A Prolific Solvate Former, Galunisertib, under the Pressure of Crystal Structure Prediction, Produces Ten Diverse Polymorphs

Structural insight into piezo-solvatochromism of Reichardt's dye

To date, accurate modelling of the solvation process is challenging, often over-simplifying the solvent-solute interactions. The interplay between the molecular arrangement associated with the solvation process and crystal nucleation has been investigated by analysis of the piezo-solvatochromic behaviour of Reichardt's dye, ET(1), in methanol, ethanol and acetone under high pressure. High-pressure single-crystal X-ray diffraction and UV-Vis spectroscopy reveal the impact of solute-solvent interactions on the optical properties of ET(1). The study underscores the intricate relationship between solvent properties, molecular conformation and crystal packing. The connection between liquid and solid phases emphasizes the capabilities of high-pressure methods for expanding the field of crystal engineering. The high-pressure environment allowed the determination of the crystal structures reported here that are built from organic molecules fourfold solvated with ethanol or methanol: ET(1)·4CH3OH and ET(1)·4C2H5OH·H2O. The observed piezo-solvatochromic effects highlight the potential of ET(1) in nonlinear optoelectronics and expand the application of solvatochromic chemical indicators to pressure sensors.

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.

Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials

The reliability of organic molecular crystal structure prediction has improved tremendously in recent years. Crystal structure predictions for small, mostly rigid molecules are quickly becoming routine. Structure predictions for larger, highly flexible molecules are more challenging, but their crystal structures can also now be predicted with increasing rates of success. These advances are ushering in a new era where crystal structure prediction drives the experimental discovery of new solid forms. After briefly discussing the computational methods that enable successful crystal structure prediction, this perspective presents case studies from the literature that demonstrate how state-of-the-art crystal structure prediction can transform how scientists approach problems involving the organic solid state. Applications to pharmaceuticals, porous organic materials, photomechanical crystals, organic semi-conductors, and nuclear magnetic resonance crystallography are included. Finally, efforts to improve our understanding of which predicted crystal structures can actually be produced experimentally and other outstanding challenges are discussed.

Application of the FFLUX Force Field to Molecular Crystals: A Study of Formamide

In this work, we present the first application of the quantum chemical topology force field FFLUX to the solid state. FFLUX utilizes Gaussian process regression machine learning models trained on data from the interacting quantum atom partitioning scheme to predict atomic energies and flexible multipole moments that change with geometry. Here, the ambient (α) and high-pressure (β) polymorphs of formamide are used as test systems and optimized using FFLUX. Optimizing the structures with increasing multipolar ranks indicates that the lattice parameters of the α phase differ by less than 5% to the experimental structure when multipole moments up to the quadrupole are used. These differences are found to be in line with the dispersion-corrected density functional theory. Lattice dynamics calculations are also found to be possible using FFLUX, yielding harmonic phonon spectra comparable to dispersion-corrected DFT while enabling larger supercells to be considered than is typically possible with first-principles calculations. These promising results indicate that FFLUX can be used to accurately determine properties of molecular solids that are difficult to access using DFT, including the structural dynamics, free energies, and properties at finite temperature.

Desolvation Processes in Channel Solvates of Niclosamide

The antiparasitic drug niclosamide (NCL) is notable for its ability to crystallize in multiple 1:1 channel solvate forms, none of which are isostructural. Here, using a combination of time-resolved synchrotron powder X-ray diffraction and thermogravimetry, the process-induced desolvation mechanisms of methanol and acetonitrile solvates are investigated. Structural changes in both solvates follow a complicated molecular-level trajectory characterized by a sudden shift in lattice parameters several degrees below the temperature where the desolvated phase first appears. Model fitting of kinetic data obtained under isothermal heating conditions suggests that the desolvation is rate-limited by the nucleation of the solvent-free product. The desolvation pathways identified in these systems stand in contrast to previous investigations of the NCL channel hydrate, where water loss by diffusion initially yields an anhydrous isomorph that converts to the thermodynamic polymorph at significantly higher temperatures. Taking the view that each solvate lattice is a unique "pre-organized" precursor, a comparison of the pathways from different starting topologies to the same final product provides the opportunity to reevaluate assumptions of how various factors (e.g., solvent binding strength, density) influence solid-state desolvation processes.

Predicting crystal form stability under real-world conditions

The physicochemical properties of molecular crystals, such as solubility, stability, compactability, melting behaviour and bioavailability, depend on their crystal form1. In silico crystal form selection has recently come much closer to realization because of the development of accurate and affordable free-energy calculations2-4. Here we redefine the state of the art, primarily by improving the accuracy of free-energy calculations, constructing a reliable experimental benchmark for solid-solid free-energy differences, quantifying statistical errors for the computed free energies and placing both hydrate crystal structures of different stoichiometries and anhydrate crystal structures on the same energy landscape, with defined error bars, as a function of temperature and relative humidity. The calculated free energies have standard errors of 1-2 kJ mol-1 for industrially relevant compounds, and the method to place crystal structures with different hydrate stoichiometries on the same energy landscape can be extended to other multi-component systems, including solvates. These contributions reduce the gap between the needs of the experimentalist and the capabilities of modern computational tools, transforming crystal structure prediction into a more reliable and actionable procedure that can be used in combination with experimental evidence to direct crystal form selection and establish control5.

