1
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Wu EJ, Kelly AW, Iuzzolino L, Lee AY, Zhu X. Unprecedented Packing Polymorphism of Oxindole: An Exploration Inspired by Crystal Structure Prediction. Angew Chem Int Ed Engl 2024; 63:e202406214. [PMID: 38825853 DOI: 10.1002/anie.202406214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/13/2024] [Accepted: 05/29/2024] [Indexed: 06/04/2024]
Abstract
Crystal polymorphism, characterized by different packing arrangements of the same compound, strongly ties to the physical properties of a molecule. Determining the polymorphic landscape is complex and time-consuming, with the number of experimentally observed polymorphs varying widely from molecule to molecule. Furthermore, disappearing polymorphs, the phenomenon whereby experimentally observed forms cannot be reproduced, pose a significant challenge for the pharmaceutical industry. Herein, we focused on oxindole (OX), a small rigid molecule with four known polymorphs, including a reported disappearing form. Using crystal structure prediction (CSP), we assessed OX solid-state landscape and thermodynamic stability by comparing predicted structures with experimentally known forms. We then performed melt and solution crystallization in bulk and nanoconfinement to validate our predictions. These experiments successfully reproduced the known forms and led to the discovery of four novel polymorphs. Our approach provided insights into reconstructing disappearing polymorphs and building more comprehensive polymorph landscapes. These results also establish a new record of packing polymorphism for rigid molecules.
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Affiliation(s)
- Emily J Wu
- Analytical Research & Development, Merck & Co., Inc., Rahway, New Jersey, 07065, United States
| | - Andrew W Kelly
- Analytical Research & Development, Merck & Co., Inc., Rahway, New Jersey, 07065, United States
| | - Luca Iuzzolino
- Modeling & Informatics, Discovery Chemistry, Merck & Co., Inc., Rahway, New Jersey, 07065, United States
| | - Alfred Y Lee
- Analytical Research & Development, Merck & Co., Inc., Rahway, New Jersey, 07065, United States
| | - Xiaolong Zhu
- Analytical Research & Development, Merck & Co., Inc., Rahway, New Jersey, 07065, United States
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2
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Ye Z, Wang N, Zhou J, Ouyang D. Organic crystal structure prediction via coupled generative adversarial networks and graph convolutional networks. Innovation (N Y) 2024; 5:100562. [PMID: 38379785 PMCID: PMC10878116 DOI: 10.1016/j.xinn.2023.100562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 12/29/2023] [Indexed: 02/22/2024] Open
Abstract
Organic crystal structures exert a profound impact on the physicochemical properties and biological effects of organic compounds. Quantum mechanics (QM)-based crystal structure predictions (CSPs) have somewhat alleviated the dilemma that experimental crystal structure investigations struggle to conduct complete polymorphism studies, but the high computing cost poses a challenge to its widespread application. The present study aims to construct DeepCSP, a feasible pure machine learning framework for minute-scale rapid organic CSP. Initially, based on 177,746 data entries from the Cambridge Crystal Structure Database, a generative adversarial network was built to conditionally generate trial crystal structures under selected feature constraints for the given molecule. Simultaneously, a graph convolutional attention network was used to predict the density of stable crystal structures for the input molecule. Subsequently, the distances between the predicted density and the definition-based calculated density would be considered to be the crystal structure screening and ranking basis, and finally, the density-based crystal structure ranking would be output. Two such distinct algorithms, performing the generation and ranking functionalities, respectively, collectively constitute the DeepCSP, which has demonstrated compelling performance in marketed drug validations, achieving an accuracy rate exceeding 80% and a hit rate surpassing 85%. Inspiringly, the computing speed of the pure machine learning methodology demonstrates the potential of artificial intelligence in advancing CSP research.
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Affiliation(s)
- Zhuyifan Ye
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China
- Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China
| | - Nannan Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China
| | - Jiantao Zhou
- State Key Laboratory of Internet of Things for Smart City, University of Macau, Macau 999078, China
- Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 999078, China
| | - Defang Ouyang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China
- Department of Public Health and Medicinal Administration, Faculty of Health Sciences, University of Macau, Macau 999078, China
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3
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Beran GJO. Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials. Chem Sci 2023; 14:13290-13312. [PMID: 38033897 PMCID: PMC10685338 DOI: 10.1039/d3sc03903j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 11/02/2023] [Indexed: 12/02/2023] Open
Abstract
The reliability of organic molecular crystal structure prediction has improved tremendously in recent years. Crystal structure predictions for small, mostly rigid molecules are quickly becoming routine. Structure predictions for larger, highly flexible molecules are more challenging, but their crystal structures can also now be predicted with increasing rates of success. These advances are ushering in a new era where crystal structure prediction drives the experimental discovery of new solid forms. After briefly discussing the computational methods that enable successful crystal structure prediction, this perspective presents case studies from the literature that demonstrate how state-of-the-art crystal structure prediction can transform how scientists approach problems involving the organic solid state. Applications to pharmaceuticals, porous organic materials, photomechanical crystals, organic semi-conductors, and nuclear magnetic resonance crystallography are included. Finally, efforts to improve our understanding of which predicted crystal structures can actually be produced experimentally and other outstanding challenges are discussed.
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Affiliation(s)
- Gregory J O Beran
- Department of Chemistry, University of California Riverside Riverside CA 92521 USA
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4
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Abstract
Twenty years ago, I wrote a Chem. Commun. feature article entitled "Crystal Engineering: where from? Where to?": an update is in order. In this Highlight I argue that molecular crystal engineering, one of the areas of fast development of the field, has definitely reached the stage of "delivering the goods": new functional materials assembled via non-covalent interactions and/or improved properties of existing materials. As a proof of concept, the crystal engineering approach to tackle two contemporary emergencies, namely, urea fertilizer degradation and development of antimicrobial resistance by pathogens, is discussed and application-driven examples are provided.
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Affiliation(s)
- Dario Braga
- Chemistry Department G. Ciamician, University of Bologna, Via F. Selmi 2, 4016 Bologna, Italy.
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5
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Butler PWV, Day GM. Reducing overprediction of molecular crystal structures via threshold clustering. Proc Natl Acad Sci U S A 2023; 120:e2300516120. [PMID: 37252993 PMCID: PMC10266058 DOI: 10.1073/pnas.2300516120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 05/01/2023] [Indexed: 06/01/2023] Open
Abstract
Crystal structure prediction is becoming an increasingly valuable tool for assessing polymorphism of crystalline molecular compounds, yet invariably, it overpredicts the number of polymorphs. One of the causes for this overprediction is in neglecting the coalescence of potential energy minima, separated by relatively small energy barriers, into a single basin at finite temperature. Considering this, we demonstrate a method underpinned by the threshold algorithm for clustering potential energy minima into basins, thereby identifying kinetically stable polymorphs and reducing overprediction.
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Affiliation(s)
- Patrick W. V. Butler
- School of Chemistry, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
| | - Graeme M. Day
- School of Chemistry, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
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6
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Catlow CRA. Crystal structure prediction: achievements and opportunities. IUCRJ 2023; 10:143-144. [PMID: 36862486 PMCID: PMC9980386 DOI: 10.1107/s2052252523001835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
This editorial gives gives an update on the current status of crystal structure prediction and its opportunities and challenges.
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Affiliation(s)
- C. Richard A. Catlow
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, United Kingdom
- School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, United Kingdom
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7
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The Relevance of Crystal Forms in the Pharmaceutical Field: Sword of Damocles or Innovation Tools? Int J Mol Sci 2022; 23:ijms23169013. [PMID: 36012275 PMCID: PMC9408954 DOI: 10.3390/ijms23169013] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/01/2022] [Accepted: 08/05/2022] [Indexed: 12/22/2022] Open
Abstract
This review is aimed to provide to an “educated but non-expert” readership and an overview of the scientific, commercial, and ethical importance of investigating the crystalline forms (polymorphs, hydrates, and co-crystals) of active pharmaceutical ingredients (API). The existence of multiple crystal forms of an API is relevant not only for the selection of the best solid material to carry through the various stages of drug development, including the choice of dosage and of excipients suitable for drug development and marketing, but also in terms of intellectual property protection and/or extension. This is because the physico-chemical properties, such as solubility, dissolution rate, thermal stability, processability, etc., of the solid API may depend, sometimes dramatically, on the crystal form, with important implications on the drug’s ultimate efficacy. This review will recount how the scientific community and the pharmaceutical industry learned from the catastrophic consequences of the appearance of new, more stable, and unsuspected crystal forms. The relevant aspects of hydrates, the most common pharmaceutical solid solvates, and of co-crystals, the association of two or more solid components in the same crystalline materials, will also be discussed. Examples will be provided of how to tackle multiple crystal forms with screening protocols and theoretical approaches, and ultimately how to turn into discovery and innovation the purposed preparation of new crystalline forms of an API.
