pharmaceutical drugs

This review considers advances in the understanding of active pharmaceutical ingredient polymorphism since around 2010 mainly from a structural view point, with a focus on twelve model drugs. New polymorphs of most of these drugs have been identified despite that the polymorphism of these old drugs has been extensively studied so far. In addition to the conventional modifications of preparative solvents, temperatures, and pressure, more strategic structure-based methods have successfully yielded new polymorphs. The development of analytical techniques, including X-ray analyses, spectroscopy, and microscopy has facilitated the identification of unknown crystal structures and also the discovery of new polymorphs. Computational simulations have played an important role in explaining and predicting the stability order of polymorphs. Furthermore, these make significant contributions to the design of new polymorphs by considering structure and energy. The new technologies and insights discussed in this review will contribute to the control of polymorphic forms, both during manufacture and in the drug formulation.

Pharmaceutical cocrystals, salts and polymorphs: Advanced characterization techniques

The main goal of a novel drug development is to obtain it with optimal physiochemical, pharmaceutical and biological properties. Pharmaceutical companies and scientists modify active pharmaceutical ingredients (APIs), which often are cocrystals, salts or carefully selected polymorphs, to improve the properties of a parent drug. To find the best form of a drug, various advanced characterization methods should be used. In this review, we have described such analytical methods, dedicated to solid drug forms. Thus, diffraction, spectroscopic, thermal and also pharmaceutical characterization methods are discussed. They all are necessary to study a solid API in its intrinsic complexity from bulk down to the molecular level, gain information on its structure, properties, purity and possible transformations, and make the characterization efficient, comprehensive and complete. Furthermore, these methods can be used to monitor and investigate physical processes, involved in the drug development, in situ and in real time. The main aim of this paper is to gather information on the current advancements in the analytical methods and highlight their pharmaceutical relevance.

NMR crystallography: structure and properties of materials from solid-state nuclear magnetic resonance observables

This topical review provides a brief overview of recent developments in NMR crystallography and related NMR approaches to studying the properties of molecular and ionic solids. Areas of complementarity with diffraction-based methods are underscored. These include the study of disordered systems, of dynamic systems, and other selected examples where NMR can provide unique insights. Highlights from the literature as well as recent work from my own group are discussed.

Exploring Systematic Discrepancies in DFT Calculations of Chlorine Nuclear Quadrupole Couplings

Previous studies have revealed significant discrepancies between density functional theory (DFT)-calculated and experimental nuclear quadrupolar coupling constants (C_Q) for chlorine atoms, particularly in ionic solids. Various aspects of the computations are systematically investigated here, including the choice of the DFT functional, basis set convergence, and geometry optimization protocol. The effects of fast (fs) time-scale dynamics are probed using molecular dynamics (MD) and nuclear quantum effects (NQEs) are considered using path-integral MD calculations. It is shown that the functional choice is the most important factor related to improving the accuracy of the quadrupolar coupling calculations, and that functionals beyond the generalized gradient approximation (GGA) level, such as hybrid and meta-GGA functionals, are required for good correlations with experiment. The influence of molecular dynamics and NQEs is less important than the functional choice in the studied systems. A method which involves scaling the calculated quadrupolar coupling constant is proposed here; its application leads to good agreement with experimental data.

Hydrogen Atomic Positions of O-H···O Hydrogen Bonds in Solution and in the Solid State: The Synergy of Quantum Chemical Calculations with ¹H-NMR Chemical Shifts and X-ray Diffraction Methods

The exact knowledge of hydrogen atomic positions of O-H···O hydrogen bonds in solution and in the solid state has been a major challenge in structural and physical organic chemistry. The objective of this review article is to summarize recent developments in the refinement of labile hydrogen positions with the use of: (i) density functional theory (DFT) calculations after a structure has been determined by X-ray from single crystals or from powders; (ii) ¹H-NMR chemical shifts as constraints in DFT calculations, and (iii) use of root-mean-square deviation between experimentally determined and DFT calculated ¹H-NMR chemical shifts considering the great sensitivity of ¹H-NMR shielding to hydrogen bonding properties.

