Abstract
The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and 'best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.
| Original language | British English |
|---|---|
| Pages (from-to) | 439-459 |
| Number of pages | 21 |
| Journal | Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials |
| Volume | 72 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Aug 2016 |
Keywords
- Cambridge Structural Database
- crystal structure prediction
- lattice energies
- polymorphism
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In: Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials, Vol. 72, No. 4, 01.08.2016, p. 439-459.
Research output: Contribution to journal › Article › peer-review
TY - JOUR
T1 - Report on the sixth blind test of organic crystal structure prediction methods
AU - Reilly, Anthony M.
AU - Cooper, Richard I.
AU - Adjiman, Claire S.
AU - Bhattacharya, Saswata
AU - Boese, A. Daniel
AU - Brandenburg, Jan Gerit
AU - Bygrave, Peter J.
AU - Bylsma, Rita
AU - Campbell, Josh E.
AU - Car, Roberto
AU - Case, David H.
AU - Chadha, Renu
AU - Cole, Jason C.
AU - Cosburn, Katherine
AU - Cuppen, Herma M.
AU - Curtis, Farren
AU - Day, Graeme M.
AU - DiStasio, Robert A.
AU - Dzyabchenko, Alexander
AU - Van Eijck, Bouke P.
AU - Elking, Dennis M.
AU - Van Den Ende, Joost A.
AU - Facelli, Julio C.
AU - Ferraro, Marta B.
AU - Fusti-Molnar, Laszlo
AU - Gatsiou, Christina Anna
AU - Gee, Thomas S.
AU - De Gelder, René
AU - Ghiringhelli, Luca M.
AU - Goto, Hitoshi
AU - Grimme, Stefan
AU - Guo, Rui
AU - Hofmann, Detlef W.M.
AU - Hoja, Johannes
AU - Hylton, Rebecca K.
AU - Iuzzolino, Luca
AU - Jankiewicz, Wojciech
AU - De Jong, Daniël T.
AU - Kendrick, John
AU - De Klerk, Niek J.J.
AU - Ko, Hsin Yu
AU - Kuleshova, Liudmila N.
AU - Li, Xiayue
AU - Lohani, Sanjaya
AU - Leusen, Frank J.J.
AU - Lund, Albert M.
AU - Lv, Jian
AU - Ma, Yanming
AU - Marom, Noa
AU - Masunov, Artëm E.
AU - McCabe, Patrick
AU - McMahon, David P.
AU - Meekes, Hugo
AU - Metz, Michael P.
AU - Misquitta, Alston J.
AU - Mohamed, Sharmarke
AU - Monserrat, Bartomeu
AU - Needs, Richard J.
AU - Neumann, Marcus A.
AU - Nyman, Jonas
AU - Obata, Shigeaki
AU - Oberhofer, Harald
AU - Oganov, Artem R.
AU - Orendt, Anita M.
AU - Pagola, Gabriel I.
AU - Pantelides, Constantinos C.
AU - Pickard, Chris J.
AU - Podeszwa, Rafal
AU - Price, Louise S.
AU - Price, Sarah L.
AU - Pulido, Angeles
AU - Read, Murray G.
AU - Reuter, Karsten
AU - Schneider, Elia
AU - Schober, Christoph
AU - Shields, Gregory P.
AU - Singh, Pawanpreet
AU - Sugden, Isaac J.
AU - Szalewicz, Krzysztof
AU - Taylor, Christopher R.
AU - Tkatchenko, Alexandre
AU - Tuckerman, Mark E.
AU - Vacarro, Francesca
AU - Vasileiadis, Manolis
AU - Vazquez-Mayagoitia, Alvaro
AU - Vogt, Leslie
AU - Wang, Yanchao
AU - Watson, Rona E.
AU - De Wijs, Gilles A.
AU - Yang, Jack
AU - Zhu, Qiang
AU - Groom, Colin R.
N1 - Funding Information: The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr Peter Horton (XXII), Dr Brian Samas (XXIII), Professor Bruce Foxman (XXIV) and Professor Kraig Wheeler [(XXV) and (XXVI)]. We are also grateful to Dr Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of (XXVI), as well as numerous colleagues at the CCDC for assistance in organizing the blind test. Submission 2: We acknowledge Dr Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements No. 307358 (ERC-stG-2012- ANGLE) and No. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures using the GAUSSIAN98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6:We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organization for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr Bouke van Eijck for his valuable advice on our predicted structure of (XXV). We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial support from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 'Toward Crystal Engineering from First Principles', by the NSF award # EPS-1003897 'The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)', and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the US Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from the College of Engineering at Khalifa University and I am grateful for the support of Professor Robert Bennell and Professor Bayan Sharif in facilitating the acquisition of all necessary resources. All of the theoretical data reported in this work were obtained using the High Performance Computing Cluster of Khalifa University and Dr Yacine Addad is acknowledged for providing systems support. Dr Louise S. Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous email exchanges concerning the blind test. Professor Sarah L. Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom's Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: RJN acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the UK [EP/J017639/1]. RJN and CJP acknowledge use of the Archer facilities of the UK's national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/ 1]). CJP also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. BM acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, through grant ESPRC EP/ K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the US Army Research Laboratory and the US Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the US Army Research Laboratory and the US Army Research Office under contract/grant number W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project No. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: JH and AT acknowledge support from the Deutsche Forschungsgemeinschaft under the program DFGSPP 1807. H-YK, RAD and RC acknowledge support from the Department of Energy (DOE) under Grant No. DESC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University. Publisher Copyright: © Anthony M. Reilly et al. 2016.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and 'best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.
AB - The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and 'best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z′ = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The results of the sixth blind test of organic crystal structure prediction methods are presented and discussed, highlighting progress for salts, hydrates and bulky flexible molecules, as well as on-going challenges.
KW - Cambridge Structural Database
KW - crystal structure prediction
KW - lattice energies
KW - polymorphism
UR - http://www.scopus.com/inward/record.url?scp=84982852155&partnerID=8YFLogxK
U2 - 10.1107/S2052520616007447
DO - 10.1107/S2052520616007447
M3 - Article
AN - SCOPUS:84982852155
SN - 2052-5192
VL - 72
SP - 439
EP - 459
JO - Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials
JF - Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials
IS - 4
ER -