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8
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Newman JA, Iuzzolino L, Tan M, Orth P, Bruhn J, Lee AY. From Powders to Single Crystals: A Crystallographer's Toolbox for Small-Molecule Structure Determination. Mol Pharm 2022; 19:2133-2141. [PMID: 35576503 PMCID: PMC10152450 DOI: 10.1021/acs.molpharmaceut.2c00020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Although the crystal structures of small-molecule compounds are often determined from single-crystal X-ray diffraction (scXRD), recent advances in three-dimensional electron diffraction (3DED) and crystal structure prediction (CSP) methods promise to expand the structure elucidation toolbox available to the crystallographer. Herein, a comparative assessment of scXRD, 3DED, and CSP in combination with powder X-ray diffraction is carried out on two former drug candidate compounds and a multicomponent crystal of a key building block in the synthesis of gefapixant citrate.
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Affiliation(s)
- Justin A. Newman
- Department
of Analytical Research and Development, Merck & Co., Inc., 126 East Lincoln Avenue, Rahway, New Jersey 07065, United States
| | - Luca Iuzzolino
- Department
of Computational and Structural Chemistry, Merck & Co., Inc., Rahway, 126 East Lincoln Avenue, Rahway, New Jersey 07065, United States
| | - Melissa Tan
- Department
of Analytical Research and Development, Merck & Co., Inc., 126 East Lincoln Avenue, Rahway, New Jersey 07065, United States
| | - Peter Orth
- Department
of Computational and Structural Chemistry, Merck & Co., Inc., 2000 Galloping Hill Road, Kenilworth, New Jersey 07033, United States
| | - Jessica Bruhn
- Nanoimaging
Services, San Diego, California 92121, United States
| | - Alfred Y. Lee
- Department
of Analytical Research and Development, Merck & Co., Inc., 126 East Lincoln Avenue, Rahway, New Jersey 07065, United States
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9
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Xiouras C, Cameli F, Quilló GL, Kavousanakis ME, Vlachos DG, Stefanidis GD. Applications of Artificial Intelligence and Machine Learning Algorithms to Crystallization. Chem Rev 2022; 122:13006-13042. [PMID: 35759465 DOI: 10.1021/acs.chemrev.2c00141] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Artificial intelligence and specifically machine learning applications are nowadays used in a variety of scientific applications and cutting-edge technologies, where they have a transformative impact. Such an assembly of statistical and linear algebra methods making use of large data sets is becoming more and more integrated into chemistry and crystallization research workflows. This review aims to present, for the first time, a holistic overview of machine learning and cheminformatics applications as a novel, powerful means to accelerate the discovery of new crystal structures, predict key properties of organic crystalline materials, simulate, understand, and control the dynamics of complex crystallization process systems, as well as contribute to high throughput automation of chemical process development involving crystalline materials. We critically review the advances in these new, rapidly emerging research areas, raising awareness in issues such as the bridging of machine learning models with first-principles mechanistic models, data set size, structure, and quality, as well as the selection of appropriate descriptors. At the same time, we propose future research at the interface of applied mathematics, chemistry, and crystallography. Overall, this review aims to increase the adoption of such methods and tools by chemists and scientists across industry and academia.
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Affiliation(s)
- Christos Xiouras
- Chemical Process R&D, Crystallization Technology Unit, Janssen R&D, Turnhoutseweg 30, 2340 Beerse, Belgium
| | - Fabio Cameli
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
| | - Gustavo Lunardon Quilló
- Chemical Process R&D, Crystallization Technology Unit, Janssen R&D, Turnhoutseweg 30, 2340 Beerse, Belgium.,Chemical and BioProcess Technology and Control, Department of Chemical Engineering, Faculty of Engineering Technology, KU Leuven, Gebroeders de Smetstraat 1, 9000 Ghent, Belgium
| | - Mihail E Kavousanakis
- School of Chemical Engineering, National Technical University of Athens, Heroon Polytechniou 9, 15780 Zografou, Greece
| | - Dionisios G Vlachos
- Department of Chemical and Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, Delaware 19716, United States
| | - Georgios D Stefanidis
- School of Chemical Engineering, National Technical University of Athens, Heroon Polytechniou 9, 15780 Zografou, Greece.,Laboratory for Chemical Technology, Ghent University; Tech Lane Ghent Science Park 125, B-9052 Ghent, Belgium
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10
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Nikhar R, Szalewicz K. Reliable crystal structure predictions from first principles. Nat Commun 2022; 13:3095. [PMID: 35654882 PMCID: PMC9163189 DOI: 10.1038/s41467-022-30692-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 05/10/2022] [Indexed: 11/28/2022] Open
Abstract
An inexpensive and reliable method for molecular crystal structure predictions (CSPs) has been developed. The new CSP protocol starts from a two-dimensional graph of crystal's monomer(s) and utilizes no experimental information. Using results of quantum mechanical calculations for molecular dimers, an accurate two-body, rigid-monomer ab initio-based force field (aiFF) for the crystal is developed. Since CSPs with aiFFs are essentially as expensive as with empirical FFs, tens of thousands of plausible polymorphs generated by the crystal packing procedures can be optimized. Here we show the robustness of this protocol which found the experimental crystal within the 20 most stable predicted polymorphs for each of the 15 investigated molecules. The ranking was further refined by performing periodic density-functional theory (DFT) plus dispersion correction (pDFT+D) calculations for these 20 top-ranked polymorphs, resulting in the experimental crystal ranked as number one for all the systems studied (and the second polymorph, if known, ranked in the top few). Alternatively, the polymorphs generated can be used to improve aiFFs, which also leads to rank one predictions. The proposed CSP protocol should result in aiFFs replacing empirical FFs in CSP research.
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Affiliation(s)
- Rahul Nikhar
- Department of Physics and Astronomy, University of Delaware, Newark, DE, 19716, USA
| | - Krzysztof Szalewicz
- Department of Physics and Astronomy, University of Delaware, Newark, DE, 19716, USA.
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11
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Mathew R, Sergeyev IV, Aussenac F, Gkoura L, Rosay M, Baias M. Complete resonance assignment of a pharmaceutical drug at natural isotopic abundance from DNP-Enhanced solid-state NMR. SOLID STATE NUCLEAR MAGNETIC RESONANCE 2022; 119:101794. [PMID: 35462269 DOI: 10.1016/j.ssnmr.2022.101794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 03/31/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
Solid-state dynamic nuclear polarization enhanced magic angle spinning (DNP-MAS) NMR measurements coupled with density functional theory (DFT) calculations enable the full resonance assignment of a complex pharmaceutical drug molecule without the need for isotopic enrichment. DNP dramatically enhances the NMR signals, thereby making possible previously intractable two-dimensional correlation NMR spectra at natural abundance. Using inputs from DFT calculations, herein we describe a significant improvement to the structure elucidation process for complex organic molecules. Further, we demonstrate that a series of two-dimensional correlation experiments, including 15N-13C TEDOR, 13C-13C INADEQUATE/SARCOSY, 19F-13C HETCOR, and 1H-13C HETCOR, can be obtained at natural isotopic abundance within reasonable experiment times, thus enabling a complete resonance assignment of sitagliptin, a pharmaceutical used for the treatment of type 2 diabetes.
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Affiliation(s)
- Renny Mathew
- Division of Science, New York University Abu Dhabi, P.O. Box 129188, Abu Dhabi, United Arab Emirates
| | - Ivan V Sergeyev
- Bruker Biospin Corporation, 15 Fortune Drive, Billerica, MA, USA
| | - Fabien Aussenac
- Bruker France, 34 rue de l'industrie, 67166, Wissembourg, France.
| | - Lydia Gkoura
- Division of Science, New York University Abu Dhabi, P.O. Box 129188, Abu Dhabi, United Arab Emirates.
| | - Melanie Rosay
- Bruker Biospin Corporation, 15 Fortune Drive, Billerica, MA, USA
| | - Maria Baias
- Division of Science, New York University Abu Dhabi, P.O. Box 129188, Abu Dhabi, United Arab Emirates
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12
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Weatherby JA, Rumson AF, Price AJA, Otero de la Roza A, Johnson ER. A density-functional benchmark of vibrational free-energy corrections for molecular crystal polymorphism. J Chem Phys 2022; 156:114108. [DOI: 10.1063/5.0083082] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Many crystal structure prediction protocols only concern themselves with the electronic energy of molecular crystals. However, vibrational contributions to the free energy ( Fvib) can be significant in determining accurate stability rankings for crystal candidates. While force-field studies have been conducted to gauge the magnitude of these free-energy corrections, highly accurate results from quantum mechanical methods, such as density-functional theory (DFT), are desirable. Here, we introduce the PV17 set of 17 polymorphic pairs of organic molecular crystals, for which plane wave DFT is used to calculate the vibrational free energies and free-energy differences (Δ Fvib) between each pair. Our DFT results confirm that the vibrational free-energy corrections are small, having a mean value of 1.0 kJ/mol and a maximum value of 2.3 kJ/mol for the PV17 set. Furthermore, we assess the accuracy of a series of lower-cost DFT, semi-empirical, and force-field models for computing Δ Fvib that have been proposed in the literature. It is found that calculating Fvib using the Γ-point frequencies does not provide Δ Fvib values of sufficiently high quality. In addition, Δ Fvib values calculated using various approximate methods have mean absolute errors relative to our converged DFT results of equivalent or larger magnitude than the vibrational free-energy corrections themselves. Thus, we conclude that, in a crystal structure prediction protocol, it is preferable to forego the inclusion of vibrational free-energy corrections than to estimate them with any of the approximate methods considered here.
