A molecular picture of the problems in ensuring structural purity of tazofelone

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....

Crystallization of chiral molecular compounds: what can be learned from the Cambridge Structural Database?

A detailed study on chiral compound structures found in the Cambridge Structural Database (CSD) is presented. Solvates, salts and co-crystals have intentionally been excluded, in order to focus on the most basic structures of single enantiomers, scalemates and racemates. Similarity between the latter and structures of achiral monomolecular compounds has been established and utilized to arrive at important conclusions about crystallization of chiral compounds. For example, the fundamental phenomenon of conglomerate formation and, in particular, their frequency of occurrence is addressed. In addition, rarely occurring kryptoracemates and scalemic compounds (anomalous racemates) are discussed. Finally, an extended search of enantiomer solid solutions in the CSD is performed to show that there are up to 1800 instances most probably hiding among the deposited crystal structures, while only a couple of dozen have been previously known and studied.

Mercury 4.0: from visualization to analysis, design and prediction

The program Mercury, developed at the Cambridge Crystallographic Data Centre, was originally designed primarily as a crystal structure visualization tool. Over the years the fields and scientific communities of chemical crystallography and crystal engineering have developed to require more advanced structural analysis software. Mercury has evolved alongside these scientific communities and is now a powerful analysis, design and prediction platform which goes a lot further than simple structure visualization.

Same or different – that is the question: identification of crystal forms from crystal structure data

An analysis of the CSD with structural comparison tools shows that differentiating between polymorphism and redeterminations is not always straight forward and requires of complementary tools at the hands of an expert practitioner.

Experimental and computational approaches to rationalise multicomponent supramolecular assemblies: dapsone monosolvates

The monosolvate crystal energy landscapes of dapsone (DDS) including the solvents carbon tetrachloride, acetone, cyclohexanone, dimethyl formamide, tetrahydrofuran, methyl ethyl ketone, 1,2-dichloroethane, 1,4-dioxane, dichloromethane and chloroform were established using experimental and computational approaches. To rationalise and understand solvate formation, solvate stability and desolvation reactions a careful control of the experimental crystallisation and storage conditions, a range of thermoanalytical methods and crystal structure prediction were required. Six of the eight DDS monosolvates are reported and characterised for the first time. Structural similarity and diversity of the at ambient conditions unstable monosolvates were apparent from the computed crystal energy landscapes, which had the experimental packings as lowest energy structures. The computed structures were used as input for Rietveld refinements and isostructurality of four of the monosolvates was confirmed. Packing comparisons of the solvate structures and molecular properties of the solvent molecules indicated that both size/shape of the solvent molecule and the possible DDSsolvent interactions are the important factors for DDS solvate formation. Through the combination of experiment and theory solvate stability and structural features have been rationalised.

A Million Crystal Structures: The Whole Is Greater than the Sum of Its Parts

The founding in 1965 of what is now called the Cambridge Structural Database (CSD) has reaped dividends in numerous and diverse areas of chemical research. Each of the million or so crystal structures in the database was solved for its own particular reason, but collected together, the structures can be reused to address a multitude of new problems. In this Review, which is focused mainly on the last 10 years, we chronicle the contribution of the CSD to research into molecular geometries, molecular interactions, and molecular assemblies and demonstrate its value in the design of biologically active molecules and the solid forms in which they are delivered. Its potential in other commercially relevant areas is described, including gas storage and delivery, thin films, and (opto)electronics. The CSD also aids the solution of new crystal structures. Because no scientific instrument is without shortcomings, the limitations of CSD research are assessed. We emphasize the importance of maintaining database quality: notwithstanding the arrival of big data and machine learning, it remains perilous to ignore the principle of garbage in, garbage out. Finally, we explain why the CSD must evolve with the world around it to ensure it remains fit for purpose in the years ahead.

