Powder diffraction and crystal structure prediction identify four new coumarin polymorphs

Crystal Polymorph Search in the NPT Ensemble via a Deposition/Sublimation Alchemical Path

The formulation of active pharmaceutical ingredients involves discovering stable crystal packing arrangements or polymorphs, each of which has distinct pharmaceutically relevant properties. Traditional experimental screening techniques utilizing various conditions are commonly supplemented with in silico crystal structure prediction (CSP) to inform the crystallization process and mitigate risk. Predictions are often based on advanced classical force fields or quantum mechanical calculations that model the crystal potential energy landscape but do not fully incorporate temperature, pressure, or solution conditions during the search procedure. This study proposes an innovative alchemical path that utilizes an advanced polarizable atomic multipole force field to predict crystal structures based on direct sampling of the NPT ensemble. The use of alchemical (i.e., nonphysical) intermediates, a novel Monte Carlo barostat, and an orthogonal space tempering bias combine to enhance the sampling efficiency of the deposition/sublimation phase transition. The proposed algorithm was applied to 2-((4-(2-(3,4-dichlorophenyl)ethyl)phenyl)amino)benzoic acid (Cambridge Crystallography Database Centre ID: XAFPAY) as a case study to showcase the algorithm. Each experimentally determined polymorph with one molecule in the asymmetric unit was successfully reproduced via approximately 1000 short 1 ns simulations per space group where each simulation was initiated from random rigid body coordinates and unit cell parameters. Utilizing two threads of a recent Intel CPU (a Xeon Gold 6330 CPU at 2.00 GHz), 1 ns of sampling using the polarizable AMOEBA force field can be acquired in 4 h (equating to more than 300 ns/day using all 112 threads/56 cores of a dual CPU node) within the Force Field X software (https://ffx.biochem.uiowa.edu). These results demonstrate a step forward in the rigorous use of the NPT ensemble during the CSP search process and open the door to future algorithms that incorporate solution conditions using continuum solvation methods.

Concomitant polymorphs of 2-imino-2H-chromene-3-carboxylic acid amide: experimental and quantum chemical study

2-Iminocoumarin-3-carboxamide (2-imino-2 H-chromene-3-carboxylic acid) is a perspective compound for use in the pharmaceutical industry. This compound crystallized from several solvents as two concomitant polymorphic forms. The monoclinic polymorph, crystallized initially, is formed due to strong N-H...O hydrogen bonds, weak C-H...O and C-H...N(π) hydrogen bonds, and stacking interactions of `head-to-head' type. The triclinic polymorphic form obtained due to slow evaporation of the same solution is formed due to only strong intermolecular interactions, N-H...O hydrogen bonds of two types, and stacking interactions of two types. Analysis of pairwise interaction energies showed that the monoclinic structure is columnar while the triclinic one is layered. Calculations in a periodic approximation of their lattice energies confirmed that the monoclinic polymorphic crystals are metastable as compared to the stable triclinic polymorph. Further quantum chemical modeling of possible structure deformations proved that both concomitant polymorphs can not be transformed into a new polymorphic form under external influence.

Multimer Embedding Approach for Molecular Crystals up to Harmonic Vibrational Properties

Accurate calculations of molecular crystals are crucial for drug design and crystal engineering. However, periodic high-level density functional calculations using hybrid functionals are often prohibitively expensive for the relevant systems. These expensive periodic calculations can be circumvented by the usage of embedding methods in which, for instance, the periodic calculation is only performed at a lower-cost level and then monomer energies and dimer interactions are replaced by those of the higher-level method. Herein, we extend such a multimer embedding approach to enable energy corrections for trimer interactions and the calculation of harmonic vibrational properties up to the dimer level. We evaluate this approach for the X23 benchmark set of molecular crystals by approximating a periodic hybrid density functional (PBE0+MBD) by embedding multimers into less expensive calculations using a generalized-gradient approximation functional (PBE+MBD). We show that trimer interactions are crucial for accurately approximating lattice energies within 1 kJ/mol and might also be needed for further improvement of lattice constants and hence cell volumes. Finally, the vibrational properties are already very well captured at the monomer and dimer level, making it possible to approximate vibrational free energies at room temperature within 1 kJ/mol.

Unveiling the topology of partially disordered micro-crystalline nitro-perylenediimide with X-aggregate stacking: an integrated approach