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Affiliation(s)
- Joseph A. Weatherby
- Department of Chemistry, Dalhousie University, 6274 Coburg Rd, Halifax, Nova Scotia B3H 4R2, Canada
| | - Adrian F. Rumson
- Department of Chemistry, Dalhousie University, 6274 Coburg Rd, Halifax, Nova Scotia B3H 4R2, Canada
| | - Alastair J. A. Price
- Department of Chemistry, Dalhousie University, 6274 Coburg Rd, Halifax, Nova Scotia B3H 4R2, Canada
| | - Alberto Otero de la Roza
- Departamento de Química Física y Analítica and MALTA Consolider Team, Facultad de Química, Universidad de Oviedo, 33006 Oviedo, Spain
| | - Erin R. Johnson
- Department of Chemistry, Dalhousie University, 6274 Coburg Rd, Halifax, Nova Scotia B3H 4R2, Canada
- Department of Physics and Atmospheric Science, Dalhousie University, 6310 Coburg Rd, Halifax, Nova Scotia B3H 4R2, Canada
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13
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Beran GJO, Wright SE, Greenwell C, Cruz-Cabeza AJ. The interplay of intra- and intermolecular errors in modeling conformational polymorphs. J Chem Phys 2022; 156:104112. [DOI: 10.1063/5.0088027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Conformational polymorphs of organic molecular crystals represent a challenging test for quantum chemistry because they require careful balancing of the intra- and intermolecular interactions. This study examines 54 molecular conformations from 20 sets of conformational polymorphs, along with the relative lattice energies and 173 dimer interactions taken from six of the polymorph sets. These systems are studied with a variety of van der Waals-inclusive density functionals theory models; dispersion-corrected spin-component-scaled second-order Møller–Plesset perturbation theory (SCS-MP2D); and domain local pair natural orbital coupled cluster singles, doubles, and perturbative triples [DLPNO-CCSD(T)]. We investigate how delocalization error in conventional density functionals impacts monomer conformational energies, systematic errors in the intermolecular interactions, and the nature of error cancellation that occurs in the overall crystal. The density functionals B86bPBE-XDM, PBE-D4, PBE-MBD, PBE0-D4, and PBE0-MBD are found to exhibit sizable one-body and two-body errors vs DLPNO-CCSD(T) benchmarks, and the level of success in predicting the relative polymorph energies relies heavily on error cancellation between different types of intermolecular interactions or between intra- and intermolecular interactions. The SCS-MP2D and, to a lesser extent, ωB97M-V models exhibit smaller errors and rely less on error cancellation. Implications for crystal structure prediction of flexible compounds are discussed. Finally, the one-body and two-body DLPNO-CCSD(T) energies taken from these conformational polymorphs establish the CP1b and CP2b benchmark datasets that could be useful for testing quantum chemistry models in challenging real-world systems with complex interplay between intra- and intermolecular interactions, a number of which are significantly impacted by delocalization error.
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Affiliation(s)
- Gregory J. O. Beran
- Department of Chemistry, University of California, Riverside, California 92521, USA
| | - Sarah E. Wright
- Department of Chemical Engineering and Analytical Science, University of Manchester, Manchester, United Kingdom
| | - Chandler Greenwell
- Department of Chemistry, University of California, Riverside, California 92521, USA
| | - Aurora J. Cruz-Cabeza
- Department of Chemical Engineering and Analytical Science, University of Manchester, Manchester, United Kingdom
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14
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Sugden IJ, Francia NF, Jensen T, Adjiman CS, Salvalaglio M. Rationalising the difference in crystallisability of two sulflowers using efficient in silico methods. CrystEngComm 2022. [DOI: 10.1039/d2ce00942k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The molecular structures of the first and second generation sulflowers, sulflower and persulfurated coronene (PSC), are remarkably similar: carbon ring structures decorated with sulfur atoms, without any additional moiety.
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Affiliation(s)
- Isaac J. Sugden
- Molecular Systems Engineering Group, Department of Chemical Engineering, Sargent Centre for Process Systems Engineering, Institute for Molecular Science and Engineering, Imperial College London, London SW7 2AZ, UK
| | - Nicholas F. Francia
- Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, UK
| | - Torsten Jensen
- School of Chemistry, University of Bristol, Cantock's Close, Bristol, BS8 1TS, UK
| | - Claire S. Adjiman
- Molecular Systems Engineering Group, Department of Chemical Engineering, Sargent Centre for Process Systems Engineering, Institute for Molecular Science and Engineering, Imperial College London, London SW7 2AZ, UK
| | - Matteo Salvalaglio
- Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, UK
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15
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Price SL. Progress in understanding crystallisation: a personal perspective. Faraday Discuss 2022; 235:569-581. [DOI: 10.1039/d2fd00077f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
After this discussion meeting, most participants felt that we do not understand crystallisation. However, in the 1980s I believe that most scientists would have considered that crystallisation was adequately understood....
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16
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Belenguer AM, Lampronti GI, Michalchuk AAL, Emmerling F, Sanders JKM. Quantitative reversible one pot interconversion of three crystalline polymorphs by ball mill grinding. CrystEngComm 2022. [DOI: 10.1039/d2ce00393g] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
We demonstrate here using a disulfide system the first example of reversible, selective, and quantitative transformation between three crystalline polymorphs by ball mill grinding.
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Affiliation(s)
- Ana M. Belenguer
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
| | - Giulio I. Lampronti
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
- Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge, CB2 3EQ, UK
| | - Adam A. L. Michalchuk
- BAM Federal Institute for Materials Research and Testing, Richard-Willstätter-Str. 11, D-12489 Berlin, Germany
| | - Franziska Emmerling
- BAM Federal Institute for Materials Research and Testing, Richard-Willstätter-Str. 11, D-12489 Berlin, Germany
| | - Jeremy K. M. Sanders
- Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK
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17
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Dudek MK, Druzbicki K. Along the road to Crystal Structure Prediction (CSP) of pharmaceutical-like molecules. CrystEngComm 2022. [DOI: 10.1039/d1ce01564h] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Computational methods used for predicting crystal structures of organic compounds are mature enough to be routinely used with many rigid and semi-rigid organic molecules. The usefulness of Crystal Structure Prediction...
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18
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Braun DE, Hald P, Kahlenberg V, Griesser UJ. Expanding the Solid Form Landscape of Bipyridines. CRYSTAL GROWTH & DESIGN 2021; 21:7201-7217. [PMID: 34867088 PMCID: PMC8640990 DOI: 10.1021/acs.cgd.1c01045] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 10/19/2021] [Indexed: 06/13/2023]
Abstract
Two bipyridine isomers (2,2'- and 4,4'-), used as coformers and ligands in coordination chemistry, were subjected to solid form screening and crystal structure prediction. One anhydrate and a formic acid disolvate were crystallized for 2,2'-bipyridine, whereas multiple solid-state forms, anhydrate, dihydrate, and eight solvates with carboxylic acids, including a polymorphic acetic acid disolvate, were found for the 4,4'-isomer. Seven of the solvates are reported for the first time, and structural information is provided for six of the new solvates. All twelve solid-state forms were investigated comprehensively using experimental [thermal analysis, isothermal calorimetry, X-ray diffraction, gravimetric moisture (de)sorption, and IR spectroscopy] and computational approaches. Lattice and interaction energy calculations confirmed the thermodynamic driving force for disolvate formation, mediated by the absence of H-bond donor groups of the host molecules. The exposed location of the N atoms in 4,4'-bipyridine facilitates the accommodation of bigger carboxylic acids and leads to higher conformational flexibility compared to 2,2'-bipyridine. For the 4,4'-bipyridine anhydrate ↔ hydrate interconversion hardly any hysteresis and a fast transformation kinetics are observed, with the critical relative humidity being at 35% at room temperature. The computed anhydrate crystal energy landscapes have the 2,2'-bipyridine as the lowest energy structure and the 4,4'-bipyridine among the low-energy structures and suggest a different crystallization behavior of the two compounds.
