Effect of packing motifs on the energy ranking and electronic properties of putative crystal structures of tricyano-1,4-dithiino[c]-isothiazole

2016 ◽  
Vol 72 (4) ◽  
pp. 562-570 ◽  
Author(s):  
Farren Curtis ◽  
Xiaopeng Wang ◽  
Noa Marom
Keyword(s):  
Crystal Structure ◽  
Optical Properties ◽  
Structure Prediction ◽  
Density Functional ◽  
Crystal Packing ◽  
Crystal Structure Prediction ◽  
Dispersion Interactions ◽  
Blind Test ◽  
Electronic And Optical Properties ◽  
Inclusive Density

We present an analysis of putative structures of tricyano-1,4-dithiino[c]-isothiazole (TCS3), generated within the sixth crystal structure prediction blind test. Typical packing motifs are identified and characterized in terms of distinct patterns of close contacts and regions of electrostatic and dispersion interactions. We find that different dispersion-inclusive density functional theory (DFT) methods systematically favor specific packing motifs, which may affect the outcome of crystal structure prediction efforts. The effect of crystal packing on the electronic and optical properties of TCS3 is investigated using many-body perturbation theory within theGWapproximation and the Bethe–Salpeter equation (BSE). We find that a structure withPna21symmetry and a bilayer packing motif exhibits intermolecular bonding patterns reminiscent of π–π stacking and has markedly different electronic and optical properties than the experimentally observedP21/nstructure with a cyclic dimer motif, including a narrower band gap, enhanced band dispersion and broader optical absorption. ThePna21bilayer structure is close in energy to the observed structure and may be feasible to grow.

scholarly journals Towards crystal structure prediction of complex organic compounds – a report on the fifth blind test

2011 ◽  
Vol 67 (6) ◽  
pp. 535-551 ◽  
Author(s):  
David A. Bardwell ◽  
Claire S. Adjiman ◽  
Yelena A. Arnautova ◽  
Ekaterina Bartashevich ◽  
Stephan X. M. Boerrigter ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Density Functional ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Functional Theory ◽  
Flexible Molecule ◽  
Successful Prediction ◽  
The Many ◽  
Complex Organic

Following on from the success of the previous crystal structure prediction blind tests (CSP1999, CSP2001, CSP2004 and CSP2007), a fifth such collaborative project (CSP2010) was organized at the Cambridge Crystallographic Data Centre. A range of methodologies was used by the participating groups in order to evaluate the ability of the current computational methods to predict the crystal structures of the six organic molecules chosen as targets for this blind test. The first four targets, two rigid molecules, one semi-flexible molecule and a 1:1 salt, matched the criteria for the targets from CSP2007, while the last two targets belonged to two new challenging categories – a larger, much more flexible molecule and a hydrate with more than one polymorph. Each group submitted three predictions for each target it attempted. There was at least one successful prediction for each target, and two groups were able to successfully predict the structure of the large flexible molecule as their first place submission. The results show that while not as many groups successfully predicted the structures of the three smallest molecules as in CSP2007, there is now evidence that methodologies such as dispersion-corrected density functional theory (DFT-D) are able to reliably do so. The results also highlight the many challenges posed by more complex systems and show that there are still issues to be overcome.

scholarly journals Report on the sixth blind test of organic crystal structure prediction methods

2016 ◽  
Vol 72 (4) ◽  
pp. 439-459 ◽  
Author(s):  
Anthony M. Reilly ◽  
Richard I. Cooper ◽  
Claire S. Adjiman ◽  
Saswata Bhattacharya ◽  
A. Daniel Boese ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Density Functional ◽  
Organic Crystal ◽  
Drug Candidate ◽  
Prediction Methods ◽  
Chloride Salt ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Flexible Molecules

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disorderedZ′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.

scholarly journals First-year experience with fully automated crystal structure prediction

2014 ◽  
Vol 70 (a1) ◽  
pp. C1618-C1618
Author(s):  
Marcus Neumann ◽  
Bernd Doser
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Density Functional ◽  
Method Development ◽  
Force Fields ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Structure Generation ◽  
Statistical Correlations ◽  
Pharmaceutical Molecules