Profound knowledge of the molecular structure and supramolecular organization of organic molecules is essential to understand their structure-property relationships. Herein we demonstrate the packing arrangement of partially disordered nitro-perylenediimide (NO2-PDI), revealing that the perylenediimide units exhibit an X-shaped packing pattern. The packing of NO2-PDI is derived using a complementary approach that utilises solid-state NMR (ssNMR) and 3D electron diffraction (3D ED) techniques. Perylenediimide (PDI) molecules are captivating due to their high luminescence efficiency and optoelectronic properties, which are related to supramolecular self-assembly. Increasing the alkyl chain length on the imide substituent poses a more significant challenge in crystallizing the resulting molecule. In addition to the alkyl tails, other functional groups, like the nitro group attached as a bay substituent, can also cause disorder. Such heterogeneity could lead to diffuse scattering, which then complicates the interpretation of diffraction experiment data, where perfect periodicity is expected. As a result, there is an unmet need to develop a methodology for solving the structures of difficult-to-crystallize materials. A synergistic approach is utilised in this manuscript to understand the packing arrangement of the disordered material NO2-PDI by making use of 3D ED, ssNMR and density functional theory calculations (DFT). The combination of these experimental and theoretical approaches provides great promise in enabling the structural investigation of novel materials with customized properties across various applications, which are, due to the internal disorder, very difficult to study by diffraction techniques. By effectively addressing these challenges, our methodology opens up new avenues for material characterization, thereby driving exciting advancements in the field.

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.

libMBD: A general-purpose package for scalable quantum many-body dispersion calculations

Many-body dispersion (MBD) is a powerful framework to treat van der Waals (vdW) dispersion interactions in density-functional theory and related atomistic modeling methods. Several independent implementations of MBD with varying degree of functionality exist across a number of electronic structure codes, which both limits the current users of those codes and complicates dissemination of new variants of MBD. Here, we develop and document libMBD, a library implementation of MBD that is functionally complete, efficient, easy to integrate with any electronic structure code, and already integrated in FHI-aims, DFTB+, VASP, Q-Chem, CASTEP, and Quantum ESPRESSO. libMBD is written in modern Fortran with bindings to C and Python, uses MPI/ScaLAPACK for parallelization, and implements MBD for both finite and periodic systems, with analytical gradients with respect to all input parameters. The computational cost has asymptotic cubic scaling with system size, and evaluation of gradients only changes the prefactor of the scaling law, with libMBD exhibiting strong scaling up to 256 processor cores. Other MBD properties beyond energy and gradients can be calculated with libMBD, such as the charge-density polarization, first-order Coulomb correction, the dielectric function, or the order-by-order expansion of the energy in the dipole interaction. Calculations on supramolecular complexes with MBD-corrected electronic structure methods and a meta-review of previous applications of MBD demonstrate the broad applicability of the libMBD package to treat vdW interactions.

Ritonavir Revisited: Melt Crystallization Can Easily Find the Late-Appearing Polymorph II and Unexpectedly Discover a New Polymorph III

Identification of a thermodynamically stable polymorph is an important step in the early stage of drug development. Ritonavir (RIT) is a well-known case where the most stable polymorph II emerged after being marketed, leading to a loss of $250 million. Herein, we report the findings that routine melt crystallization can reveal the late-appearing polymorph II of RIT at small supercooling, but the probability of nucleation is very low. The addition of 30-50% polyethylene glycol (PEG) promotes the crystallization of Form II as the only phase at low supercooling, making it easier to detect in polymorphism screening. During the course of our research, a new polymorph, denoted Form III, was unexpectedly discovered, crystallizing as the major phase from neat RIT melts. Single crystals of Form III were grown from melt microdroplets. Benefiting from the ability of synchrotron radiation to detect weak diffraction signals that cannot be accessible by a laboratory diffractometer, a reasonable structure of Form III was solved with slight disorder relative to thiazole groups (P1 space group and Z' = 4). The thermodynamic stability ranking of the three true polymorphs is Form II > Form I > Form III, as opposed to the order of solubility. The capacity to efficiently reveal rich polymorphs, especially the kinetically hindered polymorph, and rapidly grow single crystals of a new phase for structure determination together highlights the necessity of incorporating melt crystallization into routine methods for pharmaceutical polymorphism screening.

Cocrystal Synthesis through Crystal Structure Prediction

Crystal structure prediction (CSP) is an invaluable tool in the pharmaceutical industry because it allows to predict all the possible crystalline solid forms of small-molecule active pharmaceutical ingredients. We have used a CSP-based cocrystal prediction method to rank ten potential cocrystal coformers by the energy of the cocrystallization reaction with an antiviral drug candidate, MK-8876, and a triol process intermediate, 2-ethynylglyclerol. For MK-8876, the CSP-based cocrystal prediction was performed retrospectively and successfully predicted the maleic acid cocrystal as the most likely cocrystal to be observed. The triol is known to form two different cocrystals with 1,4-diazabicyclo[2.2.2]octane (DABCO), but a larger solid form landscape was desired. CSP-based cocrystal screening predicted the triol-DABCO cocrystal as rank one, while a triol-l-proline cocrystal was predicted as rank two. Computational finite-temperature corrections enabled determination of relative crystallization propensities of the triol-DABCO cocrystals with different stoichiometries and prediction of the triol-l-proline polymorphs in the free-energy landscape. The triol-l-proline cocrystal was obtained during subsequent targeted cocrystallization experiments and was found to exhibit an improved melting point and deliquescence behavior over the triol-free acid, which could be considered as an alternative solid form in the synthesis of islatravir.

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.

