Attempted prediction of the crystal structures of six monosaccharides

Crystal structure prediction is changing from basic science to applied technology

Prediction of true polymorphs as dynamic ensembles in contrast to hypothetical static crystal structures.

Modeling Polymorphic Molecular Crystals with Electronic Structure Theory

Interest in molecular crystals has grown thanks to their relevance to pharmaceuticals, organic semiconductor materials, foods, and many other applications. Electronic structure methods have become an increasingly important tool for modeling molecular crystals and polymorphism. This article reviews electronic structure techniques used to model molecular crystals, including periodic density functional theory, periodic second-order Møller-Plesset perturbation theory, fragment-based electronic structure methods, and diffusion Monte Carlo. It also discusses the use of these models for predicting a variety of crystal properties that are relevant to the study of polymorphism, including lattice energies, structures, crystal structure prediction, polymorphism, phase diagrams, vibrational spectroscopies, and nuclear magnetic resonance spectroscopy. Finally, tools for analyzing crystal structures and intermolecular interactions are briefly discussed.

Crystal structure and prediction

The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

How can Databases assist with the Prediction of Chemical Compounds?

An overview is given on the ways databases can be employed to aid in the prediction of chemical compounds, in particular inorganic crystalline compounds. Methods currently employed and possible future approaches are discussed.

Crystal structure prediction of flexible molecules using parallel genetic algorithms with a standard force field

This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential.

Determination, prediction, and understanding of structures, using the energy landscapes of chemical systems – Part II

In the past decade, new theoretical approaches have been developed to determine, predict and understand the struc-ture of chemical compounds. The central element of these methods has been the investigation of the energy landscape of chemical systems. Applications range from extended crystalline and amorphous compounds over clusters and molecular crystals to proteins. In this review, we are going to give an introduction to energy landscapes and methods for their investigation, together with a number of examples. These include structure prediction of extended and mo-lecular crystals, structure prediction and folding of proteins, structure analysis of zeolites, and structure determination of crystals from powder diffraction data.

Prediction of crystal structure of a rare monosaccharide – influence of model geometry

Crystal structure of a hexagonal monosaccharide, C11H18N2O4, was succesfully predicted by potential energy minimisation. Four starting molecular models differing in ring conformations were based on similar structures and the positions of two substituents (-NH2, -CN) were found by semiempirical AM1 calculations. Generated structures were ranked according to both potential energy values and corre-sponding Rwp ´s. Calculated potential energy was sensitive to changes in the geometries of the sachcharide rings as well as to the positions of substituents. Rigid body Rietveld refinements did not improve accuracy of the crystal structures with low Rwp ´s and high potential energy.

Prediction of crystal structures of two monosaccharides by potential energy minimisation

Crystal structures of a monoclinic and a hexagonal monosaccharide, 40 atoms per molecule, were successfully predicted by a potential energy minimisation method. The intermolecular interactions were described by three terms covering electrostatic, attraction and repulsion contributions to the total energy. Two types of atomic charges based on the Hartree-Fock wave function, Mulliken and derived from the electrostatic field generated by a molecule, were combined with two force fields called Williams and Dreiding. With the cell parameters fixed, the correct structure was found in approximately 75 % of cases. With the cell parameters optimised no reasonable structure was found for the hexagonal monosaccharide. The accuracy of the predicted structures was evaluated by means of X-ray Rietveld refinements.

Conformation, dynamics, solvation and relative stabilities of selected β-hexopyranoses in water: a molecular dynamics study with the gromos 45A4 force field

The present article reports long timescale (200 ns) simulations of four beta-D-hexopyranoses (beta-D-glucose, beta-D-mannose, beta-D-galactose and beta-D-talose) using explicit-solvent (water) molecular dynamics and vacuum stochastic dynamics simulations together with the GROMOS 45A4 force field. Free-energy and solvation free-energy differences between the four compounds are also calculated using thermodynamic integration. Along with previous experimental findings, the present results suggest that the formation of intramolecular hydrogen-bonds in water is an 'opportunistic' consequence of the close proximity of hydrogen-bonding groups, rather than a major conformational driving force promoting this proximity. In particular, the conformational preferences of the hydroxymethyl group in aqueous environment appear to be dominated by 1,3-syn-diaxial repulsion, with gauche and solvation effects being secondary, and intramolecular hydrogen-bonding essentially negligible. The rotational dynamics of the exocyclic hydroxyl groups, which cannot be probed experimentally, is found to be rapid (10-100 ps timescale) and correlated (flip-flop hydrogen-bonds interconverting preferentially through an asynchronous disrotatory pathway). Structured solvent environments are observed between the ring and lactol oxygen atoms, as well as between the 4-OH and hydroxymethyl groups. The calculated stability differences between the four compounds are dominated by intramolecular effects, while the corresponding differences in solvation free energies are small. An inversion of the stereochemistry at either C(2) or C(4) from equatorial to axial is associated with a raise in free energy. Finally, the particularly low hydrophilicity of beta-D-talose appears to be caused by the formation of a high-occurrence hydrogen-bonded bridge between the 1,3-syn-diaxial 2-OH and 4-OH groups. Overall, good agreement is found with available experimental and theoretical data on the structural, dynamical, solvation and energetic properties of these compounds. However, this detailed comparison also reveals some discrepancies, suggesting the need (and providing a solid basis) for further refinement.

Ab initio crystal structure prediction?I. Rigid molecules

A new methodology for the prediction of molecular crystal structures using only the atomic connectivity of the molecule under consideration is presented. The approach is based on the global minimization of the lattice enthalpy of the crystal. The modeling of the electrostatic interactions is accomplished through a set of distributed charges that are optimally and automatically selected and positioned based on results of quantum mechanical calculations. A four-step global optimization algorithm is used for the identification of the local minima of the lattice enthalpy surface. A parallelized implementation of the algorithm permits a much more extensive search of the solution space than has hitherto been possible, allowing the identification of crystal structures in less frequently occurring space groups and with more than one molecule in the asymmetric unit. The algorithm has been applied successfully to the prediction of the crystal structures of 3-aza-bicyclo(3.3.1)nonane-2,4-dione (P2(1)/a, Z' = 1), allopurinol (P2(1)/c, Z' = 1), 1,3,4,6,7,9-hexa-azacycl(3.3.3)azine (Pbca, Z' = 2), and triethylenediamine (P6(3)/m, Z' = 1). In all cases, the experimentally known structure is among the most stable predicted structures, but not necessarily the global minimum.

Global optimization of clusters, crystals, and biomolecules

Finding the optimal solution to a complex optimization problem is of great importance in many fields, ranging from protein structure prediction to the design of microprocessor circuitry. Some recent progress in finding the global minima of potential energy functions is described, focusing on applications of the simple "basin-hopping" approach to atomic and molecular clusters and more complicated hypersurface deformation techniques for crystals and biomolecules. These methods have produced promising results and should enable larger and more complex systems to be treated in the future.

Examples of successful crystal structure prediction: polymorphs of primidone and progesterone

The field of crystal structure prediction and its potential value to the pharmaceutical industry is described. The process of structure prediction employed here is summarized and the results of its application to primidone and progesterone are reported. It is shown that the process successfully generates the known polymorphs of these molecules, starting from the molecular structure alone. Observations related to the application of the structure prediction process are reported.