With improving hardware and software performance, usability has become one of the main obstacles to a more widespread use of Crystal Structure Prediction (CSP) with the GRACE program. In terms of method development, important milestones had already been passed by the time of the 5th blind test [1] in 2010, including the parameterization of dispersion-corrected Density Functional Theory (DFT-D) [2], the generation of tailor-made force fields from ab-initio reference data [3], a Monte-Carlo parallel tempering crystal structure generation engine and a DFT-d reranking procedure exploiting statistical correlations. These components have now been incorporated in automated data flow processes that remove the burden of scores of expert decisions from the user. Summarizing the results of CSP studies performed with the new Force Field Factory and CSP Factory modules throughout a year, the current performance of CSP is critically assessed and further method development needs are pinpointed. Studied compounds include 20 small molecules with competing hydrogen bonds motifs, 4 mono-hydrates of non-ionic molecules and the hydrates and chloride salts of several amino acids. The ability to handle flexible pharmaceutical molecules is demonstrated by a validation study on aripiprazole with one and two molecules per asymmetric unit. Salient features of the energy landscapes of other pharmaceutical molecules are discussed. Statistics are presented for the accuracy of tailor-made force fields, and the energy ranking performance of several DFT-d flavors is compared.

scholarly journals Crystal structure prediction of indomethacin

2014 ◽  
Vol 70 (a1) ◽  
pp. C1540-C1540
Author(s):  
Xiaozhou Li ◽  
Kristoffer Johansson ◽  
Andrew Bond ◽  
Jacco van de Streek
Keyword(s):  
Crystal Structure ◽  
Force Field ◽  
Crystal Structures ◽  
Structure Prediction ◽  
Molecular Crystal ◽  
Density Functional ◽  
Computational Cost ◽  
Stable Form ◽  
Crystal Structure Prediction ◽  
Blind Test

Indomethacin is a non-steroidal anti-inflammatory and antipyretic agent. Because different packing arrangements of the same drug can greatly affect drug properties such as colours, solubility, stability, melting point, dissolution rate and so forth, it is important to predict its polymorphs. The computational prediction of the stable form will reduce undesirable risks in both clinical trials and manufacturing. Reported polymorphs of indomethacin include α, β, γ, δ, ε, η and ζ [1], of which only the thermodynamically stable form γ and the metastable form α are determined. Density functional theory with dispersion-correction (DFT-D) has been used extensively to study molecular crystal structures[2]. It gives better results with a compromise between the computational cost and accuracy towards the reproduction of molecular crystal structures. In the fourth blind test of crystal structure prediction in 2007, the DFT-D method gave a very successful result that predicted all four structures correctly. Rather than using transferable force fields, a dedicated tailor-made force field (TMFF) parameterised by DFT-D calculations[3] is used for every chemical compound. The force field is used to generate a set of crystal structures and delimit a candidate window for energy ranking. The powder diffraction patterns of predicted polymorphs are calculated to compare with experimental data.

scholarly journals Blind crystal structure prediction of a novel second polymorph of 1-hydroxy-7-azabenzotriazole

2006 ◽  
Vol 62 (4) ◽  
pp. 642-650 ◽  
Author(s):  
Harriott Nowell ◽  
Christopher S. Frampton ◽  
Julie Waite ◽  
Sarah L. Price
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Structure Refinement ◽  
Lattice Energy ◽  
Polymorphic Form ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Coupling Reagent ◽  
Energy Penalty ◽  
Alcohol Solvents

The commercially available peptide coupling reagent 1-hydroxy-7-azabenzotriazole has been shown to crystallize in two polymorphic forms. The two polymorphs differ in their hydrogen-bonding motif, with form I having an R_2^2(10) dimer motif and form II having a C(5) chain motif. The previously unreported form II was used as an informal blind test of computational crystal structure prediction for flexible molecules. The crystal structure of form II has been successfully predicted blind from lattice-energy minimization calculations following a series of searches using a large number of rigid conformers. The structure for form II was the third lowest in energy with form I found as the global minimum, with the energy calculated as the sum of the ab initio intramolecular energy penalty for conformational distortion and the intermolecular lattice energy which is calculated from a distributed multipole representation of the charge density. The predicted structure was sufficiently close to the experimental structure that it could be used as a starting model for crystal structure refinement. A subsequent limited polymorph screen failed to yield a third polymorphic form, but demonstrated that alcohol solvents are implicated in the formation of the form I dimer structure.