Inverse Design of Tetracene Polymorphs with Enhanced Singlet Fission Performance by Property-Based Genetic Algorithm Optimization

The efficiency of solar cells may be improved by using singlet fission (SF), in which one singlet exciton splits into two triplet excitons. SF occurs in molecular crystals. A molecule may crystallize in more than one form, a phenomenon known as polymorphism. Crystal structure may affect SF performance. In the common form of tetracene, SF is experimentally known to be slightly endoergic. A second, metastable polymorph of tetracene has been found to exhibit better SF performance. Here, we conduct inverse design of the crystal packing of tetracene using a genetic algorithm (GA) with a fitness function tailored to simultaneously optimize the SF rate and the lattice energy. The property-based GA successfully generates more structures predicted to have higher SF rates and provides insight into packing motifs associated with improved SF performance. We find a putative polymorph predicted to have superior SF performance to the two forms of tetracene, whose structures have been determined experimentally. The putative structure has a lattice energy within 1.5 kJ/mol of the most stable common form of tetracene.

XDM-corrected hybrid DFT with numerical atomic orbitals predicts molecular crystal lattice energies with unprecedented accuracy

Molecular crystals are important for many applications, including energetic materials, organic semiconductors, and the development and commercialization of pharmaceuticals. The exchange-hole dipole moment (XDM) dispersion model has shown good performance in the calculation of relative and absolute lattice energies of molecular crystals, although it has traditionally been applied in combination with plane-wave/pseudopotential approaches. This has limited XDM to use with semilocal functional approximations, which suffer from delocalization error and poor quality conformational energies, and to systems with a few hundreds of atoms at most due to unfavorable scaling. In this work, we combine XDM with numerical atomic orbitals, which enable the efficient use of XDM-corrected hybrid functionals for molecular crystals. We test the new XDM-corrected functionals for their ability to predict the lattice energies of molecular crystals for the X23 set and 13 ice phases, the latter being a particularly stringent test. A composite approach using a XDM-corrected, 25% hybrid functional based on B86bPBE achieves a mean absolute error of 0.48 kcal mol^-1 per molecule for the X23 set and 0.19 kcal mol^-1 for the total lattice energies of the ice phases, compared to recent diffusion Monte-Carlo data. These results make the new XDM-corrected hybrids not only far more computationally efficient than previous XDM implementations, but also the most accurate density-functional methods for molecular crystal lattice energies to date.

Direct structure determination of vemurafenib polymorphism from compact spherulites using 3D electron diffraction

The spherulitic morphology is considered to be the most common morphology of crystalline materials and is particularly apparent in melt-crystallized products. Yet, historically, the polycrystalline nature of spherulites has hindered successful crystal structure determination. Here, we report the direct structure determination of a clinical drug, vemurafenib (VMN), in compact spherulite form using 3D electron diffraction (3D ED). VMN has four known polymorphs. We first solved the crystal structures of α-, β-, and γ-VMN from compact spherulites using 3D ED, and the resulting structures were highly consistent with those obtained by single-crystal X-ray diffraction. We then determined the crystal structure of δ-VMN-the least stable polymorph which cannot be cultivated as a single crystal-directly from the compact spherulite sample. We unexpectedly discovered a new polymorph during our studies, denoted as ε-VMN. Single crystals of ε-VMN are extremely thin and not suitable for study by X-ray diffraction. Again, we determined the structure of ε-VMN in a compact spherulite form. This successful structure elucidation of all five VMN polymorphs demonstrates the possibility of directly determining structures from melt-grown compact spherulite samples. Thereby, this discovery will improve the efficiency and broaden the scope of polymorphism research, especially within the field of melt crystallization.

Polymorphs with Remarkably Distinct Physical and/or Chemical Properties

Polymorphism in crystals is known since 1822 and the credit goes to Mitscherlich who realized the existence of different crystal structures of the same compound while working with some arsenate and phosphate salts. Later on, this phenomenon was observed also in organic crystals. With the advent of different technologies, especially the easy availability of single crystal XRD instruments, polymorphism in crystals has become a common phenomenon. Almost 37 % of compounds (single component) are polymorphic to date. As the energies of the different polymorphic forms are very close to each other, small changes in crystallization conditions might lead to different polymorphic structures. As a result, sometimes it is difficult to control polymorphism. For this reason, it is considered to be a nuisance to crystal engineering. It has been realized that the property of a material depends not only on the molecular structure but also on its crystal structure. Therefore, it is not only of interest to academia but also has widespread applications in the materials science as well as pharmaceutical industries. In this review, we have discussed polymorphism which causes significant changes in materials properties in different fields of solid-state science, such as electrical, magnetic, SHG, thermal expansion, mechanical, luminescence, color, and pharmaceutical. Therefore, this review will interest researchers from supramolecular chemistry, materials science as well as medicinal chemistry.