Solvent-induced polymorphism in dipodal N-donor ligands containing a biphenyl core

Polymorph screenings for two related dipodal N-donor ligands containing a biphenyl core, namely 4,4'-bis(pyridin-4-ylmethyl)-1,1'-biphenyl (1) and 4,4'-bis(1H-imidazol-1-ylmethyl)-1,1'-biphenyl (2) were performed, and the new phases were isolated and their crystal structures analysed. Profiling included methods such as PXRD and thermal analysis. Hirshfeld surface analyses, as well as crystal lattice energy calculations provided deeper insight in the interplay of the intermolecular forces and the stability of the isolated phases. Furthermore, our studies revealed the presence of solvent-induced polymorphism, whereby the metastable phase is dominant upon crystallisation from THF (1a) and EtOH (2c). Upon heating, these phases transform into a more stable form, whereby the transformations were followed by PXRD studies (1, 2).

Pushing Technique Boundaries to Probe Conformational Polymorphism

We present an extensive exploration of the solid-form landscape of chlorpropamide (CPA) using a combined experimental-computational approach at the frontiers of both fields. We have obtained new conformational polymorphs of CPA, placing them into context with known forms using flexible-molecule crystal structure prediction. We highlight the formation of a new polymorph (ζ-CPA) via spray-drying experiments despite its notable metastability (14 kJ/mol) relative to the thermodynamic α-form, and we identify and resolve the ball-milled η-form isolated in 2019. Additionally, we employ impurity- and gel-assisted crystallization to control polymorphism and the formation of novel multicomponent forms. We, thus, demonstrate the power of this collaborative screening approach to observe, rationalize, and control the formation of new metastable forms.

Review of Applications of Density Functional Theory (DFT) Quantum Mechanical Calculations to Study the High-Pressure Polymorphs of Organic Crystalline Materials

Since its inception, chemistry has been predominated by the use of temperature to generate or change materials, but applications of pressure of more than a few tens of atmospheres for such purposes have been rarely observed. However, pressure is a very effective thermodynamic variable that is increasingly used to generate new materials or alter the properties of existing ones. As computational approaches designed to simulate the solid state are normally tuned using structural data at ambient pressure, applying them to high-pressure issues is a highly challenging test of their validity from a computational standpoint. However, the use of quantum chemical calculations, typically at the level of density functional theory (DFT), has repeatedly been shown to be a great tool that can be used to both predict properties that can be later confirmed by experimenters and to explain, at the molecular level, the observations of high-pressure experiments. This article's main goal is to compile, analyze, and synthesize the findings of works addressing the use of DFT in the context of molecular crystals subjected to high-pressure conditions in order to give a general overview of the possibilities offered by these state-of-the-art calculations.

Dehydration of Niclosamide Monohydrate Polymorphs: Different Mechanistic Pathways to the Same Product

Many active pharmaceutical ingredients (APIs) can crystallize as hydrates or anhydrates, the relative stability of which depends on their internal structures as well as the external environment. Hydrates may dehydrate unexpectedly or intentionally, though the molecular-level mechanisms by which such transformations occur are difficult to predict a priori. Niclosamide is an anthelmintic drug on the World Health Organization's "List of Essential Medicines" that crystallizes in two monohydrate forms: HA and HB. Through complementary time-resolved synchrotron powder X-ray diffraction and thermogravimetric kinetic studies, we demonstrate that the two monohydrates dehydrate via distinctly different solid state pathways yet yield the same final anhydrate phase. Water loss from HA via diffusion yields an isomorphous desolvate intermediate which can rearrange to at least two different polymorphs, only one of which exhibits long-term stability. In contrast, dehydration of HB proceeds via a surface nucleation process where simultaneous water loss and product formation occur with no detectable crystalline intermediates. Comparative analysis of the two systems serves to highlight the complex relationship between lattice structure and solid state dehydration processes.

Reducing overprediction of molecular crystal structures via threshold clustering

Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction.

Discriminating and understanding molecular crystal polymorphism

Polymorph discrimination for a molecular crystal has long been a challenging task, which, nonetheless, is a major concern in the pharmaceutical industry. In this work, we have investigated polymorph discrimination on three different molecular crystals, tetrolic acid, oxalic acid, and oxalyl dihydrazide, covering both packing polymorphism and conformational polymorphism. To gain more understanding, we have performed energy decomposition analysis based on many-body expansion, and have compared the results from the XO-PBC method, that is, the eXtended ONIOM method (XO) with the periodic boundary condition (PBC), with those from some commonly used dispersion corrected density functional theory (DFT-D) methods. It is shown here that, with the XYG3 doubly hybrid functional chosen as the target high level to capture the intra- and short-range intermolecular interactions, and the periodic PBE as the basic low level to take long range interactions into account, the XO-PBC(XYG3:PBE) method not only obtains the correct experimental stability orderings, but also predicts reasonable polymorph energy ranges for all three cases. Our results have demonstrated the usefulness of the present theoretical methods, in particular XO-PBC, while highlighted the importance of a better treatment of different kinds of interactions to be beneficial to polymorph control.