The application of tailor-made force fields and molecular dynamics for NMR crystallography: a case study of free base cocaine

Motional averaging has been proven to be significant in predicting the chemical shifts in ab initio solid-state NMR calculations, and the applicability of motional averaging with molecular dynamics has been shown to depend on the accuracy of the molecular mechanical force field. The performance of a fully automatically generated tailor-made force field (TMFF) for the dynamic aspects of NMR crystallography is evaluated and compared with existing benchmarks, including static dispersion-corrected density functional theory calculations and the COMPASS force field. The crystal structure of free base cocaine is used as an example. The results reveal that, even though the TMFF outperforms the COMPASS force field for representing the energies and conformations of predicted structures, it does not give significant improvement in the accuracy of NMR calculations. Further studies should direct more attention to anisotropic chemical shifts and development of the method of solid-state NMR calculations.

Structure and physicochemical characterization of a naproxen-picolinamide cocrystal

Naproxen (NPX) is a nonsteroidal anti-inflammatory drug with pain- and fever-relieving properties, currently marketed in the sodium salt form to overcome solubility problems; however, alternative solutions for improving its solubility across all pH values are desirable. NPX is suitable for cocrystal formation, with hydrogen-bonding possibilities via the COOH group. The crystal structure is presented of a 1:1 cocrystal of NPX with picolinamide as a coformer [systematic name: (S)-2-(6-methoxynaphthalen-2-yl)propanoic acid-pyridine-2-carboxamide (1/1), C14H14O3·C6H6N2O]. The pharmaceutically relevant physical properties were investigated and the intrinsic dissolution rate was found to be essentially the same as that of commercial naproxen. An NMR crystallography approach was used to investigate the H-atom positions in the two crystallographically unique COOH-CONH hydrogen-bonded dimers. 1H solid-state NMR distinguished the two carboxyl protons, despite the very similar crystallographic environments. The nature of the hydrogen bonding was confirmed by solid-state NMR and density functional theory calculations.

13C and 19F solid-state NMR and X-ray crystallographic study of halogen-bonded frameworks featuring nitrogen-containing heterocycles

Halogen bonding is a noncovalent interaction between the electrophilic region of a halogen (σ-hole) and an electron donor. We report a crystallographic and structural analysis of halogen-bonded compounds by applying a combined X-ray diffraction (XRD) and solid-state nuclear magnetic resonance (SSNMR) approach. Single-crystal XRD was first used to characterize the halogen-bonded cocrystals formed between two fluorinated halogen-bond donors (1,4-diiodotetrafluorobenzene and 1,3,5-trifluoro-2,4,6-triiodobenzene) and several nitrogen-containing heterocycles (acridine, 1,10-phenanthroline, 2,3,5,6-tetramethylpyrazine, and hexamethylenetetramine). New structures are reported for the following three cocrystals, all in the P2₁/c space group: acridine-1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C₆F₃I₃·C₁₃H₉N, 1,10-phenanthroline-1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C₆F₃I₃·C₁₂H₈N₂, and 2,3,5,6-tetramethylpyrazine-1,3,5-trifluoro-2,4,6-triiodobenzene (1/1), C₆F₃I₃·C₈H₁₂N₂. ¹³C and ¹⁹F solid-state magic-angle spinning (MAS) NMR is shown to be a convenient method to characterize the structural features of the halogen-bond donor and acceptor, with chemical shifts attributable to cocrystal formation observed in the spectra of both nuclides. Cross polarization (CP) from ¹⁹F to ¹³C results in improved spectral sensitivity in characterizing the perfluorinated halogen-bond donor when compared to conventional ¹H CP. Gauge-including projector-augmented wave density functional theory (GIPAW DFT) calculations of magnetic shielding constants, along with optimization of the XRD structures, provide a final set of structures in best agreement with the experimental ¹³C and ¹⁹F chemical shifts. Data for carbons bonded to iodine remain outliers due to well-known relativistic effects.

Determining carbon-carbon connectivities in natural abundance organic powders using dipolar couplings

We present a solid-state NMR methodology capable of investigating the carbon skeleton of natural abundance organic powders. The methodology is based on the (13)C-(13)C dipolar coupling interaction and allows carbon-carbon connectivities to be unambiguously established for a wide range of organic solids. This methodology is particularly suitable for disordered solids, such as natural or synthetic macromolecules, which cannot be studied using conventional diffraction or NMR techniques.