Any compound can crystallise in more than one crystal forms, a phenomenon known as Polymorphism. Although different polymorphs have the same chemical properties, their physical properties (e.g. solubility) differ significantly as a result of the different spatial arrangement of the molecules1. This phenomenon has substantial industrial implications. For example, the production of Ritanovir, a HIV drug, was stopped as a consequence of the unexpected appearance of an unknown polymorph with poor therapeutic effectiveness, affecting patients and leading to large financial losses for its manufacturer. Thus the ability to reliably predict the number and the structure of polymorphs would be a valuable tool for the better design of products and processes.
Over the last two decades, there has been great progress on the development of computational methods for the prediction of the polymorphic forms in which a compound can crystallise. These predictions are mainly based on the lattice energy minimisation of a large number of trial structures. Success is dependent upon the accuracy of the lattice energy calculations, especially in terms of electrostatics and the impact of molecular flexibility, and the ability to optimise a hundreds of thousands to millions of putative structures. Such approaches have been proven to be successful in predicting the polymorphs of compounds with one or two polymorphs in many cases2.
In this study, predictions are made for the first time for the molecule with the largest number of known polymorphs (ten), 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (also known as ROY because of the Red, Orange and Yellow colours of its polymorphs)..For seven of these polymorphs the structure is known. In addition to the large number of polymorphs, its exceptional properties make ROY a widely used molecule in experimental studies related to polymorphism3.
The objective of the study is to determine whether known polymorphs can be identified as low-energy structures in the computational energy landscape of ROY crystals. We use a multi-stage methodology. A model is first chosen based on existing experimental information (seven known structures and relative stability of the seven solved polymorphs). Then a large number of structures are generated and locally minimised with a computationally inexpensive model, using the CrystalPredictor4,5 algorithm. Then the most promising structures (lowest in energy) are further minimised with CrystalOptimizer6,7, a program performing local minimisation, adopting a highly accurate though computationally expensive model.
The seven known structures are predicted as lattice energy minima. Moreover five of the known structures are within the fifteen lowest energy structures. Some of the remaining low energy structures are likely candidates for the unresolved polymorphs.
1. Bernstein, J., “Polymorphism in Molecular Crystals”. Clarendon Press, Oxford, 2002
2. G.M. Day et. al. , “Significant progress in predicting the crystal structures of small organic molecules-a report on the fourth blind test”, Acta. Cryst., B65:107-125 (2009)
3. Yu, L., “Polymorphism in Molecular Solids: An Extraordinary system of Red, Orange and Yellow crystals”, Acc. Chem. Res., Vol. 43, No. 9 , 1257-1266
4. P.G. Karamertzanis and C.C. Pantelides, “Ab initio-Crystal Structure Prediction – I. Rigid molecules”, J. Comput. Chem., 26:304-324 (2005)
5. P.G. Karamertzanis and C.C. Pantelides, “Ab initio-Crystal Structure Prediction – II. Flexible molecules”, Molecular Physics, Vol. 105 , Nos. 2-3, 273-291 (2007)
6. A.V. Kazantsev et.al., J. Chem. Theory Comput., submitted (October 2010)
7. A.V. Kazantsev et.al., “CrystalOptimizer: An efficient algorithm for lattice energy minimisation of organic crystals using quantum mechanical calculations”, Molecular Systems Engineering, C.S. Adjiman and A. Galindo, Wiley-VCH
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