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 structure determination protocol based on combined analysis of 3D-ED data, powder XRD data, solid-state NMR data and DFT-D calculations reveals the structure of a new polymorph of l-tyrosine

We report the crystal structure of a new polymorph of l-tyrosine (denoted the β polymorph), prepared by crystallization from the gas phase following vacuum sublimation. Structure determination was carried out by combined analysis of three-dimensional electron diffraction (3D-ED) data and powder X-ray diffraction (XRD) data. Specifically, 3D-ED data were required for reliable unit cell determination and space group assignment, with structure solution carried out independently from both 3D-ED data and powder XRD data, using the direct-space strategy for structure solution implemented using a genetic algorithm. Structure refinement was carried out both from powder XRD data, using the Rietveld profile refinement technique, and from 3D-ED data. The final refined structure was validated both by periodic DFT-D calculations, which confirm that the structure corresponds to an energy minimum on the energy landscape, and by the fact that the values of isotropic ¹³C NMR chemical shifts calculated for the crystal structure using DFT-D methodology are in good agreement with the experimental high-resolution solid-state ¹³C NMR spectrum. Based on DFT-D calculations using the PBE0-MBD method, the β polymorph is meta-stable with respect to the previously reported crystal structure of l-tyrosine (now denoted the α polymorph). Crystal structure prediction calculations using the AIRSS approach suggest that there are three other plausible crystalline polymorphs of l-tyrosine, with higher energy than the α and β polymorphs.

High-Accuracy Semiempirical Quantum Models Based on a Minimal Training Set

A great need exists for computationally efficient quantum simulation approaches that can achieve an accuracy similar to high-level theories at a fraction of the computational cost. In this regard, we have leveraged a machine-learned interaction potential based on Chebyshev polynomials to improve density functional tight binding (DFTB) models for organic materials. The benefit of our approach is two-fold: (1) many-body interactions can be corrected for in a systematic and rapidly tunable process, and (2) high-level quantum accuracy for a broad range of compounds can be achieved with ∼0.3% of data required for one advanced deep learning potential. Our model exhibits both transferability and extensibility through comparison to quantum chemical results for organic clusters, solid carbon phases, and molecular crystal phase stability rankings. Our efforts thus allow for high-throughput physical and chemical predictions with up to coupled-cluster accuracy for systems that are computationally intractable with standard approaches.

Structure, Spectroscopic Investigation, Molecular Docking and In vitro Cytotoxicity Studies on 4,7-dihydroxycoumarin: A Breast Cancer Drug

Coumarin derivatives are broadly used as anti-inflammatory, antioxidants, anticancer, and antiviral drugs in recent years. In particular, hydroxy coumarins have great importance because of their various biological and pharmacological purposes. The quantum chemical studies of 4,7-dihydroxycoumarin (DHC) have been performed using the cc-pVTZ level of basis set. The DHC molecular structure has been optimized and the computed frequency assignments have been correlated well with the experimental results. The experimental [Formula: see text]C NMR shifts of DHC have been compared with the computed [Formula: see text]C NMR in the dimethyl sulfoxide (DMSO) solution using the Gauge-invariant atomic orbital (GIAO) method. The electron delocalization within the DHC is shown by highest occupied molecular orbitals (HOMO)-lowest unoccupied molecular orbitals (LUMO) energy analysis, and the resulting small energy gap value reveal the molecule’s bioactive characteristics. The natural bond orbital (NBO) analysis approves the bioactive property of the DHC molecule. The DHC compound has a cytotoxic impact on the MCF-7 breast cancer cell line, according to in vitro cytotoxicity studies. The docking study approves that the DHC works as a new inhibitor of breast cancer targeted proteins such as epidermal growth factor receptor (EGFR), estrogen receptor (ER), and progesterone receptor (PR). Thus, this work covers the approach for the evolution of new drugs against breast cancer.

Solid-State Structural Properties of Alloxazine Determined from Powder XRD Data in Conjunction with DFT-D Calculations and Solid-State NMR Spectroscopy: Unraveling the Tautomeric Identity and Pathways for Tautomeric Interconversion

We report the solid-state structural properties of alloxazine, a tricyclic ring system found in many biologically important molecules, with structure determination carried out directly from powder X-ray diffraction (XRD) data. As the crystal structures containing the alloxazine and isoalloxazine tautomers both give a high-quality fit to the powder XRD data in Rietveld refinement, other techniques are required to establish the tautomeric form in the solid state. In particular, high-resolution solid-state ¹⁵N NMR data support the presence of the alloxazine tautomer, based on comparison between isotropic chemical shifts in the experimental ¹⁵N NMR spectrum and the corresponding values calculated for the crystal structures containing the alloxazine and isoalloxazine tautomers. Furthermore, periodic DFT-D calculations at the PBE0-MBD level indicate that the crystal structure containing the alloxazine tautomer has significantly lower energy. We also report computational investigations of the interconversion between the tautomeric forms in the crystal structure via proton transfer along two intermolecular N-H···N hydrogen bonds; DFT-D calculations at the PBE0-MBD level indicate that the tautomeric interconversion is associated with a lower energy transition state for a mechanism involving concerted (rather than sequential) proton transfer along the two hydrogen bonds. However, based on the relative energies of the crystal structures containing the alloxazine and isoalloxazine tautomers, it is estimated that under conditions of thermal equilibrium at ambient temperature, more than 99.9% of the molecules in the crystal structure will exist as the alloxazine tautomer.

