16 results found
Schmidt J, Weatherby J, Sugden I, et al., 2021, Computational screening of organic semiconductors: exploring side-group functionalisation and assembly to optimise charge transport in chiral molecules, Crystal Growth and Design, ISSN: 1528-7483
Molecular materials are challenging to design as their packing arrangement and hence properties are subject to subtle variations in the interplay of soft intermolecular interactions that are difficult to predict. The rational design of new molecular materials with tailored properties is currently hampered by the lack of knowledge of how a candidate molecule will pack in space and how we can control the polymorphs we can experimentally obtain. Here, we develop a simplified approach to aid the material design process, by the development of a screening process that is used to test 1344 helicene molecules that have potential as organic electronic materials. Our approach bridges the gap between single molecule design, molecular assembly, and the resulting charge-carrier mobilities. We find that fluorination significantly improves electron transport in the molecular material by up to 200%; the reference helicene packing showed a mobility of 0.30 cm2 V-1 s-1, fluorination increased the mobility to up to 0.96 and 0.97 (13-fluoroH and 4,13-difluoroH), assuming an outer reorganisation energy of 0.30 eV. Side groups containing triple bonds largely lead to improved transfer integrals. We validate our screening approach through the use of crystal structure prediction to confirm the presence of favourable packing motifs to maximize charge mobility.
Bowskill DH, Sugden IJ, Konstantinopoulos S, et al., 2021, Crystal structure prediction methods for organic molecules: state of the art., Annual Review of Chemical and Biomolecular Engineering, Vol: 14, ISSN: 1947-5438
The prediction of the crystal structures that a given organic molecule is likely to form is an important theoretical problem of significant interest for the pharmaceutical and agrochemical industries, among others. As evidenced by a series of six blind tests organized over the past 2 decades, methodologies for crystal structure prediction (CSP) have witnessed substantial progress and have now reached a stage of development where they can begin to be applied to systems of practical significance. This article reviews the state of the art in general-purpose methodologies for CSP, placing them within a common framework that highlights both their similarities and their differences. The review discusses specific areas that constitute the main focus of current research efforts toward improving the reliability and widening applicability of these methodologies, and offers some perspectives for the evolution of this technology over the next decade. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 12 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Cruz-Cabeza AJ, Taylor E, Sugden IJ, et al., 2020, Can solvated intermediates inform us about nucleation pathways? The case of β-pABA, CrystEngComm, Vol: 22, Pages: 7447-7459, ISSN: 1466-8033
Classical nucleation theory teaches the idea that molecular clusters form and grow in solution and that depending on prevailing conditions there is a chance for some to grow large enough to overcome the interfacial energy penalty and become mature crystals. However, from such a kinetic analysis, nothing is learnt of the nature of the composition or the molecular packing in such clusters. As a means of addressing this shortcoming consideration has, in the past, been given to the idea that in certain systems crystallography may offer additional, structural, insights. From this approach the notions of ‘nucleation pathway’ or ‘nucleation transition state’ have become useful concepts around which to formulate hypotheses as to how clusters may yield specific molecular packing, resulting for example, in the observation of crystal polymorphs. Here we offer an in-depth crystallographic analysis related to the nucleation of the α and β polymorphs of para-aminobenzoic acid in an attempt to reveal the pathways leading to the two forms. Using a combination of CSD analyses, crystal structure prediction and targeted crystallizations we explore plausible solution pathways to these polymorphs and discuss our results in the light of known kinetic data for the nucleation and growth of this material.
Shunnar AF, Dhokale B, Karothu DP, et al., 2020, Efficient screening for ternary molecular ionic cocrystals using a complementary mechanosynthesis and computational structure prediction approach, Chemistry: A European Journal, Vol: 26, Pages: 4752-4765, ISSN: 0947-6539
The discovery of molecular ionic cocrystals (ICCs) of active pharmaceutical ingredients (APIs) widens the opportunities for optimizing the physicochemical properties of the API whilst facilitating the delivery of multiple therapeutic agents. However, ICCs are often observed serendipitously in crystallization screens and the factors dictating their crystallization are poorly understood. We demonstrate that mechanochemical ball-milling is a versatile technique for the reproducible synthesis of ternary molecular ICCs in less than 30 minutes of grinding with or without solvent. Computational crystal structure prediction (CSP) calculations were performed on ternary molecular ICCs for the first time and the observed crystal structures of all ICCs were correctly predicted. Periodic DFT-D calculations reveal that all ICCs are thermodynamically stable (mean stabilization energy: -2 kJ mol -1 ) relative to the crystallization of a physical mixture of the binary salt and acid. The results suggest that a combined mechanosynthesis and CSP approach could be used to target the synthesis of higher-order molecular ICCs with functional properties.