Halogen bond and polymorphism in trans-bis(2-iodo-5-halopyridine)dihalocopper(ii) complexes: crystallographic, theoretical and magnetic studies

As the halogen atom on position 5 of the 2I5YP ligand gets heavier the probability of crystallizing the syn-conformer increases; 2I5Cl-Cl crystallizes as the anti-conformer whereas 2I5Br-Cl crystallizes as syn- and anti-conformers.

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.

Minimal Basis Set Hartree-Fock Corrected with Atom-Centered Potentials for Molecular Crystal Modeling and Crystal Structure Prediction

Crystal structure prediction (CSP), determining the experimentally observable structure of a molecular crystal from the molecular diagram, is an important challenge with technologically relevant applications in materials manufacturing and drug design. For the purpose of screening the randomly generated candidate crystal structures, CSP protocols require energy ranking methods that are fast and can accurately capture the small energy differences between molecular crystals. In addition, a good ranking method should also produce accurate equilibrium geometries, both intramolecular and intermolecular. In this article, we explore the combination of minimal-basis-set Hartree-Fock (HF) with atom-centered potentials (ACPs) as a method for modeling the structure and energetics of molecular crystals. The ACPs are developed for the H, C, N, and O atoms and fitted to a set of reference data at the B86bPBE-XDM level in order to mitigate basis-set incompleteness and missing correlation. In particular, ACPs are developed in combination with two methods: HF-D3/MINIs and HF-3c. The application of ACPs greatly improves the performance of HF-D3/MINIs for lattice energies, crystal energy differences, energy-volume and energy-strain relations, and crystal geometries. In the case of HF-3c, the improvement in the crystal energy differences is much smaller than in HF-D3/MINIs, but lattice energies and particularly crystal geometries are considerably better when ACPs are used. The resulting methods may be useful for CSP but also for quick calculation of molecular crystal lattice energies and geometries.

Efficient Crystal Structure Prediction for Structurally Related Molecules with Accurate and Transferable Tailor-Made Force Fields

Crystal structure prediction (CSP) his generally used to complement experimental solid form screening and applied to individual molecules in drug development. The fast development of algorithms and computing resources offers the opportunity to use CSP earlier and for a broader range of applications in the drug design cycle. This study presents a novel paradigm of CSP specifically designed for structurally related molecules, referred to as Quick-CSP. The approach prioritizes more accurate physics through robust and transferable tailor-made force fields (TMFFs), such that significant efficiency gains are achieved through the reduction of expensive ab initio calculations. The accuracy of the TMFF is increased by the introduction of electrostatic multipoles, and the fragment-based force field parameterization scheme is demonstrated to be transferable for a family of chemically related molecules. The protocol is benchmarked with structurally related compounds from the Bromodomain and Extraterminal (BET) domain inhibitors series. A new convergence criterion is introduced that aims at performing only as many ab initio optimizations of crystal structures as required to locate the bottom of the crystal energy landscape within a user-defined accuracy. The overall approach provides significant cost savings ranging from three- to eight-fold less than the full-CSP workflow. The reported advancements expand the scope and utility of the underlying CSP building blocks as well as their novel reassembly to other applications earlier in the drug design cycle to guide molecule design and selection.

Global analysis of the energy landscapes of molecular crystal structures by applying the threshold algorithm

Polymorphism in molecular crystals has important consequences for the control of materials properties and our understanding of crystallization. Computational methods, including crystal structure prediction, have provided important insight into polymorphism, but have usually been limited to assessing the relative energies of structures. We describe the implementation of the Monte Carlo threshold algorithm as a method to provide an estimate of the energy barriers separating crystal structures. By sampling the local energy minima accessible from multiple starting structures, the simulations yield a global picture of the crystal energy landscapes and provide valuable information on the depth of the energy minima associated with crystal structures. We present results from applying the threshold algorithm to four polymorphic organic molecular crystals, examine the influence of applying space group symmetry constraints during the simulations, and discuss the relationship between the structure of the energy landscape and the intermolecular interactions present in the crystals.

Ambiguous structure determination from powder data: four different structural models of 4,11-di-fluoro-quinacridone with similar X-ray powder patterns, fit to the PDF, SSNMR and DFT-D

Four different structural models, which all fit the same X-ray powder pattern, were obtained in the structure determination of 4,11-di-fluoro-quinacridone (C₂₀H₁₀N₂O₂F₂) from unindexed X-ray powder data by a global fit. The models differ in their lattice parameters, space groups, Z, Z', molecular packing and hydrogen bond patterns. The molecules form a criss-cross pattern in models A and B, a layer structure built from chains in model C and a criss-cross arrangement of dimers in model D. Nevertheless, all models give a good Rietveld fit to the experimental powder pattern with acceptable R-values. All molecular geometries are reliable, except for model D, which is slightly distorted. All structures are crystallochemically plausible, concerning density, hydrogen bonds, intermolecular distances etc. All models passed the checkCIF test without major problems; only in model A a missed symmetry was detected. All structures could have probably been published, although 3 of the 4 structures were wrong. The investigation, which of the four structures is actually the correct one, was challenging. Six methods were used: (1) Rietveld refinements, (2) fit of the crystal structures to the pair distribution function (PDF) including the refinement of lattice parameters and atomic coordinates, (3) evaluation of the colour, (4) lattice-energy minimizations with force fields, (5) lattice-energy minimizations by two dispersion-corrected density functional theory methods, and (6) multinuclear CPMAS solid-state NMR spectroscopy (¹H, ¹³C, ¹⁹F) including the comparison of calculated and experimental chemical shifts. All in all, model B (perhaps with some disorder) can probably be considered to be the correct one. This work shows that a structure determination from limited-quality powder data may result in totally different structural models, which all may be correct or wrong, even if they are chemically sensible and give a good Rietveld refinement. Additionally, the work is an excellent example that the refinement of an organic crystal structure can be successfully performed by a fit to the PDF, and the combination of computed and experimental solid-state NMR chemical shifts can provide further information for the selection of the most reliable structure among several possibilities.

