The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.
With 12 crystal forms, 5-methyl-2-[(2-nitrophenyl) amino]-3-thiophenecabonitrile (a.k.a. ROY) holds the current record for the largest number of fully characterized organic crystal polymorphs. Four of these polymorphs were discovered or characterized since 2019,...
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.
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.
The discovery of molecular ionic cocrystals (ICCs) of active pharmaceutical ingredients (APIs) widens the opportunities for optimizing the physicochemical properties of APIs 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 here that mechanochemical ball milling is a versatile technique for the reproducible synthesis of ternary molecular ICCs in less than 30 min of grinding with or without solvent. Computational crystal structure prediction (CSP) calculations have been performed on ternary molecular ICCs for the first time and the observed crystal structures of all the ICCs were correctly predicted. Periodic dispersion‐corrected DFT calculations revealed that all the 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.
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