Crystal structure prediction of N-halide phthalimide compounds: Halogen bond synthon as a touchstone

We address crystal structure prediction problem by combining evolutionary algorithm USPEX (used to predict sets of low-energy crystal structures) and synthon approach (extracting preferable supramolecular synthons from Cambridge Structural Database,...

Imidacloprid Crystal Polymorphs for Disease Vector Control and Pollinator Protection

Imidacloprid, the world's leading insecticide, has been approved recently for controlling infectious disease vectors; yet, in agricultural settings, it has been implicated in the frightening decline of pollinators. This argues for strategies that sharply reduce the environmental impact of imidacloprid. When used as a contact insecticide, the effectiveness of imidacloprid relies on physical contact between its crystal surfaces and insect tarsi. Herein, seven new imidacloprid crystal polymorphs are reported, adding to two known forms. Anticipating that insect uptake of imidacloprid molecules would depend on the respective free energies of crystal polymorph surfaces, measurements of insect knockdown times for the metastable crystal forms were as much as nine times faster acting than the commercial form against Aedes, Anopheles, and Culex mosquitoes as well as Drosophila (fruit flies). These results suggest that replacement of commercially available imidacloprid crystals (a.k.a. Form I) in space-spraying with any one of three new polymorphs, Forms IV, VI, IX, would suppress vector-borne disease transmission while reducing environmental exposure and harm to nontarget organisms.

Photophysical properties of a boron analogue of coumarin

In this report, we present a study into the structure and electronic properties of difluoroboronsalicylaldoxime (DFBS), a boron-based structural analog of coumarin. The modification of the heterocyclic ring of coumarin with boron results in a compound with similar structural parameters and molecular orbitals to coumarin. DFT and TDDFT calculations reveal a significant stabilization of the LUMO in DFBS; this is supported by a ∼40 nm red shift of the lowest electronic transition in the absorption spectrum. Interestingly, DFBS is emissive, while unmodified coumarin is effectively non-radiative. Comparisons between DFBS, emissive coumarin variants, and unmodified coumarin suggest that the charge transfer character of the transition contributes to the fluorescence.

Polymorphic forms of antiandrogenic drug nilutamide: structural and thermodynamic aspects

Attempts to obtain new cocrystals of nonsteroidal antiandrogenic drug nilutamide produced alternative polymorphic forms of the compound (Form II and Form III) and their crystal structures were elucidated by single-crystal X-ray diffraction. Apart from the cocrystallization technique, lyophilization was found to be an effective strategy for achieving polymorph control of nilutamide, which was difficult to obtain by other methods. The physicochemical properties and relative stability of the commercial Form I and newly obtained Form II were comprehensively investigated by a variety of analytical methods (thermal analysis, solution calorimetry, solubility, and sublimation), whereas for Form III, only a handful of experimental parameters were obtained due to the elusive nature of the polymorph. Form I and Form II were found to be monotropically related, with Form I being confirmed as the thermodynamically most stable solid phase. In addition, the performance of different DFT-D and semi-empirical schemes for lattice energy calculation and polymorph energy ranking was compared and analysed. Lattice energy calculations using periodic DFT at B3LYP-D3/6-31(F+)G(d,p) and PBEh-3c/def2-mSVP levels of theory were found to provide the most accurate lattice energy values for Form I against experimental data, while PIXEL and PBEh-3c/def2-mSVP were the only methods that predicted the correct order of stability of Forms I and II.

FFCASP: A Massively Parallel Crystal Structure Prediction Algorithm

A new algorithm called Fast and Flexible CrystAl Structure Predictor (FFCASP) was developed to predict the structure of covalent and molecular crystals. FFCASP is massively parallel and able to handle more than 200 atoms in the unit cell (in other terms, it allows global optimization around 100 individual parameters). It uses a global optimizer specialized for Crystal Structure Prediction (CSP) which combines particle swarm and simulated annealing optimizers. Three different molecular crystals, including diverse intermolecular interactions, namely, cytosine, coumarin, and pyrazinamide, have been selected to evaluate the performance of FFCASP. While cytosine polymorphs have been searched by employing two different force fields (a DFT-SAPT based intermolecular potential and generalized amber force field (GAFF)) up to Z = 16, only GAFF has been used both in coumarin and pyrazinamide polymorph searches up to Z = 4. For these three molecular crystals, FFCASP generated more than 20 000 crystal structures, and the unique ones have been further treated by DFT-D3. A combination of data mining and a machine learning approach was introduced to determine the unique structures and their distribution into different clusters, which ultimately gives an opportunity to retrieve the common features and relations between the resulting structures. There are two known experimental crystal structures of cytosine, and both were successfully located with FFCASP. Two of the reported crystal structures of coumarin have been reproduced. Similarly, in pyrazinamide, three known experimental structures have been rediscovered. In addition to finding the experimentally known structures, FFCASP also located other low-energy structures for each considered molecular crystals. These successes of FFCASP offer the possibility to discover the polymorphic nature of other important molecular crystals (e.g., drugs) as well.