Crystal Engineering of Pharmaceutical Cocrystals in the Discovery and Development of Improved Drugs

The subject of crystal engineering started in the 1970s with the study of topochemical reactions in the solid state. A broad chemical definition of crystal engineering was published in 1989, and the supramolecular synthon concept was proposed in 1995 followed by heterosynthons and their potential applications for the design of pharmaceutical cocrystals in 2004. This review traces the development of supramolecular synthons as robust and recurring hydrogen bond patterns for the design and construction of supramolecular architectures, notably, pharmaceutical cocrystals beginning in the early 2000s to the present time. The ability of a cocrystal between an active pharmaceutical ingredient (API) and a pharmaceutically acceptable coformer to systematically tune the physicochemical properties of a drug (i.e., solubility, permeability, hydration, color, compaction, tableting, bioavailability) without changing its molecular structure is the hallmark of the pharmaceutical cocrystals platform, as a bridge between drug discovery and pharmaceutical development. With the design of cocrystals via heterosynthons and prototype case studies to improve drug solubility in place (2000-2015), the period between 2015 to the present time has witnessed the launch of several salt-cocrystal drugs with improved efficacy and high bioavailability. This review on the design, synthesis, and applications of pharmaceutical cocrystals to afford improved drug products and drug substances will interest researchers in crystal engineering, supramolecular chemistry, medicinal chemistry, process development, and pharmaceutical and materials sciences. The scale-up of drug cocrystals and salts using continuous manufacturing technologies provides high-value pharmaceuticals with economic and environmental benefits.

The interplay of intra- and intermolecular errors in modeling conformational polymorphs

Conformational polymorphs of organic molecular crystals represent a challenging test for quantum chemistry because they require careful balancing of the intra- and intermolecular interactions. This study examines 54 molecular conformations from 20 sets of conformational polymorphs, along with the relative lattice energies and 173 dimer interactions taken from six of the polymorph sets. These systems are studied with a variety of van der Waals-inclusive density functionals theory models; dispersion-corrected spin-component-scaled second-order Møller–Plesset perturbation theory (SCS-MP2D); and domain local pair natural orbital coupled cluster singles, doubles, and perturbative triples [DLPNO-CCSD(T)]. We investigate how delocalization error in conventional density functionals impacts monomer conformational energies, systematic errors in the intermolecular interactions, and the nature of error cancellation that occurs in the overall crystal. The density functionals B86bPBE-XDM, PBE-D4, PBE-MBD, PBE0-D4, and PBE0-MBD are found to exhibit sizable one-body and two-body errors vs DLPNO-CCSD(T) benchmarks, and the level of success in predicting the relative polymorph energies relies heavily on error cancellation between different types of intermolecular interactions or between intra- and intermolecular interactions. The SCS-MP2D and, to a lesser extent, ωB97M-V models exhibit smaller errors and rely less on error cancellation. Implications for crystal structure prediction of flexible compounds are discussed. Finally, the one-body and two-body DLPNO-CCSD(T) energies taken from these conformational polymorphs establish the CP1b and CP2b benchmark datasets that could be useful for testing quantum chemistry models in challenging real-world systems with complex interplay between intra- and intermolecular interactions, a number of which are significantly impacted by delocalization error.

Emerging Landscape of Computational Modeling in Pharmaceutical Development

Computational chemistry applications have become an integral part of the drug discovery workflow over the past 35 years. However, computational modeling in support of drug development has remained a relatively uncharted territory for a significant part of both academic and industrial communities. This review considers the computational modeling workflows for three key components of drug preclinical and clinical development, namely, process chemistry, analytical research and development, as well as drug product and formulation development. An overview of the computational support for each step of the respective workflows is presented. Additionally, in context of solid form design, special consideration is given to modern physics-based virtual screening methods. This covers rational approaches to polymorph, coformer, counterion, and solvent virtual screening in support of solid form selection and design.

Selective desolvation in two-step nucleation mechanism steers crystal structure formation

The two-step nucleation (TSN) theory and crystal structure prediction (CSP) techniques are two disjointed yet popular methods to predict nucleation rate and crystal structure, respectively. The TSN theory is a well-established mechanism to describe the nucleation of a wide range of crystalline materials in different solvents. However, it has never been expanded to predict the crystal structure or polymorphism. On the contrary, the existing CSP techniques only empirically account for the solvent effects. As a result, the TSN theory and CSP techniques continue to evolve as separate methods to predict two essential attributes of nucleation - rate and structure. Here we bridge this gap and show for the first time how a crystal structure is formed within the framework of TSN theory. A sequential desolvation mechanism is proposed in TSN, where the first step involves partial desolvation to form dense clusters followed by selective desolvation of functional groups directing the formation of crystal structure. We investigate the effect of the specific interaction on the degree of solvation around different functional groups of glutamic acid molecules using molecular simulations. The simulated energy landscape and activation barriers at increasing supersaturations suggest sequential and selective desolvation. We validate computationally and experimentally that the crystal structure formation and polymorph selection are due to a previously unrecognized consequence of supersaturation-driven asymmetric desolvation of molecules.