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Affiliation(s)
- Doris E. Braun
- Institute
of Pharmacy, University of Innsbruck, Innrain 52c, 6020 Innsbruck, Austria
| | - Patricia Hald
- Institute
of Pharmacy, University of Innsbruck, Innrain 52c, 6020 Innsbruck, Austria
| | - Volker Kahlenberg
- Institute
of Mineralogy and Petrography, University
of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
| | - Ulrich J. Griesser
- Institute
of Pharmacy, University of Innsbruck, Innrain 52c, 6020 Innsbruck, Austria
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19
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Fowles DJ, Palmer DS, Guo R, Price SL, Mitchell JBO. Toward Physics-Based Solubility Computation for Pharmaceuticals to Rival Informatics. J Chem Theory Comput 2021; 17:3700-3709. [PMID: 33988381 PMCID: PMC8190954 DOI: 10.1021/acs.jctc.1c00130] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
![]()
We demonstrate that
physics-based calculations of intrinsic aqueous
solubility can rival cheminformatics-based machine learning predictions.
A proof-of-concept was developed for a physics-based approach via
a sublimation thermodynamic cycle, building upon previous work that
relied upon several thermodynamic approximations, notably the 2RT approximation, and limited conformational sampling. Here,
we apply improvements to our sublimation free-energy model with the
use of crystal phonon mode calculations to capture the contributions
of the vibrational modes of the crystal. Including these improvements
with lattice energies computed using the model-potential-based Ψmol method leads to accurate estimates of sublimation free
energy. Combining these with hydration free energies obtained from
either molecular dynamics free-energy perturbation simulations or
density functional theory calculations, solubilities comparable to
both experiment and informatics predictions are obtained. The application
to coronene, succinic acid, and the pharmaceutical desloratadine shows
how the methods must be adapted for the adoption of different conformations
in different phases. The approach has the flexibility to extend to
applications that cannot be covered by informatics methods.
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Affiliation(s)
- Daniel J Fowles
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, U.K
| | - David S Palmer
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, 295 Cathedral Street, Glasgow, Scotland G1 1XL, U.K
| | - Rui Guo
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
| | - Sarah L Price
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
| | - John B O Mitchell
- EaStCHEM School of Chemistry and Biomedical Sciences Research Complex, University of St Andrews, St Andrews, Scotland KY16 9ST, U.K
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20
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Cook C, McKinley JL, Beran GJO. Modeling the α- and β-resorcinol phase boundary via combination of density functional theory and density functional tight-binding. J Chem Phys 2021; 154:134109. [PMID: 33832233 PMCID: PMC8019358 DOI: 10.1063/5.0044385] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/10/2021] [Indexed: 02/06/2023] Open
Abstract
The ability to predict not only what organic crystal structures might occur but also the thermodynamic conditions under which they are the most stable would be extremely useful for discovering and designing new organic materials. The present study takes a step in that direction by predicting the temperature- and pressure-dependent phase boundary between the α and β polymorphs of resorcinol using density functional theory (DFT) and the quasi-harmonic approximation. To circumvent the major computational bottleneck associated with computing a well-converged phonon density of states via the supercell approach, a recently developed approximation is employed, which combines a supercell phonon density of states from dispersion-corrected third-order density functional tight binding [DFTB3-D3(BJ)] with frequency corrections derived from a smaller B86bPBE-XDM functional DFT phonon calculation on the crystallographic unit cell. This mixed DFT/DFTB quasi-harmonic approach predicts the lattice constants and unit cell volumes to within 1%-2% at lower pressures. It predicts the thermodynamic phase boundary in almost perfect agreement with the experiment, although this excellent agreement does reflect fortuitous cancellation of errors between the enthalpy and entropy of transition.
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Affiliation(s)
- Cameron Cook
- Department of Chemistry, University of California, Riverside, California 92521, USA
| | - Jessica L. McKinley
- Department of Chemistry, University of California, Riverside, California 92521, USA
| | - Gregory J. O. Beran
- Department of Chemistry, University of California, Riverside, California 92521, USA
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21
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Bowskill DH, Sugden IJ, Konstantinopoulos S, Adjiman CS, Pantelides CC. Crystal Structure Prediction Methods for Organic Molecules: State of the Art. Annu Rev Chem Biomol Eng 2021; 12:593-623. [PMID: 33770462 DOI: 10.1146/annurev-chembioeng-060718-030256] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- David H Bowskill
- Molecular Systems Engineering Group, Centre for Process Systems Engineering, Department of Chemical Engineering, and Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom;
| | - Isaac J Sugden
- Molecular Systems Engineering Group, Centre for Process Systems Engineering, Department of Chemical Engineering, and Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom;
| | - Stefanos Konstantinopoulos
- Molecular Systems Engineering Group, Centre for Process Systems Engineering, Department of Chemical Engineering, and Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom;
| | - Claire S Adjiman
- Molecular Systems Engineering Group, Centre for Process Systems Engineering, Department of Chemical Engineering, and Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom;
| | - Constantinos C Pantelides
- Molecular Systems Engineering Group, Centre for Process Systems Engineering, Department of Chemical Engineering, and Institute for Molecular Science and Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom;
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22
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Aina AA, Misquitta AJ, Price SL. A non-empirical intermolecular force-field for trinitrobenzene and its application in crystal structure prediction. J Chem Phys 2021; 154:094123. [PMID: 33685142 DOI: 10.1063/5.0043746] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
An anisotropic atom-atom distributed intermolecular force-field (DIFF) for rigid trinitrobenzene (TNB) is developed using distributed multipole moments, dipolar polarizabilities, and dispersion coefficients derived from the charge density of the isolated molecule. The short-range parameters of the force-field are fitted to first- and second-order symmetry-adapted perturbation theory dimer interaction energy calculations using the distributed density-overlap model to guide the parameterization of the short-range anisotropy. The second-order calculations are used for fitting the damping coefficients of the long-range dispersion and polarization and also for relaxing the isotropic short-range coefficients in the final model, DIFF-srL2(rel). We assess the accuracy of the unrelaxed model, DIFF-srL2(norel), and its equivalent without short-range anisotropy, DIFF-srL0(norel), as these models are easier to derive. The model potentials are contrasted with empirical models for the repulsion-dispersion fitted to organic crystal structures with multipoles of iterated stockholder atoms (ISAs), FIT(ISA,L4), and with Gaussian Distributed Analysis (GDMA) multipoles, FIT(GDMA,L4), commonly used in modeling organic crystals. The potentials are tested for their ability to model the solid state of TNB. The non-empirical models provide more reasonable relative lattice energies of the three polymorphs of TNB and propose more sensible hypothetical structures than the empirical force-field (FIT). The DIFF-srL2(rel) model successfully has the most stable structure as one of the many structures that match the coordination sphere of form III. The neglect of the conformational flexibility of the nitro-groups is a significant approximation. This methodology provides a step toward force-fields capable of representing all phases of a molecule in molecular dynamics simulations.
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Affiliation(s)
- Alex A Aina
- Department of Chemistry, University College London, 20 Gordon St., London WC1H 0AJ, United Kingdom
| | - Alston J Misquitta
- School of Physics and Astronomy and The Thomas Young Centre for Theory and Simulation of Materials at Queen Mary, University of London, London E1 4NS, United Kingdom
| | - Sarah L Price
- Department of Chemistry, University College London, 20 Gordon St., London WC1H 0AJ, United Kingdom
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23
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Hong RS, Mattei A, Sheikh AY, Bhardwaj RM, Bellucci MA, McDaniel KF, Pierce MO, Sun G, Li S, Wang L, Mondal S, Ji J, Borchardt TB. Novel Physics-Based Ensemble Modeling Approach That Utilizes 3D Molecular Conformation and Packing to Access Aqueous Thermodynamic Solubility: A Case Study of Orally Available Bromodomain and Extraterminal Domain Inhibitor Lead Optimization Series. J Chem Inf Model 2021; 61:1412-1426. [PMID: 33661005 DOI: 10.1021/acs.jcim.0c01410] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Drug design with patient centricity for ease of administration and pill burden requires robust understanding of the impact of chemical modifications on relevant physicochemical properties early in lead optimization. To this end, we have developed a physics-based ensemble approach to predict aqueous thermodynamic crystalline solubility, with a 2D chemical structure as the input. Predictions for the bromodomain and extraterminal domain (BET) inhibitor series show very close match (0.5 log unit) with measured thermodynamic solubility for cases with low crystal anisotropy and good match (1 log unit) for high anisotropy structures. The importance of thermodynamic solubility is clearly demonstrated by up to a 4 log unit drop in solubility compared to kinetic (amorphous) solubility in some cases and implications thereof, for instance on human dose. We have also demonstrated that incorporating predicted crystal structures in thermodynamic solubility prediction is necessary to differentiate (up to 4 log unit) between solubility of molecules within the series. Finally, our physics-based ensemble approach provides valuable structural insights into the origins of 3-D conformational landscapes, crystal polymorphism, and anisotropy that can be leveraged for both drug design and development.