Data-efficient machine learning for molecular crystal structure prediction

The combination of modern machine learning (ML) approaches with high-quality data from quantum mechanical (QM) calculations can yield models with an unrivalled accuracy/cost ratio. However, such methods are ultimately limited by the computational effort required to produce the reference data. In particular, reference calculations for periodic systems with many atoms can become prohibitively expensive for higher levels of theory. This trade-off is critical in the context of organic crystal structure prediction (CSP). Here, a data-efficient ML approach would be highly desirable, since screening a huge space of possible polymorphs in a narrow energy range requires the assessment of a large number of trial structures with high accuracy. In this contribution, we present tailored Δ-ML models that allow screening a wide range of crystal candidates while adequately describing the subtle interplay between intermolecular interactions such as H-bonding and many-body dispersion effects. This is achieved by enhancing a physics-based description of long-range interactions at the density functional tight binding (DFTB) level-for which an efficient implementation is available-with a short-range ML model trained on high-quality first-principles reference data. The presented workflow is broadly applicable to different molecular materials, without the need for a single periodic calculation at the reference level of theory. We show that this even allows the use of wavefunction methods in CSP.

Usage of Quantum Chemical Methods to Understand the Formation of Concomitant Polymorphs of Acetyl 2-(N-(2-Fluorophenyl)imino)coumarin-3-carboxamide

Crystallization of concomitant polymorphs is a very intriguing process that is difficult to be studied experimentally. A comprehensive study of two polymorphic modifications of acetyl 2-(N-(2-fluorophenyl)imino)coumarin-3-carboxamide using quantum chemical methods has revealed molecular and crystal structure dependence on crystallization conditions. Fast crystallization associated with a kinetically controlled process results in the formation of a columnar structure with a nonequilibrium molecular conformation and more isotropic topology of interaction energies between molecules. Slow crystallization may be considered as a thermodynamically controlled process and leads to the formation of a layered crystal structure with the conformation of the molecule corresponding to local minima and anisotropic topology of interaction energies. Fast crystallization results in the formation of a lot of weak intermolecular interactions, while slow crystallization leads to the formation of small amounts of stronger interactions.

Using X-ray Diffraction Techniques for Biomimetic Drug Development, Formulation, and Polymorphic Characterization

Drug development is a decades-long, multibillion dollar investment that often limits itself. To decrease the time to drug approval, efforts are focused on drug targets and drug formulation for optimal biocompatibility and efficacy. X-ray structural characterization approaches have catalyzed the drug discovery and design process. Single crystal X-ray diffraction (SCXRD) reveals important structural details and molecular interactions for the manifestation of a disease or for therapeutic effect. Powder X-ray diffraction (PXRD) has provided a method to determine the different phases, purity, and stability of biological drug compounds that possess crystallinity. Recently, synchrotron sources have enabled wider access to the study of noncrystalline or amorphous solids. One valuable technique employed to determine atomic arrangements and local atom ordering of amorphous materials is the pair distribution function (PDF). PDF has been used in the study of amorphous solid dispersions (ASDs). ASDs are made up of an active pharmaceutical ingredient (API) within a drug dispersed at the molecular level in an amorphous polymeric carrier. This information is vital for appropriate formulation of a drug for stability, administration, and efficacy purposes. Natural or biomimetic products are often used as the API or the formulation agent. This review profiles the deep insights that X-ray structural techniques and associated analytical methods can offer in the development of a drug.

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.

Statistical Mechanical Approximations to More Efficiently Determine Polymorph Free Energy Differences for Small Organic Molecules

Methods to efficiently determine the relative stability of polymorphs of organic crystals are highly desired in crystal structure predictions (CSPs). Current methodologies include calculating the free energy of static lattice phonons, quasi-harmonic approximations (QHA), and computing the full thermodynamic cycle using replica exchange molecular dynamics (REMD). We found that 13 out of the 29 systems minimized from experimental crystal structures restructured to a lower energy minimum when heated and annealed using REMD, a phenomenon that QHA alone cannot capture. Here, we present a series of methods that are intermediate in accuracy and expense between QHA and computing the full thermodynamic cycle, which can save 42-80% of the computational cost and introduces, on this benchmark, a relatively small (0.16 ± 0.04 kcal/mol) error relative to the full thermodynamic cycle. In particular, a method that Boltzmann weights harmonic free energies from along the trajectory of REMD replica exchange appears to be an appropriate intermediate between QHA and the full thermodynamic cycle using MD when screening crystal polymorph stability.