Directing Crystallization Outcomes of Conformationally Flexible Molecules: Polymorphs, Solvates, and Desolvation Pathways of Fluconazole

Control over polymorphism and solvatomorphism in API assisted by structural information, e.g., molecular conformation or associations via hydrogen bonds, is crucial for the industrial development of new drugs, as the crystallization products differ in solubility, dissolution profile, compressibility, or melting temperature. The stability of the final formulation and technological factors of the pharmaceutical powders further emphasize the importance of precise crystallization protocols. This is particularly important when working with highly flexible molecules with considerable conformational freedom and a large number of hydrogen bond donors or acceptors (e.g., fluconazole, FLU). Here, cooling and suspension crystallization were applied to access polymorphs and solvates of FLU, a widely used azole antifungal agent with high molecular flexibility and several reported polymorphs. Each of four polymorphic forms, FLU I, II, III, or IV, can be obtained from the same set of alcohols (MeOH, EtOH, isPrOH) and DMF via careful control of the crystallization conditions. For the first time, two types of isostructural channel solvates of FLU were obtained (nine new structures). Type I solvates were prepared by cooling crystallization in Tol, ACN, DMSO, BuOH, and BuON. Type II solvates formed in DCM, ACN, nPrOH, and BuOH during suspension experiments. We propose desolvation pathways for both types of solvates based on the structural analysis of the newly obtained solvates and their desolvation products. Type I solvates desolvate to FLU form I by hydrogen-bonded chain rearrangements. Type II solvates desolvation leads first to an isomorphic desolvate, followed by a phase transition to FLU form II through hydrogen-bonded dimer rearrangement. Combining solvent-mediated phase transformations with structural analysis and solid-state NMR, supported by periodic electronic structure calculations, allowed us to elucidate the interrelations and transformation pathways of FLU.

Progress in understanding crystallisation: a personal perspective

After this discussion meeting, most participants felt that we do not understand crystallisation. However, in the 1980s I believe that most scientists would have considered that crystallisation was adequately understood....

Polymorphism and isomorphism in trans-bis(2,5-diiodopyridine)dihalocopper(ii) complexes: theoretical and crystallographic studies

Two conformational polymorphs of [Cu(25dIpy)2Cl2] have been prepared, the anti-polymorph crystallized from 2-propanol at room temperature (green) and the syn-polymorph crystallized from acetonitrile at 60 °C (brown).

Along the road to Crystal Structure Prediction (CSP) of pharmaceutical-like molecules

Computational methods used for predicting crystal structures of organic compounds are mature enough to be routinely used with many rigid and semi-rigid organic molecules. The usefulness of Crystal Structure Prediction...

How many more polymorphs of ROY remain undiscovered

With 12 crystal forms, 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecabonitrile (a.k.a. ROY) holds the current record for the largest number of fully characterized organic crystal polymorphs. Four of these polymorph structures have been reported since 2019, raising the question of how many more ROY polymorphs await future discovery. Employing crystal structure prediction and accurate energy rankings derived from conformational energy-corrected density functional theory, this study presents the first crystal energy landscape for ROY that agrees well with experiment. The lattice energies suggest that the seven most stable ROY polymorphs (and nine of the twelve lowest-energy forms) on the Z′ = 1 landscape have already been discovered experimentally. Discovering any new polymorphs at ambient pressure will likely require specialized crystallization techniques capable of trapping metastable forms. At pressures above 10 GPa, however, a new crystal form is predicted to become enthalpically more stable than all known polymorphs, suggesting that further high-pressure experiments on ROY may be warranted. This work highlights the value of high-accuracy crystal structure prediction for solid-form screening and demonstrates how pragmatic conformational energy corrections can overcome the limitations of conventional density functionals for conformational polymorphs.

Crystal structure prediction suggests that the low-energy polymorphs of ROY have already been found, but a new high-pressure form is predicted.

Implications of the Conformationally Flexible, Macrocyclic Structure of the First-Generation, Direct-Acting Anti-Viral Paritaprevir on Its Solid Form Complexity and Chameleonic Behavior

Direct-acting antiviral regimens have transformed therapeutic management of hepatitis C across all prevalent genotypes. Most of the chemical matter in these regimens comprises molecules well outside the traditional drug development chemical space and presents significant challenges. Herein, the implications of high conformational flexibility and the presence of a 15-membered macrocyclic ring in paritaprevir are studied through a combination of advanced computational and experimental methods with focus on molecular chameleonicity and crystal form complexity. The ability of the molecule to toggle between high and low 3D polar surface area (PSA) conformations is underpinned by intramolecular hydrogen bonding (IMHB) interactions and intramolecular steric effects. Computational studies consequently show a very significant difference of over 75 Ų in 3D PSA between polar and apolar environments and provide the structural basis for the perplexingly favorable passive permeability of the molecule. Crystal packing and protein binding resulting in strong intermolecular interactions disrupt these intramolecular interactions. Crystalline Form I benefits from strong intermolecular interactions, whereas the weaker intermolecular interactions in Form II are partially compensated by the energetic advantage of an IMHB. Like Form I, no IMHB is observed within the receptor-bound conformation; instead, an intermolecular H-bond contributes to the potency of the molecule. The choice of metastable Form II is derisked through strategies accounting for crystal surface and packing features to manage higher form specific solid-state chemical reactivity and specific processing requirements. Overall, the results show an unambiguous link between structural features and derived properties from crystallization to dissolution, permeation, and docking into the protein pocket.

