Achieving QM Accuracy at a Fraction of Computational Cost: Lattice Energy Minimization of Organic Crystals Containing Highly Flexible Molecules
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There is a multitude of possible formulation pathways for pharmaceutical compounds among which polymorph, solvate, salt and cocrystal formation are the most common. Finding the optimal formulation by experimentation alone is often expensive and time consuming. In a quality by design environment, computational approaches can aid and direct the search for the best crystal form. We have recently developed a novel algorithm for the accurate minimization of lattice energy of crystals involving flexible organic molecules . The algorithm makes use of multipole moments (up to hexadecapole level) for the calculation of the intermolecular electrostatic interactions. It derives its accuracy from the use of isolated-molecule quantum mechanical calculations for the computation of intramolecular energy and the electrostatic field around the molecule. The main novelty of the algorithm is the use of dynamically constructed and updated local approximate models (LAMs) which essentially make available the full accuracy of the quantum mechanical model at each and every iteration of the minimization algorithm while requiring the performance of only a small number (typically 2-8) of quantum mechanical calculations. This has made possible for the first time the accurate treatment of molecules involving relatively large numbers of atoms with significant flexibility in torsional and bond angles and even bond lengths. The algorithm can handle systems with different molecules or chemical entities in the unit cell. In this paper, we discuss its use for the minimization of the lattice energy of crystals involving salts, solvates and cocrystals. The applicability of the approach in ab initio crystal structure prediction studies is also demonstrated.  Kazantsev, A.V. et al.; “CrystalOptimizer: An Efficient Algorithm for Lattice Energy Minimisation of Organic Crystals Using Isolated-Molecule Quantum Mechanical Calculations” in Process Systems Engineering. Volume 6: Molecular Systems Engineering; Adjiman C. S. and Galindo A. (Eds.); Wiley-VCH, Hamburg, 2010
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