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Affiliation(s)
- Richard S Hong
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - Alessandra Mattei
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - Ahmad Y Sheikh
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - Rajni Miglani Bhardwaj
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - Michael A Bellucci
- XtalPi, Inc., 245 Main Street, Cambridge, Massachusetts 02142, United States
| | - Keith F McDaniel
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - M Olivia Pierce
- Schrödinger Inc., 120 W 45th Street, New York, New York 10036, United States
| | - Guangxu Sun
- XtalPi, Inc., 245 Main Street, Cambridge, Massachusetts 02142, United States
| | - Sizhu Li
- XtalPi, Inc., 245 Main Street, Cambridge, Massachusetts 02142, United States
| | - Lingle Wang
- Schrödinger Inc., 120 W 45th Street, New York, New York 10036, United States
| | - Sayan Mondal
- Schrödinger Inc., 120 W 45th Street, New York, New York 10036, United States
| | - Jianguo Ji
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
| | - Thomas B Borchardt
- Research & Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, Illinois 60064, United States
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24
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Francia NF, Price LS, Salvalaglio M. Reducing crystal structure overprediction of ibuprofen with large scale molecular dynamics simulations. CrystEngComm 2021. [DOI: 10.1039/d1ce00616a] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Reduction of a large dataset of computationally predicted structures of ibuprofen by employing molecular dynamics and biased simulations at finite temperature and pressure.
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Affiliation(s)
- Nicholas F. Francia
- Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, UK
| | - Louise S. Price
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
| | - Matteo Salvalaglio
- Thomas Young Centre and Department of Chemical Engineering, University College London, London WC1E 7JE, UK
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25
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Mayo RA, Johnson ER. Improved quantitative crystal-structure comparison using powder diffractograms via anisotropic volume correction. CrystEngComm 2021. [DOI: 10.1039/d1ce01058a] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
A new anisotropic volume correction improves quantitative crystal structure comparison. Benchmarking against the 6th crystal structure prediction blind test data results in identification of two previously uncredited matching structures.
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Affiliation(s)
- R. Alex Mayo
- Department of Chemistry, Dalhousie University, 6274 Coburg Road, PO Box 15000, Halifax, Nova Scotia, B3H 4R2, Canada
| | - Erin R. Johnson
- Department of Chemistry, Dalhousie University, 6274 Coburg Road, PO Box 15000, Halifax, Nova Scotia, B3H 4R2, Canada
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26
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Rekis T, Schaller AM, Kotla SR, Schönleber A, Noohinejad L, Tolkiehn M, Paulmann C, van Smaalen S. Single-crystal-to-single-crystal phase transitions of commensurately modulated sodium saccharinate 1.875-hydrate. IUCRJ 2021; 8:139-147. [PMID: 33520250 PMCID: PMC7792995 DOI: 10.1107/s2052252520015912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/04/2020] [Indexed: 06/12/2023]
Abstract
This work reports reversible, single-crystal-to-single-crystal phase transitions of commensurately modulated sodium saccharinate 1.875-hydrate [Na(sac)(15/8)H2O]. The phases were studied in the temperature range 298 to 20 K. They exhibit complex disordered states. An unusual reentrant disorder has been discovered upon cooling through a phase transition at 120 K. The disordered region involves three sodium cations, four water molecules and one saccharinate anion. At room temperature, the structure is an eightfold superstructure that can be described by the superspace group C2/c(0σ20)s0 with q = (0, 3/4, 0). It demonstrates maximum disorder with the disordered chemical entities having slightly different but close to 0.50:0.50 disorder component ratios. Upon cooling, the crystal tends to an ordered state, smoothly reaching a unified disorder component ratio of around 0.90:0.10 for each of the entities. Between 130 and 120 K a phase transition occurs involving a sudden increase of the disorder towards the disorder component ratio 0.65:0.35. Meanwhile, the space group and general organization of the structure are retained. Between 60 and 40 K there is another phase transition leading to a twinned triclinic phase. After heating the crystal back to room temperature its structure is the same as before cooling, indicating a complete reversibility of the phase transitions.
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Affiliation(s)
- Toms Rekis
- Laboratory of Crystallography, University of Bayreuth, 95447 Bayreuth, Germany
| | - Achim M. Schaller
- Laboratory of Crystallography, University of Bayreuth, 95447 Bayreuth, Germany
| | - Surya Rohith Kotla
- Laboratory of Crystallography, University of Bayreuth, 95447 Bayreuth, Germany
| | - Andreas Schönleber
- Laboratory of Crystallography, University of Bayreuth, 95447 Bayreuth, Germany
| | - Leila Noohinejad
- P24, PETRA III, Deutsches Elektronen-Synchrotron, 22607 Hamburg, Germany
| | - Martin Tolkiehn
- P24, PETRA III, Deutsches Elektronen-Synchrotron, 22607 Hamburg, Germany
| | - Carsten Paulmann
- P24, PETRA III, Deutsches Elektronen-Synchrotron, 22607 Hamburg, Germany
- Mineralogisch-Petrographisches Institut, Universität Hamburg, 20146 Hamburg, Germany
| | - Sander van Smaalen
- Laboratory of Crystallography, University of Bayreuth, 95447 Bayreuth, Germany
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27
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Kamat K, Guo R, Reutzel-Edens SM, Price SL, Peters B. Diabat method for polymorph free energies: Extension to molecular crystals. J Chem Phys 2020; 153:244105. [PMID: 33380078 DOI: 10.1063/5.0024727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Lattice-switch Monte Carlo and the related diabat methods have emerged as efficient and accurate ways to compute free energy differences between polymorphs. In this work, we introduce a one-to-one mapping from the reference positions and displacements in one molecular crystal to the positions and displacements in another. Two features of the mapping facilitate lattice-switch Monte Carlo and related diabat methods for computing polymorph free energy differences. First, the mapping is unitary so that its Jacobian does not complicate the free energy calculations. Second, the mapping is easily implemented for molecular crystals of arbitrary complexity. We demonstrate the mapping by computing free energy differences between polymorphs of benzene and carbamazepine. Free energy calculations for thermodynamic cycles, each involving three independently computed polymorph free energy differences, all return to the starting free energy with a high degree of precision. The calculations thus provide a force field independent validation of the method and allow us to estimate the precision of the individual free energy differences.
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Affiliation(s)
- Kartik Kamat
- Department of Chemical Engineering, University of California-Santa Barbara, Santa Barbara, California 93106, USA
| | - Rui Guo
- Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
| | - Susan M Reutzel-Edens
- Small Molecule Design and Development, Eli Lilly and Company, Indianapolis, Indiana 46285, USA
| | - Sarah L Price
- Department of Chemistry, University College London, London WC1H 0AJ, United Kingdom
| | - Baron Peters
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
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28
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Woodley SM, Day GM, Catlow R. Structure prediction of crystals, surfaces and nanoparticles. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2020; 378:20190600. [PMID: 33100162 DOI: 10.1098/rsta.2019.0600] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
We review the current techniques used in the prediction of crystal structures and their surfaces and of the structures of nanoparticles. The main classes of search algorithm and energy function are summarized, and we discuss the growing role of methods based on machine learning. We illustrate the current status of the field with examples taken from metallic, inorganic and organic systems. This article is part of a discussion meeting issue 'Dynamic in situ microscopy relating structure and function'.
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Affiliation(s)
- Scott M Woodley
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
| | - Graeme M Day
- Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton SO17 1BJ, UK
| | - R Catlow
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, UK
- School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, UK
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29
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Bier I, Marom N. Machine Learned Model for Solid Form Volume Estimation Based on Packing-Accessible Surface and Molecular Topological Fragments. J Phys Chem A 2020; 124:10330-10345. [DOI: 10.1021/acs.jpca.0c06791] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Imanuel Bier
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
| | - Noa Marom
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
- Department of Chemistry, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
- Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, United States
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30
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Mathew R, Uchman KA, Gkoura L, Pickard CJ, Baias M. Identifying aspirin polymorphs from combined DFT-based crystal structure prediction and solid-state NMR. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2020; 58:1018-1025. [PMID: 31900955 DOI: 10.1002/mrc.4987] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 12/17/2019] [Accepted: 01/02/2020] [Indexed: 06/10/2023]
Abstract
A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)-based crystal structure prediction method for the high-accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid-state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form-I and form-II of aspirin. The root-mean-square deviation between experimental and calculated 1 H chemical shifts was used to identify form-I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs.