SERS Quantification of Galunisertib Delivery in Colorectal Cancer Cells by Plasmonic-Assisted Diatomite Nanoparticles

The small molecule Galunisertib (LY2157299, LY) shows multiple anticancer activities blocking the transforming growth factor-β1 receptor, responsible for the epithelial-to-mesenchymal transition (EMT) by which colorectal cancer (CRC) cells acquire migratory and metastatic capacities. However, frequent dosing of LY can produce highly toxic metabolites. Alternative strategies to reduce drug side effects can rely on nanoscale drug delivery systems that have led to a medical revolution in the treatment of cancer, improving drug efficacy and lowering drug toxicity. Here, a hybrid nanosystem (DNP-AuNPs-LY@Gel) made of a porous diatomite nanoparticle decorated with plasmonic gold nanoparticles, in which LY is retained by a gelatin shell, is proposed. The multifunctional capability of the nanosystem is demonstrated by investigating the efficient LY delivery, the enhanced EMT reversion in CRCs and the intracellular quantification of drug release with a sub-femtogram resolution by surface-enhanced Raman spectroscopy (SERS). The LY release trigger is the pH sensitivity of the gelatin shell to the CRC acidic microenvironment. The drug release is real-time monitored at single-cell level by analyzing the SERS signals of LY in CRC cells. The higher efficiency of LY delivered by the DNP-AuNPs-LY@Gel complex paves the way to an alternative strategy for lowering drug dosing and consequent side effects.

Toward Physics-Based Solubility Computation for Pharmaceuticals to Rival Informatics

We demonstrate that physics-based calculations of intrinsic aqueous solubility can rival cheminformatics-based machine learning predictions. A proof-of-concept was developed for a physics-based approach via a sublimation thermodynamic cycle, building upon previous work that relied upon several thermodynamic approximations, notably the 2RT approximation, and limited conformational sampling. Here, we apply improvements to our sublimation free-energy model with the use of crystal phonon mode calculations to capture the contributions of the vibrational modes of the crystal. Including these improvements with lattice energies computed using the model-potential-based Ψ_mol method leads to accurate estimates of sublimation free energy. Combining these with hydration free energies obtained from either molecular dynamics free-energy perturbation simulations or density functional theory calculations, solubilities comparable to both experiment and informatics predictions are obtained. The application to coronene, succinic acid, and the pharmaceutical desloratadine shows how the methods must be adapted for the adoption of different conformations in different phases. The approach has the flexibility to extend to applications that cannot be covered by informatics methods.

Modeling the α- and β-resorcinol phase boundary via combination of density functional theory and density functional tight-binding

The ability to predict not only what organic crystal structures might occur but also the thermodynamic conditions under which they are the most stable would be extremely useful for discovering and designing new organic materials. The present study takes a step in that direction by predicting the temperature- and pressure-dependent phase boundary between the α and β polymorphs of resorcinol using density functional theory (DFT) and the quasi-harmonic approximation. To circumvent the major computational bottleneck associated with computing a well-converged phonon density of states via the supercell approach, a recently developed approximation is employed, which combines a supercell phonon density of states from dispersion-corrected third-order density functional tight binding [DFTB3-D3(BJ)] with frequency corrections derived from a smaller B86bPBE-XDM functional DFT phonon calculation on the crystallographic unit cell. This mixed DFT/DFTB quasi-harmonic approach predicts the lattice constants and unit cell volumes to within 1%-2% at lower pressures. It predicts the thermodynamic phase boundary in almost perfect agreement with the experiment, although this excellent agreement does reflect fortuitous cancellation of errors between the enthalpy and entropy of transition.

Novel Physics-Based Ensemble Modeling Approach That Utilizes 3D Molecular Conformation and Packing to Access Aqueous Thermodynamic Solubility: A Case Study of Orally Available Bromodomain and Extraterminal Domain Inhibitor Lead Optimization Series

Drug design with patient centricity for ease of administration and pill burden requires robust understanding of the impact of chemical modifications on relevant physicochemical properties early in lead optimization. To this end, we have developed a physics-based ensemble approach to predict aqueous thermodynamic crystalline solubility, with a 2D chemical structure as the input. Predictions for the bromodomain and extraterminal domain (BET) inhibitor series show very close match (0.5 log unit) with measured thermodynamic solubility for cases with low crystal anisotropy and good match (1 log unit) for high anisotropy structures. The importance of thermodynamic solubility is clearly demonstrated by up to a 4 log unit drop in solubility compared to kinetic (amorphous) solubility in some cases and implications thereof, for instance on human dose. We have also demonstrated that incorporating predicted crystal structures in thermodynamic solubility prediction is necessary to differentiate (up to 4 log unit) between solubility of molecules within the series. Finally, our physics-based ensemble approach provides valuable structural insights into the origins of 3-D conformational landscapes, crystal polymorphism, and anisotropy that can be leveraged for both drug design and development.

