Systematic Finite-Temperature Reduction of Crystal Energy Landscapes

Significance 

Crystal structure prediction (CSP) is the calculation of the crystal structures of solids from first principles. Predicting the crystal structure of a compound, based only on its composition, has been a goal of the physical sciences since the early 1950s. Predicting organic crystal structures is important in academic and industrial science, particularly for pharmaceuticals and pigments, where understanding polymorphism is beneficial. Unfortunately, the crystal structures of molecular substances, particularly organic compounds, are very hard to predict and rank in order of stability. Previous studies have shown that current crystal structure prediction methods tend to overestimate the number of potential polymorphs of organic molecules. Therefore there is need for techniques that can coarsen the landscapes of crystal structures generated by CSP into a smaller set of crystal structures that are persistent, distinct at finite temperatures, and more likely to correspond to real polymorphs.

On the bright side, CSP has evolved over the past decade to the point where the identification of local minima in the rugged potential energy surface associated with the packing of irregularly shaped organic molecules has been established as the standard approach in the field. In fact, applications of the CSP methods based on the estimate of relative lattice energies, here identified by the abbreviation CSP_0, are blossoming within both industry and academia, finding applications in pharmaceutical manufacturing and functional materials design. Nevertheless, CSP_0 techniques only partially capture the physics underlying polymorphism. To this end, the need for an accurate technique has been on the rise. In light of this, University College London researchers: Dr. Nicholas Francia, Dr. Louise S. Price, Professor Sarah L. Price and Dr. Matteo Salvalaglio, in collaboration with Dr. Jonas Nyman at the Eli Lilly and Company introduced and tested a new protocol to tackle the issue of overprediction by using molecular dynamics simulations and enhanced sampling methods. Their work is currently published in the research journal, Crystal Growth & Design.

Their aim was to reduce the overprediction by systematically applying molecular dynamics simulations and biased sampling methods to cluster subsets of structures that could easily interconvert at finite temperature and pressure. In this view, they were able to rationally reduce the number of predicted putative polymorphs in crystal structure prediction (CSP)-generated crystal energy landscapes. In particular, their approach employed an unsupervised clustering approach to analyze independent finite-temperature molecular dynamics trajectories and hence identify a representative structure of each cluster of distinct lattice energy minima that were effectively equivalent at finite temperature and pressure.

The authors reported that when their approach was tested in two small organic molecules exhibiting polymorphism: namely, urea and succinic acid, a reduction in the number of candidates required for evaluation as potential polymorphs was seen. Moreover, they noted that finite-temperature sampling of the density/energy collective variable space starting from crystal structures generated from CSP_0 yielded several examples of crystal supercells that had a structure consistent with the most populated clusters, but incorporating defects.

In summary, the study demonstrated the application of a systematic coarsening approach of CSP_0-generated crystal energy landscapes, based on the application of both unbiased and biased molecular dynamics simulation methods, coupled with the clustering of finite-temperature structures based on probabilistic structural fingerprints. Overall, the researchers presented new method for reducing the number of low energy crystal structures from temperature-free CSP, using molecular dynamics and enhanced sampling techniques, which result in a small number of thermally stable putative polymorphs. In a statement to Advances in Engineering, Dr. Matteo Salvalaglio emphasized that the ideas they reported were general and will provide a useful, physics-based strategy for the systematic reduction of crystal energy landscapes.

Systematic Finite-Temperature Reduction of Crystal Energy Landscapes - Advances in Engineering

About the author

Nicholas Francia. Nicholas Francia is a PhD candidate in the Department of Chemical Engineering at University College London where he works in the Molecular Modelling & Engineering Group. He previously obtained both his Bachelor of Science and Master of Science in Chemistry at the University of Milan, studying and working in the Chemical Dynamics Theory Group in the field of solid-state physics. Within the Molecular Modelling & Engineering Group, his project exploits molecular dynamics simulations and enhanced sampling methods to refine computational crystal structure prediction of molecular crystals.

About the author

Dr Louise Price. Dr Louise S Price gained her BSc in 1997 from the University of Liverpool and her PhD in 2001 from UCL. After a short time working in administration, she joined Professor Sarah (Sally) L Price’s group in 2003, supporting the Control and Prediction of the Organic Solid State (CPOSS) Basic Technology project. She started carrying out Crystal Structure Prediction (CSP) studies as the project developed the research to be more available to industry, and has since carried out CSP work on a number of small pharmaceutical molecules for various industrial projects. She has also worked with Professor Price on the most recent CCDC Blind Tests of Crystal Structure Prediction, and on the recent EU Horizon 2020 project, MagnaPharm. She helps maintain the lattice energy optimization code, DMACRYS, and supports users learning the code both within UCL and in external groups.

About the author

Jonas Nyman. Born in Sweden in 1982. Did his undergrad studies in chemical engineering and biotechnology at the University of Borås, where he also got a Masters degree in biotechnology under prof Mohammad Taherzadeh. Jonas then switched his main field of work from molecular biology to computational chemistry and did his PhD in prof Graeme M. Day’s lab in Southampton. Jonas spent two wonderful years in the pharmaceutical industry with Dr Susan Reutzel-Edens doing computational crystal engineering and crystal structure prediction (CSP). Jonas has since started his own consulting firm, focusing on the development of efficient CSP methods, and especially comparisons between computational and experimental results on organic molecular crystals.

About the author

Professor Sally Price. Sally, officially Sarah, Price trained as a theoretical chemist at the University of Cambridge, specialising in deriving models of the forces between molecules from their wavefunctions. She worked at the Universities of Chicago and Cambridge, before becoming a lecturer in Physical Chemistry at UCL (University College London), where she is now a Professor specialising in Computational Chemistry. In developing the theory and computer codes to model the organic solid state, she has collaborated widely with experimental solid state chemists, pharmaceutical scientists, theoretical physicists and computational scientists, including leading the Basic Technology Project “Control and Prediction of the Organic Solid State”. She was awarded he Royal Society of Chemistry Interdisciplinary Prize in 2015 and elected to the Fellowship of the Royal Society in 2017 in recognition of the value of this collaborative work in revealing the complexities of organic crystallisation.

About the author

Matteo Salvalaglio. Matteo obtained his PhD in Chemical Engineering in 2011 from Politecnico di Milano (Italy), working on molecular modelling of protein-ligand complexes of interest for the chromatographic purification of antibodies. Following his PhD, Matteo held a joint post-doctoral position in the Parrinello and Mazzotti research groups at ETH Zurich (Switzerland), working on enhanced sampling molecular dynamics methods for the investigation of crystallization from solution. In 2015 Matteo joined University College London, where he is now an Associate Professor of Chemical Engineering, leading the Molecular Modelling & Engineering Group. He applies and develops molecular simulation methods to investigate how molecular properties affect technologically relevant chemical and biochemical processes.

Reference

Nicholas F. Francia, Louise S. Price, Jonas Nyman, Sarah L. Price, Matteo Salvalaglio. Systematic Finite-Temperature Reduction of Crystal Energy Landscapes. Crystal Growth & Design 2020: Volume 20, page 6847−6862.

Go To Crystal Growth & Design

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