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Affiliation(s)
- Renny Mathew
- Division of Science, New York University Abu Dhabi, Abu Dhabi, UAE
| | | | - Lydia Gkoura
- Division of Science, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Chris J Pickard
- Department of Materials Science and Metallurgy, University of Cambridge, Cambridge, UK
- Advanced Institute for Materials Research, Tohoku University, Sendai, Japan
| | - Maria Baias
- Division of Science, New York University Abu Dhabi, Abu Dhabi, UAE
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31
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Sayer T, Cox SJ. Macroscopic surface charges from microscopic simulations. J Chem Phys 2020; 153:164709. [PMID: 33138409 DOI: 10.1063/5.0022596] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Attaining accurate average structural properties in a molecular simulation should be considered a prerequisite if one aims to elicit meaningful insights into a system's behavior. For charged surfaces in contact with an electrolyte solution, an obvious example is the density profile of ions along the direction normal to the surface. Here, we demonstrate that, in the slab geometry typically used in simulations, imposing an electric displacement field D determines the integrated surface charge density of adsorbed ions at charged interfaces. This allows us to obtain macroscopic surface charge densities irrespective of the slab thickness used in our simulations. We also show that the commonly used Yeh-Berkowitz method and the "mirrored slab" geometry both impose vanishing integrated surface charge densities. We present results both for relatively simple rocksalt (1 1 1) interfaces and the more complex case of kaolinite's basal faces in contact with an aqueous electrolyte solution.
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Affiliation(s)
- Thomas Sayer
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - Stephen J Cox
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom
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32
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Taylor CR, Mulvee MT, Perenyi DS, Probert MR, Day GM, Steed JW. Minimizing Polymorphic Risk through Cooperative Computational and Experimental Exploration. J Am Chem Soc 2020; 142:16668-16680. [PMID: 32897065 PMCID: PMC7586337 DOI: 10.1021/jacs.0c06749] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
![]()
We
combine state-of-the-art computational crystal structure prediction
(CSP) techniques with a wide range of experimental crystallization
methods to understand and explore crystal structure in pharmaceuticals
and minimize the risk of unanticipated late-appearing polymorphs.
Initially, we demonstrate the power of CSP to rationalize the difficulty
in obtaining polymorphs of the well-known pharmaceutical isoniazid
and show that CSP provides the structure of the recently obtained,
but unsolved, Form III of this drug despite there being only a single
resolved form for almost 70 years. More dramatically, our blind CSP
study predicts a significant risk of polymorphism for the related
iproniazid. Employing a wide variety of experimental techniques, including
high-pressure experiments, we experimentally obtained the first three
known nonsolvated crystal forms of iproniazid, all of which were successfully
predicted in the CSP procedure. We demonstrate the power of CSP methods
and free energy calculations to rationalize the observed elusiveness
of the third form of iproniazid, the success of high-pressure experiments
in obtaining it, and the ability of our synergistic computational-experimental
approach to “de-risk” solid form landscapes.
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Affiliation(s)
- Christopher R Taylor
- Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton SO17 1NX, U.K
| | - Matthew T Mulvee
- Department of Chemistry, Durham University, South Road, Durham DH1 3LE, U.K
| | - Domonkos S Perenyi
- Department of Chemistry, Durham University, South Road, Durham DH1 3LE, U.K
| | - Michael R Probert
- Chemistry, School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne NE1 7RU, U.K
| | - Graeme M Day
- Computational Systems Chemistry, School of Chemistry, University of Southampton, Southampton SO17 1NX, U.K
| | - Jonathan W Steed
- Department of Chemistry, Durham University, South Road, Durham DH1 3LE, U.K
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33
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Catlow CRA. Computational modelling as a tool in structural science. IUCRJ 2020; 7:778-779. [PMID: 32939267 PMCID: PMC7467169 DOI: 10.1107/s2052252520011793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
This editorial gives a brief discussion of the current status and role of computational modelling as a technique in structural science.
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Affiliation(s)
- C. Richard A. Catlow
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, United Kingdom
- School of Chemistry, Cardiff University, Park Place, Cardiff CF10 3AT, United Kingdom
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34
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Hodgkinson P. NMR crystallography of molecular organics. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2020; 118-119:10-53. [PMID: 32883448 DOI: 10.1016/j.pnmrs.2020.03.001] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 02/25/2020] [Accepted: 03/13/2020] [Indexed: 06/11/2023]
Abstract
Developments of NMR methodology to characterise the structures of molecular organic structures are reviewed, concentrating on the previous decade of research in which density functional theory-based calculations of NMR parameters in periodic solids have become widespread. With a focus on demonstrating the new structural insights provided, it is shown how "NMR crystallography" has been used in a spectrum of applications from resolving ambiguities in diffraction-derived structures (such as hydrogen atom positioning) to deriving complete structures in the absence of diffraction data. As well as comprehensively reviewing applications, the different aspects of the experimental and computational techniques used in NMR crystallography are surveyed. NMR crystallography is seen to be a rapidly maturing subject area that is increasingly appreciated by the wider crystallographic community.
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Affiliation(s)
- Paul Hodgkinson
- Department of Chemistry, Durham University, Stockton Road, Durham DH1 3LE, UK.
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35
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Dudek MK, Paluch P, Pindelska E. Crystal structures of two furazidin polymorphs revealed by a joint effort of crystal structure prediction and NMR crystallography. ACTA CRYSTALLOGRAPHICA SECTION B, STRUCTURAL SCIENCE, CRYSTAL ENGINEERING AND MATERIALS 2020; 76:322-335. [PMID: 32831253 DOI: 10.1107/s205252062000373x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Accepted: 03/12/2020] [Indexed: 06/11/2023]
Abstract
This work presents the crystal structure determination of two elusive polymorphs of furazidin, an antibacterial agent, employing a combination of crystal structure prediction (CSP) calculations and an NMR crystallography approach. Two previously uncharacterized neat crystal forms, one of which has two symmetry-independent molecules (form I), whereas the other one is a Z' = 1 polymorph (form II), crystallize in P21/c and P1 space groups, respectively, and both are built by different conformers, displaying different intermolecular interactions. It is demonstrated that the usage of either CSP or NMR crystallography alone is insufficient to successfully elucidate the above-mentioned crystal structures, especially in the case of the Z' = 2 polymorph. In addition, cases of serendipitous agreement in terms of 1H or 13C NMR data obtained for the CSP-generated crystal structures different from the ones observed in the laboratory (false-positive matches) are analyzed and described. While for the majority of analyzed crystal structures the obtained agreement with the NMR experiment is indicative of some structural features in common with the experimental structure, the mentioned serendipity observed in exceptional cases points to the necessity of caution when using an NMR crystallography approach in crystal structure determination.
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Affiliation(s)
- Marta K Dudek
- Center of Molecular and Macromolecular Studies, Polish Academy of Sciences, Sienkiewicza 112, Lodz, 90-363, Poland
| | - Piotr Paluch
- Center of Molecular and Macromolecular Studies, Polish Academy of Sciences, Sienkiewicza 112, Lodz, 90-363, Poland
| | - Edyta Pindelska
- Faculty of Pharmacy, Medical University of Warsaw, Banacha 1, Warsaw, 02097, Poland
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36
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Mosca MM, Kurlin V. Voronoi-Based Similarity Distances between Arbitrary Crystal Lattices. CRYSTAL RESEARCH AND TECHNOLOGY 2020. [DOI: 10.1002/crat.201900197] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Marco M. Mosca
- Materials Innovation Factory and Computer Science department; University of Liverpool; Liverpool L69 3BX UK
| | - Vitaliy Kurlin
- Materials Innovation Factory and Computer Science department; University of Liverpool; Liverpool L69 3BX UK
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37
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Guo R, Uddin MN, Price LS, Price SL. Calculation of Diamagnetic Susceptibility Tensors of Organic Crystals: From Coronene to Pharmaceutical Polymorphs. J Phys Chem A 2020; 124:1409-1420. [PMID: 31951408 PMCID: PMC7145345 DOI: 10.1021/acs.jpca.9b07104] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
![]()
Understanding
why crystallization in strong magnetic fields can
lead to new polymorphs requires methods to calculate the diamagnetic
response of organic molecular crystals. We develop the calculation
of the macroscopic diamagnetic susceptibility tensor, χcryst, for organic molecular crystals using periodic density
functional methods. The crystal magnetic susceptibility tensor, χcryst, for all experimentally known polymorphs,
and its molecular counterpart, χmol,
are calculated for flexible pharmaceuticals such as carbamazepine,
flufenamic acid, and chalcones, and rigid molecules, such as benzene,
pyridine, acridine, anthracene, and coronene, whose molecular magnetic
properties have been traditionally studied. A tensor addition method
is developed to approximate the crystal diamagnetic susceptibility
tensor, χcryst, from the molecular one, χmol, giving good agreement with those calculated
directly using the more costly periodic density functional method
for χcryst. The response of pharmaceutical
molecules and crystals to magnetic fields, as embodied by χcryst, is largely determined by the packing in the crystal,
as well as the molecular conformation. The anisotropy of χcryst can vary considerably between polymorphs though
the isotropic terms are fairly constant. The implications for developing
a computational method for predicting whether crystallization in a
magnetic field could produce a novel or different polymorph are discussed.