Exploration and Optimization in Crystal Structure Prediction: Combining Basin Hopping with Quasi-Random Sampling

We describe the implementation of a Monte Carlo basin hopping (BH) global optimization procedure for the prediction of molecular crystal structures. The BH method is combined with quasi-random (QR) structure generation in a hybrid method for crystal structure prediction, QR-BH, which combines the low-discrepancy sampling provided by QR sequences with BH efficiency at locating low energy structures. Through tests on a set of single-component molecular crystals and co-crystals, we demonstrate that QR-BH provides faster location of low energy structures than pure QR sampling, while maintaining the efficient location of higher energy structures that are important for identifying important polymorphs.

The unexpected discovery of the ninth polymorph of tolfenamic acid

A new polymorph of tolfenamic acid, form IX, has been crystallised from a simple cooling crystallisation experiment raising the question as to why this polymorph had never been reported before.

Advancing the use of Voronoi–Dirichlet polyhedra to describe interactions in organic molecular crystal structures by the example of galunisertib polymorphs

The universal approach for studying structure/properties relationships shows that every polymorph of galunisertib is characterized with unique noncovalent interactions.

Crystal structure prediction of energetic materials and a twisted arene with Genarris and GAtor

A molecular crystal structure prediction workflow, based on the random structure generator, Genarris, and the genetic algorithm (GA), GAtor, is successfully applied to two energetic materials and a chiral arene.

Improved quantitative crystal-structure comparison using powder diffractograms via anisotropic volume correction

A new anisotropic volume correction improves quantitative crystal structure comparison. Benchmarking against the 6th crystal structure prediction blind test data results in identification of two previously uncredited matching structures.

Features of the conformation of galunisertib molecules in the crystal structures of its solvates

A comparison of galunisertib in crystal structures of pure polymorphs and solvates enables studying the effects of solvate molecules on galunisertib conformations and highlights the features of realized noncovalent interactions.

Organic solvates in the Cambridge Structural Database

Data informatics methods applied to the Cambridge Structural Database reveal shifting trends in solvate formation and inherent biases in the symmetry and packing fraction of solvates and their solvent-free analogues.

Structure prediction of crystals, surfaces and nanoparticles

We review the current techniques used in the prediction of crystal structures and their surfaces and of the structures of nanoparticles. The main classes of search algorithm and energy function are summarized, and we discuss the growing role of methods based on machine learning. We illustrate the current status of the field with examples taken from metallic, inorganic and organic systems. This article is part of a discussion meeting issue 'Dynamic in situ microscopy relating structure and function'.

Rich polymorphism in nicotinamide revealed by melt crystallization and crystal structure prediction

Overprediction is a major limitation of current crystal structure prediction (CSP) methods. It is difficult to determine whether computer-predicted polymorphic structures are artefacts of the calculation model or are polymorphs that have not yet been found. Here, we reported the well-known vitamin nicotinamide (NIC) to be a highly polymorphic compound with nine solved single-crystal structures determined by performing melt crystallization. A CSP calculation successfully identifies all six Z' = 1 and 2 experimental structures, five of which defy 66 years of attempts at being explored using solution crystallization. Our study demonstrates that when combined with our strategy for cultivating single crystals from melt microdroplets, melt crystallization has turned out to be an efficient tool for exploring polymorphic landscapes to better understand polymorphic crystallization and to more effectively test the accuracy of theoretical predictions, especially in regions inaccessible by solution crystallization.

Crystal forms in pharmaceutical applications: olanzapine, a gift to crystal chemistry that keeps on giving

This contribution reviews the efforts of many scientists around the world to discover and structurally characterize olanzapine crystal forms, clearing up inconsistencies in the scientific and patent literature and highlighting the challenges in identifying new forms amidst 60+ known polymorphs and solvates. Owing to its remarkable solid-state chemistry, olanzapine has emerged over the last three decades as a popular tool compound for developing new experimental and computational methods for enhanced molecular level understanding of solid-state structure, form diversity and crystallization outcomes. This article highlights the role of olanzapine in advancing the fundamental understanding of crystal forms, interactions within crystal structures, and growth units in molecular crystallization, as well as influencing the way in which drugs are developed today.

Virtual Coformer Screening by Crystal Structure Predictions: Crucial Role of Crystallinity in Pharmaceutical Cocrystallization

One of the most popular strategies of the optimization of drug properties in the pharmaceutical industry appears to be a solid form changing into a cocrystalline form. A number of virtual screening approaches have been previously developed to allow a selection of the most promising cocrystal formers (coformers) for an experimental follow-up. A significant drawback of those methods is related to the lack of accounting for the crystallinity contribution to cocrystal formation. To address this issue, we propose in this study two virtual coformer screening approaches based on a modern cloud-computing crystal structure prediction (CSP) technology at a dispersion-corrected density functional theory (DFT-D) level. The CSP-based methods were for the first time validated on challenging cases of indomethacin and paracetamol cocrystallization, for which the previously developed approaches provided poor predictions. The calculations demonstrated a dramatic improvement of the virtual coformer screening performance relative to the other methods. It is demonstrated that the crystallinity contribution to the formation of paracetamol and indomethacin cocrystals is a dominant one and, therefore, should not be ignored in the virtual screening calculations. Our results encourage a broad utilization of the proposed CSP-based technology in the pharmaceutical industry as the only virtual coformer screening method that directly accounts for the crystallinity contribution.

Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration

We combine state-of-the-art computational crystal structure prediction (CSP) techniques with a wide range of experimental crystallization methods to understand and explore crystal structure in pharmaceuticals and minimize the risk of unanticipated late-appearing polymorphs. Initially, we demonstrate the power of CSP to rationalize the difficulty in obtaining polymorphs of the well-known pharmaceutical isoniazid and show that CSP provides the structure of the recently obtained, but unsolved, Form III of this drug despite there being only a single resolved form for almost 70 years. More dramatically, our blind CSP study predicts a significant risk of polymorphism for the related iproniazid. Employing a wide variety of experimental techniques, including high-pressure experiments, we experimentally obtained the first three known nonsolvated crystal forms of iproniazid, all of which were successfully predicted in the CSP procedure. We demonstrate the power of CSP methods and free energy calculations to rationalize the observed elusiveness of the third form of iproniazid, the success of high-pressure experiments in obtaining it, and the ability of our synergistic computational-experimental approach to “de-risk” solid form landscapes.

The Eight Hydrates of Strychnine Sulfate

Commercial samples of strychnine sulfate were used as the starting material in crystallization experiments accompanied by stability studies. Eight hydrate forms (HyA-HyG), including five novel hydrates, were verified. The crystal structures of HyA ("pentahydrate") and HyF ("hexahydrate") were determined from single-crystal X-ray diffraction data. HyF was identified as the most stable hydrate at high water activities at room temperature (RT), and HyA and HyC were also found to be stable at ambient conditions. Long-time storage experiments over nearly two decades confirm that these three hydrates are stable at ambient conditions (20-60% relative humidity). The other five hydrates, HyB ("dihydrate"), HyD, HyE, HyG, and HyH, are only observable at the low(est) relative humidity (RH) levels at RT. Some of these latter forms can only exist within a very narrow RH range and are therefore intermediate phases. By applying a range of complementary experimental techniques such as gravimetric moisture sorption analysis, thermal analysis, moisture controlled PXRD measurements, and variable temperature IR spectroscopy in combination with principal component analysis, it was possible to identify the distinct hydrate phases and elucidate their stability and dehydration pathways. The observed (de)hydration routes, HyA ↔ HyB, HyC ↔ HyD ↔ HyE, HyF ↔ HyG ↔ HyH and HyF → HyA ↔ HyB, depended on the initial hydrate form, particle size, and atmospheric conditions. In addition, a transformation from HyC/HyA to HyF occurs at high RH values at RT. The specific moisture and temperature conditions of none of the applied drying regimes yielded a crystalline water-free form, which highlights the essential role of water molecules for the formation and stability of the crystalline strychnine sulfate phases.

Challenging the Ostwald rule of stages in mechanochemical cocrystallisation

Mechanochemistry provides an efficient, but still poorly understood route to synthesize and screen for polymorphs of organic solids. We present a hitherto unexplored effect of the milling assembly on the polymorphic outcome of mechanochemical cocrystallisation, tentatively related to the efficiency of mechanical energy transfer to the milled sample. Previous work on mechanochemical cocrystallisation has established that introducing liquid or polymer additives to milling systems can be used to direct polymorphic behavior, leading to extensive studies how the amount and nature of grinding additive affect reaction outcome and polymorphism. Here, focusing on a model pharmaceutical cocrystal of nicotinamide and adipic acid, we demonstrate that changes to the choice of milling media (i.e. number and material of milling balls) and/or the choice of milling assembly (i.e. jar material) can be used to direct polymorphism of mechanochemical cocrystallisation, enabling the selective synthesis, and even reversible and repeatable interconversion of cocrystal polymorphs. While real-time mechanistic studies of mechanochemical transformations of metal–organic materials have previously suggested that reactions follow a path described by Ostwald's rule of stages, i.e. from metastable to increasingly more stable product structures, the herein presented systematic study presents an exception to that rule, revealing that modification of energy input in the mechanochemical system, combined with a small energy difference between polymorphs, permits the selective synthesis of either the more stable room temperature form, or the new metastable high-temperature form, of the target cocrystal.

The choice of milling assembly (jar and ball material, number and size of balls) can be used to direct polymorphism in mechanochemical cocrystallisation, enabling the selective synthesis, and even reversible interconversion of cocrystal polymorphs.

ROY Reclaims Its Crown: New Ways To Increase Polymorphic Diversity

Chemical compounds that exist in multiple crystalline forms are said to exhibit polymorphism. Polymorphs have the same composition, but their structures and properties can vary markedly. In many fields, conditions for crystallizing compounds of interest are screened exhaustively to generate as many polymorphs as possible, from which the most advantageous form can be selected. We report new ways to search for polymorphs and increase polymorphic diversity, based on crystallization induced by suitably designed mixed-crystal seeds. The potential of the strategy has been demonstrated by using it to produce new polymorphs of the benchmark compound ROY as single crystals structurally characterized by X-ray diffraction. This allows ROY to reclaim its crown as the most polymorphic compound in the Cambridge Structural Database. More generally, the methods promise to become valuable tools for polymorphic screening in all fields where crystalline solids are used.