Natural deep eutectic solvent supported targeted solid-liquid polymer carrier for breast cancer therapy

Solid–liquid nanocarriers (SLNs) are at the front of the rapidly emerging field of medicinal applications with a potential role in the delivery of bioactive agents. Here, we report a new SLN of natural deep eutectic solvent (NADES) and biotin-conjugated lysine–polyethylene glycol copolymer. The SLN system was analyzed for its functional groups, thermal stability, crystalline nature, particle size, and surface morphology through the instrumental analysis of FT-IR, TGA, XRD, DLS, SEM, and TEM. Encapsulation of PTX (paclitaxel) and 7-HC (7-hydroxycoumarin) with the SLN was carried out by dialysis, and UV-visible spectra evidenced the drug loading capacity and higher encapsulation efficiency obtained. The enhanced anticancer potential of PTX- and 7-HC-loaded SLN was assessed in vitro, and the system reduces the cell viability of MDA-MB-231 cells. The PTX- and 7-HC-loaded SLN system was investigated in a breast cancer-induced rat model via in vivo studies. It shows decreased lysosomal enzymes and increased levels of caspase to cure breast tumors. It very well may be reasoned that the designed PTX- and 7-HC-loaded SLN system has strong anticancer properties and exhibits potential for delivery of drug molecules in cancer treatment.

Solid–liquid nanocarriers (SLNs) are at the front of the rapidly emerging field of medicinal applications with a potential role in the delivery of bioactive agents.

XO-PBC: An Accurate and Efficient Method for Molecular Crystals

In this work, we propose the XO-PBC method, which combines the eXtended ONIOM method (XO) with the periodic boundary condition (PBC) for the description of molecular crystals. XO-PBC tries to embed a finite cluster cut out from the solid into the periodic environment, making it feasible to employ advanced molecular quantum chemistry methods, which are usually prohibitively expensive for direct PBC calculations. In particular, XO-PBC utilizes the results from force calculations to design the scheme to fragment the molecule when crystals are made of large molecules and to select cluster model systems automatically consisting of dimer up to tetramer interactions for embedding. By applying an appropriate theory to each model, a satisfactory accuracy for the system under study is ensured, while a high efficiency is achieved with massively parallel computing by distributing model systems onto different processors. A comparison of the XO-PBC calculations with the conventional direct PBC calculations at the B3LYP level demonstrates its accuracy at substantially low cost for the description of molecular crystals. The usefulness of the XO-PBC method is further exemplified, showing that XO-PBC is able to predict the lattice energies of various types of molecular crystals within chemical accuracy (<4 kJ/mol) when the doubly hybrid density functional XYG3 is used as the target high level and the periodic PBE as the basic low level. The XO-PBC method provides a general protocol that brings the great predictive power of advanced electronic structure methods from molecular systems to the extended solids.

Overcoming the difficulties of predicting conformational polymorph energetics in molecular crystals via correlated wavefunction methods

Molecular crystal structure prediction is increasingly being applied to study the solid form landscapes of larger, more flexible pharmaceutical molecules. Despite many successes in crystal structure prediction, van der Waals-inclusive density functional theory (DFT) methods exhibit serious failures predicting the polymorph stabilities for a number of systems exhibiting conformational polymorphism, where changes in intramolecular conformation lead to different intermolecular crystal packings. Here, the stabilities of the conformational polymorphs of o-acetamidobenzamide, ROY, and oxalyl dihydrazide are examined in detail. DFT functionals that have previously been very successful in crystal structure prediction perform poorly in all three systems, due primarily to the poor intramolecular conformational energies, but also due to the intermolecular description in oxalyl dihydrazide. In all three cases, a fragment-based dispersion-corrected second-order Møller-Plesset perturbation theory (MP2D) treatment of the crystals overcomes these difficulties and predicts conformational polymorph stabilities in good agreement with experiment. These results highlight the need for methods which go beyond current-generation DFT functionals to make crystal polymorph stability predictions truly reliable.

Charge mobility calculation of organic semiconductors without use of experimental single-crystal data

Prediction of material properties of newly designed molecules is a long-term goal in organic electronics. In general, it is a difficult problem, because the material properties are dominated by the unknown packing structure. We present a practical method to obtain charge transport properties of organic single crystals, without use of experimental single-crystal data. As a demonstration, we employ the promising molecule C10-DNBDT. We succeeded in quantitative evaluation of charge mobility of the single crystal using our quantum wave-packet dynamical simulation method. Here, the single-crystal data is computationally obtained by searching possible packing structures from structural formula of the molecule. We increase accuracy in identifying the actual crystal structure from suggested ones by using not only crystal energy but also similarity between calculated and experimental powder X-ray diffraction patterns. The proposed methodology can be a theoretical design technique for efficiently developing new high-performance organic semiconductors, since it can estimate the charge transport properties at early stage in the process of material development.

Polymorphism in Solid Dispersions

Solid dispersions embed active pharmaceutical ingredients in polymeric carriers to improve their solubility. Three solid dispersion preparation techniques are typically employed: solvent evaporation, solvent-fusion, and fusion methods. Although these are also widely recommended as preparative methods for phase diagram determination, few examples exist concerning their effect on the resulting polymorph, once the solid dispersion is produced. In this study, the influence of these methods on the polymorphic form obtained in crystalline solid dispersions (CSDs) composed of flufenamic acid (FFA) and poly(ethylene glycol) was investigated. The physical mixtures and CSDs were characterized by powder X-ray diffraction, infrared spectroscopy, and differential scanning calorimetry. The results reveal that the fusion method leads to concomitant polymorphs (mainly FFA I and III) in the CSDs. In contrast, the solvent evaporation and solvent-fusion methods lead to FFA III. Collectively, these results demonstrate that preparative methods have a significant influence on the phase diagrams determined (average relative deviation ≤8%), which are often used to justify the design space of manufacturing processes, including those deemed "continuous." Consequently, choosing a preparation method that results in the desired polymorph is crucial to ensure accurate determination of phase diagrams and critical quality attributes of formulations.