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Affiliation(s)
- Rui Guo
- Department of Chemistry , University College London , 20 Gordon Street , London WC1H 0AJ , U.K
| | - M Nadia Uddin
- Department of Chemistry , University College London , 20 Gordon Street , London WC1H 0AJ , U.K
| | - Louise S Price
- Department of Chemistry , University College London , 20 Gordon Street , London WC1H 0AJ , U.K
| | - Sarah L Price
- Department of Chemistry , University College London , 20 Gordon Street , London WC1H 0AJ , U.K
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38
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Taylor R. Identifying intermolecular atom⋯atom interactions that are not just bonding but also competitive. CrystEngComm 2020. [DOI: 10.1039/d0ce00270d] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
This highlight criticises the QTAIM method and discusses algorithms for identifying intermolecular interactions that are both bonding and competitive.
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Affiliation(s)
- Robin Taylor
- Cambridge Crystallographic Data Centre
- Cambridge CB2 1EZ
- UK
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39
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Intermolecular Interactions in Molecular Organic Crystals upon Relaxation of Lattice Parameters. CRYSTALS 2019. [DOI: 10.3390/cryst9120665] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Crystal structure prediction is based on the assumption that the most thermodynamically stable structure will crystallize first. The existence of other structures such as polymorphs or from counterenantiomers requires an accurate calculation of the electronic energy. Using atom-centered Gaussian basis functions in periodic Density Functional Theory (DFT) calculations in Turbomole, the performance of two dispersion-corrected functionals, PBE-D3 and B97-D, is assessed for molecular organic crystals of the X23 benchmark set. B97-D shows a MAE (mean absolute error) of 4 kJ/mol, compared to 9 kJ/mol for PBE-D3. A strategy for the convergence of lattice energies towards the basis set limit is outlined. A simultaneous minimization of molecular structures and lattice parameters shows that both methods are able to reproduce experimental unit cell parameters to within 4–5%. Calculated lattice energies, however, deviate slightly more from the experiment, i.e., by 0.4 kJ/mol after unit cell optimization for PBE-D3 and 0.5 kJ/mol for B97-D. The accuracy of the calculated lattice energies compared to the experimental values demonstrates the ability of current DFT methods to assist in the quest for possible polymorphs and enantioselective crystallization processes.
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40
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Marchese Robinson RL, Geatches D, Morris C, Mackenzie R, Maloney AGP, Roberts KJ, Moldovan A, Chow E, Pencheva K, Vatvani DRM. Evaluation of Force-Field Calculations of Lattice Energies on a Large Public Dataset, Assessment of Pharmaceutical Relevance, and Comparison to Density Functional Theory. J Chem Inf Model 2019; 59:4778-4792. [DOI: 10.1021/acs.jcim.9b00601] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Richard L. Marchese Robinson
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Dawn Geatches
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Chris Morris
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Rebecca Mackenzie
- Science and Technology Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Andrew G. P. Maloney
- Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, United Kingdom
| | - Kevin J. Roberts
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Alexandru Moldovan
- Centre for Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Ernest Chow
- Pfizer Worldwide R&D, Ramsgate Road, Sandwich CT13 9NJ, United Kingdom
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41
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Cui P, McMahon DP, Spackman PR, Alston BM, Little MA, Day GM, Cooper AI. Mining predicted crystal structure landscapes with high throughput crystallisation: old molecules, new insights. Chem Sci 2019; 10:9988-9997. [PMID: 32055355 PMCID: PMC6991173 DOI: 10.1039/c9sc02832c] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 08/19/2019] [Indexed: 11/21/2022] Open
Abstract
New crystal forms of two well-studied organic molecules are identified in a computationally targeted way, by combining structure prediction with a robotic crystallisation screen, including a ‘hidden’ porous polymorph of trimesic acid.
Organic molecules tend to close pack to form dense structures when they are crystallised from organic solvents. Porous molecular crystals defy this rule: they contain open space, which is typically stabilised by inclusion of solvent in the interconnected pores during crystallisation. The design and discovery of such structures is often challenging and time consuming, in part because it is difficult to predict solvent effects on crystal form stability. Here, we combine crystal structure prediction (CSP) with a robotic crystallisation screen to accelerate the discovery of stable hydrogen-bonded frameworks. We exemplify this strategy by finding new phases of two well-studied molecules in a computationally targeted way. Specifically, we find a new ‘hidden’ porous polymorph of trimesic acid, δ-TMA, that has a guest-free hexagonal pore structure, as well as three new solvent-stabilized diamondoid frameworks of adamantane-1,3,5,7-tetracarboxylic acid (ADTA). Beyond porous solids, this hybrid computational–experimental approach could be applied to a wide range of materials problems, such as organic electronics and drug formulation.
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Affiliation(s)
- Peng Cui
- Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK .
| | - David P McMahon
- Computational Systems Chemistry , School of Chemistry , University of Southampton , SO17 1BJ , UK .
| | - Peter R Spackman
- Computational Systems Chemistry , School of Chemistry , University of Southampton , SO17 1BJ , UK . .,Leverhulme Research Centre for Functional Materials Design , Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK
| | - Ben M Alston
- Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK . .,Leverhulme Research Centre for Functional Materials Design , Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK
| | - Marc A Little
- Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK .
| | - Graeme M Day
- Computational Systems Chemistry , School of Chemistry , University of Southampton , SO17 1BJ , UK .
| | - Andrew I Cooper
- Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK . .,Leverhulme Research Centre for Functional Materials Design , Department of Chemistry and Materials Innovation Factory , University of Liverpool , Liverpool , L7 3NY , UK
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42
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Braun DE. Experimental and computational approaches to rationalise multicomponent supramolecular assemblies: dapsone monosolvates. Phys Chem Chem Phys 2019; 21:17288-17305. [PMID: 31348477 DOI: 10.1039/c9cp02572c] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The monosolvate crystal energy landscapes of dapsone (DDS) including the solvents carbon tetrachloride, acetone, cyclohexanone, dimethyl formamide, tetrahydrofuran, methyl ethyl ketone, 1,2-dichloroethane, 1,4-dioxane, dichloromethane and chloroform were established using experimental and computational approaches. To rationalise and understand solvate formation, solvate stability and desolvation reactions a careful control of the experimental crystallisation and storage conditions, a range of thermoanalytical methods and crystal structure prediction were required. Six of the eight DDS monosolvates are reported and characterised for the first time. Structural similarity and diversity of the at ambient conditions unstable monosolvates were apparent from the computed crystal energy landscapes, which had the experimental packings as lowest energy structures. The computed structures were used as input for Rietveld refinements and isostructurality of four of the monosolvates was confirmed. Packing comparisons of the solvate structures and molecular properties of the solvent molecules indicated that both size/shape of the solvent molecule and the possible DDSsolvent interactions are the important factors for DDS solvate formation. Through the combination of experiment and theory solvate stability and structural features have been rationalised.
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Affiliation(s)
- Doris E Braun
- Institute of Pharmacy, University of Innsbruck, Innrain 52c, 6020 Innsbruck, Austria.