Control and prediction of the organic solid state: a challenge to theory and experiment†

The ability of theoretical chemists to quantitatively model the weak forces between organic molecules is being exploited to predict their crystal structures and estimate their physical properties. Evolving crystal structure prediction methods are increasingly being used to aid the design of organic functional materials and provide information about thermodynamically plausible polymorphs of speciality organic materials to aid, for example, pharmaceutical development. However, the increasingly sophisticated experimental studies for detecting the range of organic solid-state behaviours provide many challenges for improving quantitative theories that form the basis for the computer modelling. It is challenging to calculate the relative thermodynamic stability of different organic crystal structures, let alone understand the kinetic effects that determine which polymorphs can be observed and are practically important. However, collaborations between experiment and theory are reaching the stage of devising experiments to target the first crystallization of new polymorphs or create novel organic molecular materials.

Supramolecular Organization of Nonstoichiometric Drug Hydrates: Dapsone

The observed moisture- and temperature dependent transformations of the dapsone (4,4'-diaminodiphenyl sulfone, DDS) 0. 33-hydrate were correlated to its structure and the number and strength of the water-DDS intermolecular interactions. A combination of characterization techniques was used, including thermal analysis (hot-stage microscopy, differential scanning calorimetry and thermogravimetric analysis), gravimetric moisture sorption/desorption studies and variable humidity powder X-ray diffraction, along with computational modeling (crystal structure prediction and pair-wise intermolecular energy calculations). Depending on the relative humidity the hydrate contains between 0 and 0.33 molecules of water per molecule DDS. The crystal structure is retained upon dehydration indicating that DDS hydrate shows a non-stoichiometric (de)hydration behavior. Unexpectedly, the water molecules are not located in structural channels but at isolated-sites of the host framework, which is counterintuitively for a hydrate with non-stoichiometric behavior. The water-DDS interactions were estimated to be weaker than water-host interactions that are commonly observed in stoichiometric hydrates and the lattice energies of the isomorphic dehydration product (hydrate structure without water molecules) and (form III) differ only by ~1 kJ mol-1. The computational generation of hypothetical monohydrates confirms that the hydrate with the unusual DDS:water ratio of 3:1 is more stable than a feasible monohydrate structure. Overall, this study highlights that a deeper understanding of the formation of hydrates with non-stoichiometric behavior requires a multidisciplinary approach including suitable experimental and computational methods providing a firm basis for the development and manufacturing of high quality drug products.

Crystal structure prediction of flexible pharmaceutical-like molecules: density functional tight-binding as an intermediate optimisation method and for free energy estimation

Successful methodologies for theoretical crystal structure prediction (CSP) on flexible pharmaceutical-like organic molecules explore the lattice energy surface to find a set of plausible crystal structures. The initial search stages of CSP studies use relatively simple lattice energy approximations as hundreds of thousands of minima have to be considered. These generated crystal structures often have poor molecular geometries, as well as inaccurate lattice energy rankings, and performing reasonably accurate but computationally affordable optimisations of the crystal structures generated in a search would be highly desirable. Here, we seek to explore whether semi-empirical quantum-mechanical methods can perform this task. We employed the dispersion-corrected tight-binding Hamiltonian (DFTB3-D3) to relax all the inter- and intra-molecular degrees of freedom of several thousands of generated crystal structures of five pharmaceutical-like molecules, saving a large amount of computational effort compared to earlier studies. The computational cost scales better with molecular size and flexibility than other CSP methods, suggesting that it could be extended to even larger and more flexible molecules. On average, this optimisation improved the average reproduction of the eight experimental crystal structures (RMSD15) and experimental conformers (RMSD1) by 4% and 23%, respectively. The intermolecular interactions were then further optimised using distributed multipoles, derived from the molecular wave-functions, to accurately describe the electrostatic components of the intermolecular energies. In all cases, the experimental crystal structures are close to the top of the lattice energy ranking. Phonon calculations on some of the lowest energy structures were also performed with DFTB3-D3 methods to calculate the vibrational component of the Helmholtz free energy, providing further insights into the solid-state behaviour of the target molecules. We conclude that DFTB3-D3 is a cost-effective method for optimising flexible molecules, bridging the gap between the approximate methods used in CSP searches for generating crystal structures and more accurate methods required in the final energy ranking.

