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

In traditional molecular mechanics force fields, intramolecular non-bonded interactions are modelled as intermolecular interactions, and the form of the torsion potential is based on the conformational profiles of small organic molecules. We investigate how a separate model for the intramolecular forces in pharmaceuticals could be more realistic by analysing the low barrier to rotation of the phenyl ring in the fenamates (substituted N-phenyl-aminobenzoic acids), that results in a wide range of observed angles in the numerous fenamate crystal structures. Although the conformational energy changes by significantly less than 10 kJmol-1 for a complete rotation of the phenyl ring for fenamic acid, the barrier is only small because of small correlated changes in the other bond and torsion angles. The maxima for conformations where the two aromatic rings approach coplanarity arise from steric repulsion, but the maxima when the two rings are approximately perpendicular arise from a combination of an electronic effect and intramolecular dispersion. Representing the ab initio conformational energy profiles as a cosine series alone is ineffective; however, combining a cos2ξ term to represent the electronic barrier with an intramolecular atom-atom exp-6 term for all atom pairs separated by three or more bonds (1-4 interactions) provides a very effective representation. Thus we propose a new, physically motivated, generic analytical model of conformational energy, which could be combined with an intermolecular model to form more accurate force-fields for modelling the condensed phases of pharmaceutical-like organic molecules

Calculation of Diamagnetic Susceptibility Tensors of Organic Crystals: From Coronene to Pharmaceutical Polymorphs

Understanding why crystallization in strong magnetic fields can lead to new polymorphs requires methods to calculate the diamagnetic response of organic molecular crystals. We develop the calculation of the macroscopic diamagnetic susceptibility tensor, χ^{cryst}, for organic molecular crystals using periodic density functional methods. The crystal magnetic susceptibility tensor, χ^{cryst}, for all experimentally known polymorphs, and its molecular counterpart, χ^{mol}, are calculated for flexible pharmaceuticals such as carbamazepine, flufenamic acid, and chalcones, and rigid molecules, such as benzene, pyridine, acridine, anthracene, and coronene, whose molecular magnetic properties have been traditionally studied. A tensor addition method is developed to approximate the crystal diamagnetic susceptibility tensor, χ^{cryst}, from the molecular one, χ^{mol}, giving good agreement with those calculated directly using the more costly periodic density functional method for χ^{cryst}. The response of pharmaceutical molecules and crystals to magnetic fields, as embodied by χ^{cryst}, is largely determined by the packing in the crystal, as well as the molecular conformation. The anisotropy of χ^{cryst} can vary considerably between polymorphs though the isotropic terms are fairly constant. The implications for developing a computational method for predicting whether crystallization in a magnetic field could produce a novel or different polymorph are discussed

The potential of computed crystal energy landscapes to aid solid-form development

Solid-form screening to identify all solid forms of an active pharmaceutical ingredient (API) has become increasingly important in ensuring the quality by design of pharmaceutical products and their manufacturing processes. However; despite considerable enlargement of the range of techniques that have been shown capable of producing novel solid forms; it is possible that practically important forms might not be found in the short timescales currently allowed for solid-form screening. Here; we report on the state-of-the-art use of computed crystal energy landscapes to complement pharmaceutical solid-form screening. We illustrate how crystal energy landscapes can help establish molecular-level understanding of the crystallization behavior of APIs and enhance the ability of solid-form screening to facilitate pharmaceutical development

Systematic Finite-Temperature Reduction of Crystal Energy Landscapes

Crystal structure prediction methods are prone to overestimate the number of potential polymorphs of organic molecules. In this work, we aim to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that can easily interconvert at finite temperature and pressure. Following this approach, we rationally reduce the number of predicted putative polymorphs in crystal structure prediction (CSP)-generated crystal energy landscapes. This uses an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that are effectively equivalent at finite temperature and pressure. Biased simulations are used to reduce the impact of limited sampling time and to estimate the work associated with polymorphic transformations. We demonstrate the proposed systematic approach by studying the polymorphs of urea and succinic acid, reducing an initial set of over 100 energetically plausible CSP structures to 12 and 27 respectively, including the experimentally known polymorphs. The simulations also indicate the types of disorder and stacking errors that may occur in real structures

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

The Crystal Structure of 5-Aminouracil and the Ambiguity of Alternative Polymorphs

The nucleobase derivative 5-aminouracil (AUr, C4H5N3O2) is of interest for its biological activity, yet the solid state structure of this compound has remained elusive owing to its propensity to crystallize as aggregates of microcrystalline particles. Here we report the first single-crystal structure of AUr determined from synchrotron x-ray diffraction data. An early crystal structure prediction effort, which assumed that AUr was rigid in the isolated molecule optimized conformation, provided several poor matches to the simulated PXRD pattern. Revisiting these crystal structures, by periodic electronic level modelling (PBE-TS optimization) gave more realistic relative lattice energies, but a good match to the experimental powder pattern required using the experimental cell parameters. PXRD and Raman spectroscopy suggest that phase impurities may be present in the bulk crystallization product, though the identity of alternative polymorphs could not be confirmed on the basis of the data available

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

Is zeroth order crystal structure prediction (CSP_0) coming to maturity? What should we aim for in an ideal crystal structure prediction code?

Crystal structure prediction based on searching for the global minimum in the lattice energy (CSP_0) is growing in use for guiding the discovery of new materials, for example, new functional materials, new phases of interest to planetary scientists and new polymorphs relevant to pharmaceutical development. This Faraday Discussion can assess the progress of CSP_0 over the range of types of materials to which CSP is currently and could be applied, which depends on our ability to model the variety of interatomic forces in crystals. The basic hypothesis, that the outcome of crystallisation is determined by thermodynamics, needs examining by considering methods of modelling relative thermodynamic stability not only as a function of pressure and temperature, but also of size, solvent and the presence of heterogeneous templates or impurities (CSP_thd). Given that many important materials persist, and indeed may be formed, when they are not the most thermodynamically stable structure, we need to define what would be required of an ideal CSP code (CSP_aim)

Predicting crystal structures of organic compounds

Currently, organic crystal structure prediction (CSP) methods are based on searching for the most thermodynamically stable crystal structure, making various approximations in evaluating the crystal energy. The most stable (global minimum) structure provides a prediction of an experimental crystal structure. However, depending on the specific molecule, there may be other structures which are very close in energy. In this case, the other structures on the crystal energy landscape may be polymorphs, components of static or dynamic disorder in observed structures, or there may be no route to nucleating and growing these structures. A major reason for performing CSP studies is as a complement to solid form screening to see which alternative packings to the known polymorphs are thermodynamically feasible