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

Mapping Intimacies ◽

10.26434/chemrxiv-2021-jh6cj ◽

2021 ◽

Author(s):

Shiyue Yang ◽

Graeme Day

Keyword(s):

Crystal Structures ◽

Structure Prediction ◽

Global Analysis ◽

Molecular Crystals ◽

Group Symmetry ◽

Energy Landscapes ◽

Organic Molecular Crystals ◽

Threshold Algorithm ◽

Symmetry Constraints ◽

The Relationship

We describe the implementation of the Monte Carlo threshold algorithm for molecular crystals as a method to provide an estimate of the energy barriers separating crystal structures. By sampling the local energy minima accessible from multiple starting structures, the simulations yield a global picture of the crystal energy landscapes. This provides valuable information on the depth of the energy minima associated with crystal structures and adds to the information available from crystal structure prediction methods that are used for anticipating polymorphism. We present results from applying the threshold algorithm to four polymorphic organic molecular crystals, examine the influence of applying space group symmetry constraints during the simulations, and discuss the relationship between the structure of the energy landscape and the intermolecular interactions present in the crystals.

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An optimized intermolecular force field for hydrogen-bonded organic molecular crystals using atomic multipole electrostatics

Acta Crystallographica Section B Structural Science Crystal Engineering and Materials ◽

10.1107/s2052520616007708 ◽

2016 ◽

Vol 72 (4) ◽

pp. 477-487 ◽

Cited By ~ 15

Author(s):

Edward O. Pyzer-Knapp ◽

Hugh P. G. Thompson ◽

Graeme M. Day

Keyword(s):

Force Field ◽

Crystal Structures ◽

Force Fields ◽

Molecular Crystals ◽

Intermolecular Force ◽

Organic Molecular Crystals ◽

Organic Solid ◽

Lattice Energies ◽

Validation Set ◽

Unit Cell Dimensions

We present a re-parameterization of a popular intermolecular force field for describing intermolecular interactions in the organic solid state. Specifically we optimize the performance of the exp-6 force field when used in conjunction with atomic multipole electrostatics. We also parameterize force fields that are optimized for use with multipoles derived from polarized molecular electron densities, to account for induction effects in molecular crystals. Parameterization is performed against a set of 186 experimentally determined, low-temperature crystal structures and 53 measured sublimation enthalpies of hydrogen-bonding organic molecules. The resulting force fields are tested on a validation set of 129 crystal structures and show improved reproduction of the structures and lattice energies of a range of organic molecular crystals compared with the original force field with atomic partial charge electrostatics. Unit-cell dimensions of the validation set are typically reproduced to within 3% with the re-parameterized force fields. Lattice energies, which were all included during parameterization, are systematically underestimated when compared with measured sublimation enthalpies, with mean absolute errors of between 7.4 and 9.0%.

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Engineering crystals that facilitate the acyl-transfer reaction: insight from a comparison of the crystal structures ofmyo-inositol-1,3,5-orthoformate-derived benzoates and carbonates

Acta Crystallographica Section C Structural Chemistry ◽

10.1107/s205322961601603x ◽

2016 ◽

Vol 72 (11) ◽

pp. 875-881 ◽

Cited By ~ 1

Author(s):

Majid I. Tamboli ◽

Shobhana Krishanaswamy ◽

Rajesh G. Gonnade ◽

Mysore S. Shashidhar

Keyword(s):

Molecular Structure ◽

Crystal Structures ◽

Transfer Reaction ◽

Molecular Crystals ◽

Considerable Change ◽

Chemical Processes ◽

Acyl Transfer ◽

The Relationship ◽

Reactivity Insertion ◽

Orientation Of Molecules

Minor variations in the molecular structure of constituent molecules of reactive crystals often yield crystals with significantly different properties due to altered modes of molecular association in the solid state. Hence, these studies could provide a better understanding of the complex chemical processes occurring in the crystalline state. However, reactions that proceed efficiently in molecular crystals are only a small fraction of the reactions that are known to proceed (with comparable efficiency) in the solution state. Hence, for consistent progress in this area of research, investigation of newer reactive molecular crystals which support different kinds of reactions and their related systems is essential. The crystal structures and acyl-transfer reactivity of amyo-inositol-1,3,5-orthoformate-derived dibenzoate and its carbonate (4-O-benzoyl-2-O-phenoxycarbonyl-myo-inositol 1,3,5-orthoformate, C21H18O9) and thiocarbonate (4-O-benzoyl-2-O-phenoxythiocarbonyl-myo-inositol 1,3,5-orthoformate, C21H18O8S) analogs are compared with the aim of understanding the relationship between crystal structure and acyl-transfer reactivity. Insertion of an O atom in the acyl (or thioacyl) group of an ester gives the corresponding carbonate (or thiocarbonate). This seemingly minor change in molecular structure results in a considerable change in the packing of the molecules in the crystals ofmyo-inositol-1,3,5-orthoformate-derived benzoates and the corresponding carbonates. These differences result in a lack of intermolecular acyl-transfer reactivity in crystals ofmyo-inositol-1,3,5-orthoformate-derived carbonates. Hence, this study illustrates the sensitivity of the relative orientation of molecules, their packing and ensuing changes in the reactivity of resulting crystals to minor changes in molecular structure.