Unraveling Complexity in the Solid Form Screening of a Pharmaceutical Salt: Why so Many Forms? Why so Few?

The solid form landscape of 5-HT2a antagonist 3-(4-(benzo[d]isoxazole-3-yl)piperazin-1-yl)-2,2-dimethylpropanoic acid hydrochloride (B5HCl) proved difficult to establish. Many crystalline materials were produced by solid form screening, but few forms readily grew high quality crystals to afford a clear picture or understanding of the solid form landscape. Careful control of crystallization conditions, a range of experimental methods, computational modeling of solvate structures, and crystal structure prediction were required to see potential arrangements of the salt in its crystal forms. Structural diversity in the solid form landscape of B5HCl was apparent in the layer structures for the anhydrate polymorphs (Forms I and II), dihydrate and a family of solvates with alcohols. The alcohol solvates, which provided a distinct packing from the neat forms and the dihydrate, form layers with conserved hydrogen bonding between B5HCl and the solvent, as well as stacking of the aromatic rings. The ability of the alcohol hydrocarbon moieties to efficiently pack between the layers accounted for the difficulty in growing some solvate crystals and the inability of other solvates to crystallize altogether. Through a combination of experiment and computation, the crystallization problems, form stability, and desolvation pathways of B5HCl have been rationalized at a molecular level.

Experimental and Computational Hydrate Screening: Cytosine, 5-Flucytosine and Their Solid Solution

The structural, temperature- and moisture dependent stability features of cytosine and 5-flucytosine monohydrates, two pharmaceutically important compounds, were rationalized using complementary experimental and computational approaches. Moisture sorption/desorption, water activity, thermal analysis and calorimetry were applied to determine the stability ranges of hydrate ↔ anhydrate systems, while X-ray diffraction, IR spectroscopy and crystal structure prediction provided the molecular level understanding. At 25 °C, the critical water activity for the cytosine hydrate ↔ anhydrate system is ~0.43 and for 5-flucytosine ~0.41. In 5-flucytosine the water molecules are arranged in open channels, therefore the kinetic desorption data, dehydration < 40% relative humidity (RH), conform with the thermodynamic data, whereas for the cytosine isolated site hydrate dehydration was observed at RH < 15%. Peritectic dissociation temperatures of the hydrates were measured to be 97 °C and 84.2 °C for cytosine and 5-flucytosine, respectively, and the monohydrate to anhydrate transition enthalpies to be around 10 kJ mol-1. Computed crystal energy landscapes not only revealed that the substitution of C5 (H or F) controls the packing and properties of cytosine/5-flucytosine solid forms, but also have enabled the finding of a monohydrate solid solution of the two substances which shows increased thermal- and moisture-dependent stability compared to 5-flucytosine monohydrate.

Prediction and experimental validation of solid solutions and isopolymorphs of cytosine/5-flucytosine

A computational search for polymorphs of cytosine, 5-flucytosine and a 1 : 1 mixture of the two substances not only rationalised the preferred packing arrangements but also enabled the finding and characterisation of cytosine/5-flucytosine solid solutions. The structures of the new solid forms were determined by combining laboratory powder X-ray diffraction data and computational modelling.

Why do Hydrates (Solvates) Form in Small Neutral Organic Molecules? Exploring the Crystal Form Landscapes of the Alkaloids Brucine and Strychnine