Zhang Y, Sugden IJ, Reutzel-Edens SM, et al., 2020, A systematic study of state-of-the-art methods in crystal structure prediction for organic hydrates
Hydrates are co-crystalline materials containing water as one of the molecules in the crystal lattice. The incorporationof water into the crystal lattice produces a unit cell different from that of the anhydrate and, consequently, the physicalproperties of the hydrate can differ significantly from those of the anhydrate. The existence and stability of hydrates isan important consideration in the development of pharmaceutical products: the prevalence of water duringmanufacturing and storage can mean that neat forms of an active pharmaceutical ingredient can undergo a phasetransition to hydrate form, impacting the effectiveness of the drug. Crystal structure prediction (CSP) methods can inprinciple be useful in identifying likely hydrates, by undertaking searches for all polymorphs of water and one or moregiven compounds for a given co-crystal stoichiometry. Minimal information is needed, typically just the chemicalconnectivity diagram , to search for the low lattice energy arrangements of the constituent atoms in space. Applications of CSP to hydrates have resulted in mixed success so far. In the fifth blind test organised by CambridgeCrystallographic Data Centre, one of the targets was a hydrate but none of the 10 groups that attempted to predict itsstructure put forward the correct structure within their shortlist. In the sixth blind test , only 8 groups submittedpredicted structures for the hydrate target, and only one group generated the experimental structure within theirshortlist. In order to gain a better understanding of the challenges that make CSP for hydrates difficult, we present a systematicevaluation of a CSP state-of-the-art method for organic hydrates, in which the lattice energy is partitioned intointramolecular and intermolecular contributions. Intramolecular interactions are modelled via quantum mechanicalcalculations , and intermolecular interactions are divided into electrostatics, modelled using ab initio derived distributedmultipoles , and repu
Bowskill DH, Sugden IJ, George N, et al., 2020, Efficient Parameterization of a Surrogate Model of Molecular Interactions in Crystals, Editors: Pierucci, Manenti, Bozzano, Manca, Publisher: ELSEVIER SCIENCE BV, Pages: 493-498
Konstantinopoulos S, Sugden IJ, Reutzel-Edens SM, et al., 2020, An atomistic lattice dynamics approach for free energy calculations within crystal structure prediction studies
A plethora of organic molecules exhibit polymorphism, which refers to the ability of chemical compounds to pack intodifferent crystalline motifs. This phenomenon is of special importance both to industry and academia since physicaland chemical properties, such as solubility, bioavailability and mechanical strength may vary tremendously betweenpolymorphs. From a thermodynamic standpoint, polymorphs can be identified as minima on the free energy (FE)landscape, with the most stable form corresponding to the global minimum and other forms corresponding to localminima (metastable structures). This thermodynamic understanding has motivated the development of crystalstructure prediction (CSP) tools that are designed to determine all polymorphs for a given compound with the correctorder of stability based on minimal information, such as the chemical connectivity diagram . Recent advances in CSP were highlighted in the last blind test organised by Cambridge Crystallographic Data Centre .It is worth noting that only 7 out of the 25 groups participating in the last test have incorporated FE calculations withintheir workflow, while the remaining groups used only lattice energy in their predictions, thus neglecting temperatureand vibrational effects. Lattice dynamics (LD) theory was deployed successfully for the evaluation of vibrational freeenergies, utilizing either dispersion-corrected periodic density functional theory (DFT-d) or force field methods basedon distributed multipoles expansion (DMA). DFT-d can provide very accurate results at a high computational cost,whereas the DMA-based approach provides a good trade-off between accuracy and efficiency but cannot account forinternal modes arising from intramolecular vibrations. A limitation of both methods is that they rely on the constructionof supercells, which increases computational demands and results in some ambiguity in the generation of dispersioncurves. In this work, we present a recently-developed methodology for pe
Sugden IJ, Adjiman C, Pantelides C, 2019, Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. II. Smoothed intramolecular potentials, Acta Crystallographica Section B: Structural Science, Vol: 75, Pages: 423-433, ISSN: 0108-7681
The application of Crystal Structure Prediction (CSP) to industrially-relevant molecules requires the handling of increasingly large and flexible compounds. We present a revised model for the effect of molecular flexibility on the lattice energy that removes the discontinuities and non-differentiabilities present in earlier models (Sugden et al., 2016), with a view to improving the performance of CSP. The approach is based on the concept of computing a weighted average of local models, and has been implemented within the CrystalPredictor code. Through the comparative investigation of several compounds studied in earlier literature, we show that this new model results in large reductions in computational effort (of up to 65%) and in significant increases in reliability. The approach is further applied to investigate, for the first time, the computational polymorphic landscape of flufenamic acid for Z’=1 structures, resulting in the successful identification of all three experimentally resolved polymorphs within reasonable computational time.