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The automatic selection of molecular crystal structures by combining stereochemical criteria and high-speed computing

Proceedings of the Royal Society of London Series A - Mathematical and Physical Sciences ◽

10.1098/rspa.1962.0119 ◽

1962 ◽

Vol 267 (1331) ◽

pp. 566-589 ◽

Cited By ~ 6

Keyword(s):

Crystal Structures ◽

Molecular Crystal ◽

High Speed ◽

Molecular Crystals ◽

Diamagnetic Anisotropy ◽

Initial Stage ◽

Trial Structure ◽

Relationship Of ◽

The Relationship ◽

Selection Of

The increasing use of digital computers in the final stages of the analysis of the structures of molecular crystals now means that the selection of a trial structure for automatic refinement has become the most time-consuming phase of such analyses. This paper shows that in certain types of problem this initial stage can also be carried out on computers, by making use of stereochemical information available at the outset. Examples of the successful application of such methods are given, and ways of increasing their power and flexibility when very fast computers become available are described. The relationship of such geometrical calculations to problems in crystal physics is also indicated, and it is shown that in appropriate cases measurements of, for example, diamagnetic anisotropy can be combined with geometrical results to provide an exceptionally rapid selection of possible molecular orientations.

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Predicting Porous Molecular Crystals and Clathrates

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273314083740 ◽

2014 ◽

Vol 70 (a1) ◽

pp. C1625-C1625

Author(s):

Jonas Nyman ◽

Graeme Day

Keyword(s):

Crystal Structure ◽

Crystal Structures ◽

Structure Prediction ◽

Molecular Crystals ◽

Volume Ratio ◽

Lattice Energy ◽

Computer Algorithms ◽

Crystal Structure Prediction ◽

Powerful Method ◽

Simple Molecules

The last decade has seen dramatic improvements in the theories and computer algorithms underlying computational Crystal Structure Predictions [1]. It is now possible to reliably obtain the most likely crystal structures of at least simple molecules starting from nothing more than a drawing of the molecule. We can now go even further and look for rare and exotic kinds of crystals such as porous molecular crystals, clathrates and inclusion compounds among our predictions and calculate their physical properties [2], paving the way for the "science of hypothetical materials". In our poster, we present results on the prediction of fluorophenol xenon clathrates. We have performed crystal structure predictions by global lattice energy searches on o- and m-fluorophenol. The predicted structures have then been analyzed for porosity and their likelihood of being clathrates. From the several thousands of predicted structures, we select a few likely candidates according to an empirical rule based on the guest to host volume ratio [3]. Results from solid state xenon-129 NMR indicate that we have successfully determined the crystal structures of both o- and m-fluorophenol xenon clathrates and we suggest that Crystal Structure Prediction in combination with xenon-129 NMR is a powerful method for determining the structures of clathrates in general.

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Polymorphic Behaviour of 3-Chloromandelic acid

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273314093243 ◽

2014 ◽

Vol 70 (a1) ◽

pp. C675-C675

Author(s):

Graham Tizzard ◽

Simon Coles ◽

Amy Ellis ◽

Rebecca Hylton ◽

Sarah Price ◽

...

Keyword(s):