scholarly journals Insight from energy surfaces: structure prediction by lattice energy exploration

2014 ◽  
Vol 70 (a1) ◽  
pp. C28-C28
Author(s):  
Graeme Day
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Crystal Packing ◽  
Lattice Energy ◽  
Organic Crystals ◽  
Crystal Structure Prediction ◽  
Stability Order ◽  
The Stability ◽  
Solid Form ◽  
Energy Surfaces

A long-standing challenge for the application of computational chemistry in the field of crystallography is the prediction of crystal packing, given no more than the chemical bonding of the molecules being crystallised. Recent years have seen significant progress towards reliable crystal structure prediction methods, even for traditionally challenging systems involving flexible molecules and multi-component solids [1]. These methods are based on global searches of the lattice energy surface: a search is performed to locate all possible packing arrangements, and these structures are ranked by their calculated energy [2]. One aim of this lecture is to provide an overview of advances in methods for crystal structure prediction, focussing on molecular organic crystals, and highlighting strategies that are being explored to extend the reach of these methods to more complex systems. A second aim is to discuss the range applications of crystal structure prediction calculations, which have traditionally included solid form screening, particularly of pharmaceutically active molecules, and structure determination. As energy models become more reliable at correctly ranking the stability order of putative structures, and the timescale required for structure searching decreases, crystal structure prediction has the potential for the discovery of novel molecular materials with targeted properties. Prospects for computer-guided discovery of materials will be discussed.

scholarly journals Comparing hypothetical structures generated in the third Cambridge blind test of crystal structure prediction

2005 ◽  
Vol 61 (5) ◽  
pp. 528-535 ◽  
Author(s):  
Bouke P. van Eijck
Keyword(s):  
Crystal Structure ◽  
Force Field ◽  
Structure Prediction ◽  
Crystal Structure Prediction ◽  
Blind Test ◽  
Good Correspondence ◽  
The Third ◽  
New Energy ◽  
Order Of Magnitude ◽  
True Energy

In the third Cambridge blind test of crystal structure prediction, participants submitted extended lists of up to 100 hypothetical structures. In this paper these lists are analyzed for the two small semi-rigid molecules, hydantoin and azetidine, by performing a new energy minimization using an accurate force field, and grouping these newly minimized structures into clusters of equivalent structures. Many participants found the same low-energy structures, but no list appeared to be complete even for the structures with one independent molecule in the asymmetric unit. This may well be due to the fact that a cutoff at even 100 structures cannot ensure the presence of a structure that has a relatively high ranking in another force field. Moreover, some structures should have possibly been discarded because they correspond to transition states rather than true energy minima. The r.m.s. deviation between energies in corresponding clusters was calculated to compare the reported relative crystal energies for each pair of participants. Some groups of force fields show a reasonably good correspondence, yet the order of magnitude of their discrepancies is comparable to the energy differences between, say, the first ten structures of lowest energy. Therefore, even if we assume that energy is a sufficient criterion, it is not surprising that crystal structure predictions are still inconsistent and unreliable.

scholarly journals From Concept to Crystals via Prediction: Multi-Component Organic Cage Pots by Social Self-Sorting

2019 ◽  
Author(s):  
Rebecca L. Greenaway ◽  
Valentina Santolini ◽  
Angeles Pulido ◽  
Marc A. Little ◽  
Ben M. Alston ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Structure Prediction ◽  
Chiral Recognition ◽  
Crystal Packing ◽  
A Priori ◽  
Computational Prediction ◽  
Crystal Structure Prediction ◽  
Social Self ◽  
The Social ◽  
Experimental Crystal

<p>We describe the <i>a priori </i>computational prediction and realization of multi-component cage pots, starting with molecular predictions based on candidate precursors through to crystal structure prediction and synthesis using robotic screening. The molecules were formed by the social self-sorting of a tri-topic aldehyde with both a tri-topic amine and di-topic amine, without using orthogonal reactivity or precursors of the same topicity. Crystal structure prediction suggested a rich polymorphic landscape, where there was an overall preference for chiral recognition to form heterochiral rather than homochiral packings, with heterochiral pairs being more likely to pack window-to-window to form two-component capsules. These crystal packing preferences were then observed in experimental crystal structures. <br></p>

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