Discovery of new polymorphs of the tuberculosis drug isoniazid

Two new metastable polymorphs of the tuberculosis drug isoniazid, considered monomorphic for sixty years, were discovered using melt crystallization and nanoscale confinement.

Polymorphism of 3-(5-phenyl-1,3,4-oxadiazol-2-yl)- and 3-[5-(pyridin-4-yl)-1,3,4-oxadiazol-2-yl]-2H-chromen-2-ones

This study of 3-(5-phenyl-1,3,4-oxadiazol-2-yl)-2H-chromen-2-one, C₁₇H₁₀N₂O₃, 1, and 3-[5-(pyridin-4-yl)-1,3,4-oxadiazol-2-yl]-2H-chromen-2-one, C₁₆H₉N₃O₃, 2, was performed on the assumption of the potential anticancer activity of the compounds. Three polymorphic structures for 1 and two polymorphic structures for 2 have been studied thoroughly. The strongest intermolecular interaction is stacking of the `head-to-head' type in all the studied crystals. The polymorphic structures of 1 differ with respect to the intermolecular interactions between stacked columns. Two of the polymorphs have a columnar or double columnar type of crystal organization, while the third polymorphic structure can be classified as columnar-layered. The difference between the two structures of 2 is less pronounced. Both crystals can be considered as having very similar arrangements of neighbouring columns. The formation of polymorphic modifications is caused by a subtle balance of very weak intermolecular interactions and packing differences can be identified only using an analysis based on a study of the pairwise interaction energies.

Crystal Structure Optimization and Gibbs Free Energy Comparison of Five Sulfathiazole Polymorphs by the Embedded Fragment QM Method at the DFT Level

Molecular crystal plays an important role in many fields of science and technology, but it often crystallizes in different polymorphs with different physical properties. To guide the experimental synthesis of candidate materials, the atomic-scale model is frequently used to predict the most stable polymorph and its structural properties. Here, we show how an ab initio method can be used to achieve a rapid and accurate prediction of sulfathiazole crystal polymorphs (an antibiotic drug), based on the Gibbs free energy calculation and Raman spectra analysis. At the atmospheric pressure and the temperature of 300 K, we demonstrate that form III (FIII) is the most stable structure of sulfathiazole. The agreement between the predicted and experimental crystal structures corresponds to the order of stability for five sulfathiazole polymorphs as FI < FV < FIV < FII < FIII, which is achieved by employing the density functional theory (DFT) calculations.

Reliable and practical computational description of molecular crystal polymorphs

Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies to within 1 kJ/mol per molecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods. Specifically, we present a hierarchical energy ranking approach intended for the refinement of relative stabilities in the final stage of a crystal structure prediction procedure. Such a combined approach provides excellent stability rankings for all studied systems and can be applied to molecular crystals of pharmaceutical importance.

Hydrogen bonding vs. stacking interaction in the crystals of the simplest coumarin derivatives: a study from the energetic viewpoint

Hydrogen bonded and stacked dimers have very close interaction energies in the crystals of the simplest coumarin derivatives according to the data of the crystal structure analysis based on the comparison of pairwise interaction energies.

Theory and practice of modeling van der Waals interactions in electronic-structure calculations

The accurate description of long-range electron correlation, most prominently including van der Waals (vdW) dispersion interactions, represents a particularly challenging task in the modeling of molecules and materials. vdW forces arise from the interaction of quantum-mechanical fluctuations in the electronic charge density. Within (semi-)local density functional approximations or Hartree-Fock theory such interactions are neglected altogether. Non-covalent vdW interactions, however, are ubiquitous in nature and play a key role for the understanding and accurate description of the stability, dynamics, structure, and response properties in a plethora of systems. During the last decade, many promising methods have been developed for modeling vdW interactions in electronic-structure calculations. These methods include vdW-inclusive Density Functional Theory and correlated post-Hartree-Fock approaches. Here, we focus on the methods within the framework of Density Functional Theory, including non-local van der Waals density functionals, interatomic dispersion models within many-body and pairwise formulation, and random phase approximation-based approaches. This review aims to guide the reader through the theoretical foundations of these methods in a tutorial-style manner and, in particular, highlight practical aspects such as the applicability and the advantages and shortcomings of current vdW-inclusive approaches. In addition, we give an overview of complementary experimental approaches, and discuss tools for the qualitative understanding of non-covalent interactions as well as energy decomposition techniques. Besides representing a reference for the current state-of-the-art, this work is thus also designed as a concise and detailed introduction to vdW-inclusive electronic structure calculations for a general and broad audience.