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43
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Bhardwaj RM, McMahon JA, Nyman J, Price LS, Konar S, Oswald IDH, Pulham CR, Price SL, Reutzel-Edens SM. A Prolific Solvate Former, Galunisertib, under the Pressure of Crystal Structure Prediction, Produces Ten Diverse Polymorphs. J Am Chem Soc 2019; 141:13887-13897. [DOI: 10.1021/jacs.9b06634] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Rajni M. Bhardwaj
- Small Molecule Design & Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | - Jennifer A. McMahon
- Small Molecule Design & Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
| | - Jonas Nyman
- Small Molecule Design & Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
- School of Pharmacy, University of Wisconsin—Madison, 777 Highland Avenue, Madison, Wisconsin 53705, United States
| | - Louise S. Price
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
| | - Sumit Konar
- School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K
| | - Iain D. H. Oswald
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, 161 Cathedral St, Glasgow G4 0RE, U.K
| | - Colin R. Pulham
- School of Chemistry, University of Edinburgh, David Brewster Road, Edinburgh EH9 3FJ, U.K
| | - Sarah L. Price
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
| | - Susan M. Reutzel-Edens
- Small Molecule Design & Development, Eli Lilly and Company, Indianapolis, Indiana 46285, United States
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44
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Geatches D, Rosbottom I, Marchese Robinson RL, Byrne P, Hasnip P, Probert MIJ, Jochym D, Maloney A, Roberts KJ. Off-the-shelf DFT-DISPersion methods: Are they now “on-trend” for organic molecular crystals? J Chem Phys 2019; 151:044106. [PMID: 31370509 DOI: 10.1063/1.5108829] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Affiliation(s)
- Dawn Geatches
- Science and Technologies Facilities Council, Daresbury Laboratory, Sci-Tech Daresbury, Warrington WA4 4AD, United Kingdom
| | - Ian Rosbottom
- Centre for the Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Richard L. Marchese Robinson
- Centre for the Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Peter Byrne
- Department of Physics, University of York, Heslington YO10 5DD, United Kingdom
| | - Phil Hasnip
- Department of Physics, University of York, Heslington YO10 5DD, United Kingdom
| | - Matt I. J. Probert
- Department of Physics, University of York, Heslington YO10 5DD, United Kingdom
| | - Dominik Jochym
- Science and Technology Facilities Council, Rutherford Appleton Laboratory, Harwell Campus, Didcot OX11 OQX, United Kingdom
| | - Andrew Maloney
- The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, United Kingdom
| | - Kevin J. Roberts
- Centre for the Digital Design of Drug Products, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, United Kingdom
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45
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Aina AA, Misquitta AJ, Phipps MJS, Price SL. Charge Distributions of Nitro Groups Within Organic Explosive Crystals: Effects on Sensitivity and Modeling. ACS OMEGA 2019; 4:8614-8625. [PMID: 31459950 PMCID: PMC6648017 DOI: 10.1021/acsomega.9b00648] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 05/03/2019] [Indexed: 06/10/2023]
Abstract
The charge distribution of NO2 groups within the crystalline polymorphs of energetic materials strongly affects their explosive properties. We use the recently introduced basis-space iterated stockholder atom partitioning of high-quality charge distributions to examine the approximations that can be made in modeling polymorphs and their physical properties, using 1,3,5-trinitroperhydro-1,3,5-triazine, trinitrotoluene, 1-3-5-trinitrobenzene, and hexanitrobenzene as exemplars. The NO2 charge distribution is strongly affected by the neighboring atoms, the rest of the molecules, and also significantly by the NO2 torsion angle within the possible variations found in observed crystal structures. Thus, the proposed correlations between the molecular electrostatic properties, such as trigger-bond potential or maxima in the electrostatic potential, and impact sensitivity will be affected by the changes in conformation that occur on crystallization. We establish the relationship between the NO2 torsion angle and the likelihood of occurrence in observed crystal structures, the conformational energy, and the charge and dipole magnitude on each atom, and how this varies with the neighboring groups. We examine the effect of analytically rotating the atomic multipole moments to model changes in torsion angle and establish that this is a viable approach for crystal structures but is not accurate enough to model the relative lattice energies. This establishes the basis of transferability of the NO2 charge distribution for realistic nonempirical model intermolecular potentials for simulating energetic materials.
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Affiliation(s)
- Alexander A Aina
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
| | - Alston J Misquitta
- School of Physics and Astronomy and the Thomas Young Centre for Theory and Simulation of Materials at Queen Mary, University of London, London E1 4NS, U.K
| | | | - Sarah L Price
- Department of Chemistry, University College London, 20 Gordon Street, London WC1H 0AJ, U.K
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46
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Burnham CJ, English NJ. Crystal Structure Prediction via Basin-Hopping Global Optimization Employing Tiny Periodic Simulation Cells, with Application to Water-Ice. J Chem Theory Comput 2019; 15:3889-3900. [PMID: 31084025 DOI: 10.1021/acs.jctc.9b00073] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A crystal structure prediction algorithm for use in periodic boundary conditions with empirical rigid models is presented, which employs (i) unrestricted cutoff radii for the real-space interactions, thus allowing the treatment of even very small unit cells, and (ii) a global-optimization algorithm based on the basin-hopping method of Wales et al. (D. J. Wales and J. P. K. Doye, J. Phys. Chem. A 1997, 101, 5111). The algorithm is then applied to the TIP4P model of water (W. L. Jorgensen et al., J. Chem. Phys. 1983, 79, 926.) in order to find the lowest enthalpy water-ice crystalline structures in the pressure region 0-8000 bar, in unit cells holding in the range of 1-16 molecules, and a database of the 10 lowest enthalpy structures found at pressures 0, 4000, and 8000 bar is presented. The algorithm finds many of the ice polymorphs and, in particular, finds that the lowest energy structure at zero pressure is almost exactly tied between an ice Ic (cubic ice) and ice Ih (hexagonal ice) structure, having near-identical energies.
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Affiliation(s)
- Christian J Burnham
- School of Chemical and Bioprocess Engineering , University College Dublin , Belfield, Dublin 4 , Ireland
| | - Niall J English
- School of Chemical and Bioprocess Engineering , University College Dublin , Belfield, Dublin 4 , Ireland
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47
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LeBlanc LM, Johnson ER. Crystal-energy landscapes of active pharmaceutical ingredients using composite approaches. CrystEngComm 2019. [DOI: 10.1039/c9ce00895k] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Composite methods employing dispersion-corrected DFT consistently identify experimentally isolated polymorphs as the lowest-energy crystal structures of common APIs.
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Affiliation(s)
- Luc M. LeBlanc
- Department of Chemistry
- Dalhousie University
- Halifax
- Canada
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48
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Hoja J, Ko HY, Neumann MA, Car R, DiStasio RA, Tkatchenko A. Reliable and practical computational description of molecular crystal polymorphs. SCIENCE ADVANCES 2019; 5:eaau3338. [PMID: 30746448 PMCID: PMC6357866 DOI: 10.1126/sciadv.aau3338] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 11/28/2018] [Indexed: 05/12/2023]
Abstract
Reliable prediction of the polymorphic energy landscape of a molecular crystal would yield profound insight into drug development in terms of the existence and likelihood of late-appearing polymorphs. However, the computational prediction of molecular crystal polymorphs is highly challenging due to the high dimensionality of conformational and crystallographic space accompanied by the need for relative free energies to within 1 kJ/mol per molecule. In this study, we combine the most successful crystal structure sampling strategy with the most successful first-principles energy ranking strategy of the latest blind test of organic crystal structure prediction methods. Specifically, we present a hierarchical energy ranking approach intended for the refinement of relative stabilities in the final stage of a crystal structure prediction procedure. Such a combined approach provides excellent stability rankings for all studied systems and can be applied to molecular crystals of pharmaceutical importance.
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Affiliation(s)
- Johannes Hoja
- Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Hsin-Yu Ko
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Marcus A. Neumann
- Avant-garde Materials Simulation Deutschland GmbH, Alte Str. 2, 79249 Merzhausen, Germany
| | - Roberto Car
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Robert A. DiStasio
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, NY 14853, USA
| | - Alexandre Tkatchenko
- Physics and Materials Science Research Unit, University of Luxembourg, L-1511 Luxembourg, Luxembourg
- Corresponding author.
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49
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Stevenson EL, Lancaster RW, Buanz ABM, Price LS, Tocher DA, Price SL. The solid state forms of the sex hormone 17-β-estradiol. CrystEngComm 2019. [DOI: 10.1039/c8ce01874j] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The crystal structure of the female sex hormone has been established despite its high affinity for water.
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Affiliation(s)
| | | | | | - Louise S. Price
- Department of Chemistry
- University College London
- London WC1H 0AJ
- UK
| | - Derek A. Tocher
- Department of Chemistry
- University College London
- London WC1H 0AJ
- UK
| | - Sarah L. Price
- Department of Chemistry
- University College London
- London WC1H 0AJ
- UK
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50
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Price SL. Control and prediction of the organic solid state: a challenge to theory and experiment †. Proc Math Phys Eng Sci 2018; 474:20180351. [PMID: 30333710 PMCID: PMC6189584 DOI: 10.1098/rspa.2018.0351] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 08/15/2018] [Indexed: 11/12/2022] Open
Abstract
The ability of theoretical chemists to quantitatively model the weak forces between organic molecules is being exploited to predict their crystal structures and estimate their physical properties. Evolving crystal structure prediction methods are increasingly being used to aid the design of organic functional materials and provide information about thermodynamically plausible polymorphs of speciality organic materials to aid, for example, pharmaceutical development. However, the increasingly sophisticated experimental studies for detecting the range of organic solid-state behaviours provide many challenges for improving quantitative theories that form the basis for the computer modelling. It is challenging to calculate the relative thermodynamic stability of different organic crystal structures, let alone understand the kinetic effects that determine which polymorphs can be observed and are practically important. However, collaborations between experiment and theory are reaching the stage of devising experiments to target the first crystallization of new polymorphs or create novel organic molecular materials.
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Affiliation(s)
- Sarah L. Price
- Department of Chemistry, University College London, 20 Gordon St, London WC1H 0AJ, UK
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