Crystal Structures ◽

Structure Prediction ◽

Energy Landscape ◽

Detailed Comparison ◽

Crystal Structure Prediction ◽

Large Sets ◽

Crystallisation Behaviour ◽

The Relationship ◽

Related Compounds ◽

1D Chains

For several years we have been making detailed comparisons of the crystal structures of large sets of related compounds in an attempt to understand the factors determining the adoption of particular molecular arrangements within crystal structures. In all these projects, the XPac program [1] was used to identify similarity between structures in 0-dimensions (0D) (discrete molecular arrangements e.g. dimers, trimers etc),1D (chains or stacks), 2D (sheets or planes) and 3D (frameworks or full isostructurality) as a preliminary to the detailed comparison of the similarities so identified. As part of a larger crystallographic project to investigate the relationship between structure and chirality, we have synthesized and determined crystal structures of families of monosubstituted racemic mandelic acids with fluoro, chloro, bromo, iodo, trifluoromethyl, methyl and methoxy substituents at the ortho, meta and para positions. The substituted mandelic acids are polymorphically prolific and with the inclusion of unsubstituted mandelic acid, 28 structures have been compared. Of special interest has been 3-chloromandelic acid (3-ClMA), for which so far five polymorphs have been discovered: three racemic, two of which are isostructural [2], and two enantiopure. A crystal structure prediction (CSP) study of 3-ClMA has been carried out using the CrystalPredictor [3] and CrystalOptimizer [3] algorithms to generate the crystal energy landscape which is exceptionally dense with 3050 structures within 20 kJ mol-1. Many of these are more stable than the known forms, which is consistent with the complex crystallisation behaviour observed. From our observations of the crystallisation behaviour of substituted chloromandelic acids in general and the CSP study of 3-ClMA, we expect to discover further polymorphs of 3-ClMA and to this end cross-seeding experiments using crystals from differently substituted mandelic acids and a comprehensive polymorph screen are at present being undertaken.

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Novel approach to the determination of the crystal structures of organic molecular crystals: Low temperature form of pyrene.

Chemical Physics Letters ◽

10.1016/0009-2614(78)85268-3 ◽

1978 ◽

Vol 54 (3) ◽

pp. 490-493 ◽

Cited By ~ 23

Author(s):

William Jones ◽

Subramanian Ramdas ◽

John M. Thomas

Keyword(s):

Low Temperature ◽

Crystal Structures ◽

Molecular Crystals ◽

Organic Molecular Crystals ◽

Temperature Form ◽

Novel Approach

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Interpreting computed crystal energy landscapes for pharmaceutical molecules

Acta Crystallographica Section A Foundations and Advances ◽

10.1107/s2053273314083843 ◽

2014 ◽

Vol 70 (a1) ◽

pp. C1615-C1615

Author(s):

Sarah Price

Keyword(s):

Crystal Structure ◽

Crystal Structures ◽

Structure Prediction ◽

Energy Landscape ◽

Crystal Structure Prediction ◽

Energy Landscapes ◽

Pyridinecarboxylic Acid ◽

Solid Form ◽

Pharmaceutical Molecules ◽

Polymorph Screening

Crystal Structure Prediction (CSP) algorithms aim to generate the thermodynamically feasible crystal structures of a molecule from the chemical diagram, ranking their relative stability by a necessarily approximate estimate of the crystal energy. Such calculations are becoming feasible for molecules of a size and flexibility of small molecule pharmaceuticals. Contrasting the crystal energy landscape, the computer generated structures that are thermodynamically plausible as polymorphs, with the results of experimental polymorph screening, shows that CSP studies are not limited to being a search for the most thermodynamically stable crystal structure but can play a valuable role in understanding polymorphism and the potential complexity of crystallisation behaviour.[1] This presentation will illustrate the use of CSP as a complement to industrial-type solid form screening activities. Examples will include olanzapine, [2] tazofelone, two closely related 5-HT2a agonists and 6-[(5-chloro-2-([(4-chloro-2-fluorophenyl)methyl]oxy)phenyl)methyl]-2-pyridinecarboxylic acid (GSK269984B).[3] This illustrates the use of the crystal energy landscape to understand disorder, help structurally characterise metastable polymorphs and suggest whether there are additional polymorphs to be targeted. Since crystal energy landscapes usually include a wider range of crystal structures than known polymorphs, it raises the scientific question as to what determines which structures can be observed as metastable polymorphs. Thus both scientific as well as technological challenges need to be overcome before we can predict polymorphs.

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Data-driven learning and prediction of inorganic crystal structures

Faraday Discussions ◽

10.1039/c8fd00034d ◽

2018 ◽

Vol 211 ◽

pp. 45-59 ◽

Cited By ~ 25

Author(s):

Volker L. Deringer ◽

Davide M. Proserpio ◽

Gábor Csányi ◽

Chris J. Pickard

Keyword(s):

Crystal Structure ◽

Machine Learning ◽

Crystal Structures ◽

Structure Prediction ◽

Data Driven ◽

Interatomic Potentials ◽

Crystal Structure Prediction ◽

Energy Landscapes ◽

Inorganic Crystal

Machine learning-based interatomic potentials, fitting energy landscapes “on the fly”, are emerging and promising tools for crystal structure prediction.

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