Sugden I, Adjiman C, Pantelides C, 2018, Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. Part II. Smoothed intramolecular potentials, Acta Crystallographica Section A Foundations and Advances, Vol: 74, Pages: e120-e120, ISSN: 2053-2733
Bowskill D, Sugden I, Gatsiou C-A, et al., 2018, New potentials for accurate and efficient ab initio crystal structure prediction methods, Publisher: INT UNION CRYSTALLOGRAPHY, Pages: E362-E362, ISSN: 2053-2733
Sugden IJ, Adjiman CSA, Pantelides C, 2016, Accurate and efficient representation of intramolecular energy in ab initio generation of crystal structures. I. Adaptive local approximate models, Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials, Vol: 72, Pages: 864-874, ISSN: 2052-5206
The global search stage of Crystal Structure Prediction (CSP) methods requires a fine balance between accuracy and computational cost, particularly for the study of large flexible molecules. A major improvement in the accuracy and cost of the intramolecular energy function used in the CrystalPredictor II (Habgood, M., Sugden, I. J., Kazantsev, A. V., Adjiman, C. S. & Pantelides, C. C. (2015). J Chem Theory Comput 11, 1957-1969) program is presented, where the most efficient use of computational effort is ensured via the use of adaptive Local Approximate Model (LAM) placement. The entire search space of relevant molecule’s conformations is initially evaluated using a coarse, low accuracy grid. Additional LAM points are then placed at appropriate points determined via an automated process, aiming to minimise the computational effort expended in high energy regions whilst maximising the accuracy in low energy regions. As the size, complexity, and flexibility of molecules increase, the reduction in computational cost becomes marked. This improvement is illustrated with energy calculations for benzoic acid and the ROY molecule, and a CSP study of molecule XXVI from the sixth blind test (Reilly et al., (2016). Acta Cryst. B, 72, 439-459), which is challenging due to its size and flexibility. Its known experimental form is successfully predicted as the global minimum. The computational cost of the study is tractable without the need to make unphysical simplifying assumptions.
Sugden IJ, Plant DF, Bell RG, 2016, Impact scenarios in boron carbide: A computational study, JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY, Vol: 15, ISSN: 0219-6336
Reilly AM, Cooper RI, Adjiman CS, et al., 2016, Report on the sixth blind test of organic crystal structure prediction methods., Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials, Vol: 72, Pages: 439-459, ISSN: 2052-5206
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 disordered Z' = 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.
Habgood M, Sugden IJ, Kazantsev AV, et al., 2015, Efficient handling of molecular flexibility in ab initio generation of crystal structures, Journal of Chemical Theory and Computation, Vol: 11, Pages: 1957-1969, ISSN: 1549-9618
A key step in many approaches to crystal structure prediction (CSP) is the initial generation of large numbers of candidate crystal structures via the exploration of the lattice energy surface. By using a relatively simple lattice energy approximation, this global search step aims to identify, in a computationally tractable manner, a limited number of likely candidate structures for further refinement using more detailed models. This paper presents an effective and efficient approach to modeling the effects of molecular flexibility during this initial global search. Local approximate models (LAMs), constructed via quantum mechanical (QM) calculations, are used to model the conformational energy, molecular geometry, and atomic charge distributions as functions of a subset of the conformational degrees of freedom (e.g., flexible torsion angles). The effectiveness of the new algorithm is demonstrated via its application to the recently studied 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (ROY) molecule and to two molecules, β-d-glucose and 1-(4-benzoylpiperazin-1-yl)-2-(4,7-dimethoxy-1H-pyrrolo[2,3-c]pyridin-3-yl)ethane-1,2-dione, a Bristol Myers Squibb molecule referenced as BMS-488043. All three molecules present significant challenges due to their high degree of flexibility.
Sugden IJ, Plant DF, Bell RG, 2013, Thermal rearrangement mechanisms in icosahedral carboranes and metallocarboranes, CHEMICAL COMMUNICATIONS, Vol: 49, Pages: 975-977, ISSN: 1359-7345
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