Computational methods were used to generate and explore the crystal structure landscapes of the two alkaloids strychnine and brucine. The computed structures were analyzed and rationalized by correlating the modelling results to a rich pool of available experimental data. Despite their structural similarity, the two compounds show marked differences in the formation of solid forms. For strychnine only one anhydrous form is reported in the literature and two new solvates from 1,4-dioxane were detected in the course of this work. In contrast, 22 solid forms are so far known to exist for brucine, comprising two anhydrates, four hydrates (HyA - HyC and a 5.25-hydrate), twelve solvates (alcohols and acetone) and four heterosolvates (mixed solvates with water and alcohols). For strychnine it is hard to produce any solid form other than the stable anhydrate while the formation of specific solid state forms of brucine is governed by a complex interplay between temperature and relative humidity/water activity and it is rather a challenging to avoid hydrate formation. Differences in crystal packing and the high tendency for brucine to form hydrates are not intuitive from the molecular structure alone, as both molecules have hydrogen bond acceptor groups but lack hydrogen bond donor groups. Only the evaluation of the crystal energy landscapes, in particular the close-packed crystal structures and high-energy open frameworks containing voids of molecular (water) dimensions, allowed us to unravel the diverse solid state behavior of the two alkaloids at a molecular level. In this study we demonstrate that expanding the analysis of anhydrate crystal energy landscapes to higher energy structures and calculating the solvent-accessible volume can be used to estimate non-stoichiometric or channel hydrate (solvate) formation, without explicitly computing the hydrate/solvate crystal energy landscapes.

4-Aminoquinaldine monohydrate polymorphism: Prediction and impurity aided discovery of a difficult to access stable form

Crystal structure prediction studies indicated the existence of an unknown high density monohydrate structure (Hy1B°) as global energy minimum for 4-aminoquinaldine (4-AQ). We thus performed an interdisciplinary experimental and computational study elucidating the crystal structures, solid form inter-relationships, kinetic and thermodynamic stabilities of the stable anhydrate (AH I°), the kinetic monohydrate (Hy1A ) and this novel monohydrate polymorph (Hy1B°) of 4-AQ. The crystal structure of Hy1B° was determined by combining laboratory powder X-ray diffraction data and ab initio calculations. Dehydration studies with differential scanning calorimetry and solubility measurements confirmed the result of the lattice energy calculations, which identified Hy1B° as the thermodynamically most stable hydrate form. At 25 °C the equilibrium of the 4-AQ hydrate/anhydrate system was observed at an aw (water activity) of 0.14. The finding of Hy1B° was complicated by the fact that the metastable but kinetically stable Hy1A shows a higher nucleation and growth rate. The presence of an impurity in an available 4-AQ sample facilitated the nucleation of Hy1B°, whose crystallisation is favored under hydrothermal conditions. The value of combining experimental with theoretical studies in hydrate screening and characterisation, as well as the reasons for hydrate formation in 4-AQ, are discussed.

Can computed crystal energy landscapes help understand pharmaceutical solids?

Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape.

Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules and, by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search toward completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (Glee) software, a few of these extensions are briefly discussed.

Combined crystal structure prediction and high-pressure crystallization in rational pharmaceutical polymorph screening

Organic molecules, such as pharmaceuticals, agro-chemicals and pigments, frequently form several crystal polymorphs with different physicochemical properties. Finding polymorphs has long been a purely experimental game of trial-and-error. Here we utilize in silico polymorph screening in combination with rationally planned crystallization experiments to study the polymorphism of the pharmaceutical compound Dalcetrapib, with 10 torsional degrees of freedom one of the most flexible molecules ever studied computationally. The experimental crystal polymorphs are found at the bottom of the calculated lattice energy landscape, and two predicted structures are identified as candidates for a missing, thermodynamically more stable polymorph. Pressure-dependent stability calculations suggested high pressure as a means to bring these polymorphs into existence. Subsequently, one of them could indeed be crystallized in the 0.02 to 0.50 GPa pressure range and was found to be metastable at ambient pressure, effectively derisking the appearance of a more stable polymorph during late-stage development of Dalcetrapib.

Crystal polymorphism can lead to substances with vastly differing physicochemical properties, which has serious implications in the pharmaceutical industry. Here, the authors use in silico polymorph screening to accurately predict the resulting structures under set crystallisation environments.

Analysis of the conformational profiles of fenamates shows route towards novel, higher accuracy, force-fields for pharmaceuticals

The conformational barriers of the fenamates which lead to conformational polymorphism can be represented by a novel, physically motivated, model intramolecular potential suitable for extension to other pharmaceuticals.