Hunnisett Lily M, Nyman Jonas, Francia Nicholas, Abraham Nathan S, Adjiman Claire S, Aitipamula Srinivasulu, Alkhidir Tamador, Almehairbi Mubarak, Anelli Andrea, Anstine Dylan M, Anthony John E, Arnold Joseph E, Bahrami Faezeh, Bellucci Michael A, Bhardwaj Rajni M, Bier Imanuel, Bis Joanna A, Boese A Daniel, Bowskill David H, Bramley James, Brandenburg Jan Gerit, Braun Doris E, Butler Patrick W V, Cadden Joseph, Carino Stephen, Chan Eric J, Chang Chao, Cheng Bingqing, Clarke Sarah M, Coles Simon J, Cooper Richard I, Couch Ricky, Cuadrado Ramon, Darden Tom, Day Graeme M, Dietrich Hanno, Ding Yiming, DiPasquale Antonio, Dhokale Bhausaheb, van Eijck Bouke P, Elsegood Mark R J, Firaha Dzmitry, Fu Wenbo, Fukuzawa Kaori, Glover Joseph, Goto Hitoshi, Greenwell Chandler, Guo Rui, Harter Jürgen, Helfferich Julian, Hofmann Detlef W M, Hoja Johannes, Hone John, Hong Richard, Hutchison Geoffrey, Ikabata Yasuhiro, Isayev Olexandr, Ishaque Ommair, Jain Varsha, Jin Yingdi, Jing Aling, Johnson Erin R, Jones Ian, Jose K V Jovan, Kabova Elena A, Keates Adam, Kelly Paul F, Khakimov Dmitry, Konstantinopoulos Stefanos, Kuleshova Liudmila N, Li He, Lin Xiaolu, List Alexander, Liu Congcong, Liu Yifei Michelle, Liu Zenghui, Liu Zhi Pan, Lubach Joseph W, Marom Noa, Maryewski Alexander A, Matsui Hiroyuki, Mattei Alessandra, Mayo R Alex, Melkumov John W, Mohamed Sharmarke, Momenzadeh Abardeh Zahrasadat, Muddana Hari S, Nakayama Naofumi, Nayal Kamal Singh, Neumann Marcus A, Nikhar Rahul, Obata Shigeaki, O'Connor Dana, Oganov Artem R, Okuwaki Koji, Otero-de-la-Roza Alberto, Pantelides Constantinos C, Parkin Sean, Pickard Chris J, Pilia Luca, Pivina Tatyana, Podeszwa Rafał, Price Alastair J A, Price Louise S, Price Sarah L, Probert Michael R, Pulido Angeles, Ramteke Gunjan Rajendra, Rehman Atta Ur, Reutzel-Edens Susan M, Rogal Jutta, Ross Marta J, Rumson Adrian F, Sadiq Ghazala, Saeed Zeinab M, Salimi Alireza, Salvalaglio Matteo, Sanders de Almada Leticia, Sasikumar Kiran, Sekharan Sivakumar, Shang Cheng, Shankland Kenneth, Shinohara Kotaro, Shi Baimei, Shi Xuekun, Skillman A Geoffrey, Song Hongxing, Strasser Nina, van de Streek Jacco, Sugden Isaac J, Sun Guangxu, Szalewicz Krzysztof, Tan Benjamin I, Tan Lu, Tarczynski Frank, Taylor Christopher R, Tkatchenko Alexandre, Tom Rithwik, Tuckerman Mark E, Utsumi Yohei, Vogt-Maranto Leslie, Weatherston Jake, Wilkinson Luke J, Willacy Robert D, Wojtas Lukasz, Woollam Grahame R, Yang Zhuocen, Yonemochi Etsuo, Yue Xin, Zeng Qun, Zhang Yizu, Zhou Tian, Zhou Yunfei, Zubatyuk Roman, Cole Jason C
The Cambridge Crystallographic Data Centre, 12 Union Road, Cambridge CB2 1EZ, UK.
AbbVie Inc., Research & Development, 1 N Waukegan Road, North Chicago, IL 60064, USA.
Acta Crystallogr B Struct Sci Cryst Eng Mater. 2024 Dec 1;80(Pt 6):517-47. doi: 10.1107/S2052520624007492.
A seventh blind test of crystal structure prediction was organized by the Cambridge Crystallographic Data Centre featuring seven target systems of varying complexity: a silicon and iodine-containing molecule, a copper coordination complex, a near-rigid molecule, a cocrystal, a polymorphic small agrochemical, a highly flexible polymorphic drug candidate, and a polymorphic morpholine salt. In this first of two parts focusing on structure generation methods, many crystal structure prediction (CSP) methods performed well for the small but flexible agrochemical compound, successfully reproducing the experimentally observed crystal structures, while few groups were successful for the systems of higher complexity. A powder X-ray diffraction (PXRD) assisted exercise demonstrated the use of CSP in successfully determining a crystal structure from a low-quality PXRD pattern. The use of CSP in the prediction of likely cocrystal stoichiometry was also explored, demonstrating multiple possible approaches. Crystallographic disorder emerged as an important theme throughout the test as both a challenge for analysis and a major achievement where two groups blindly predicted the existence of disorder for the first time. Additionally, large-scale comparisons of the sets of predicted crystal structures also showed that some methods yield sets that largely contain the same crystal structures.
剑桥晶体学数据中心组织了第七届晶体结构预测盲测,其包含七个复杂度各异的目标体系:一个含硅和碘的分子、一个铜配位络合物、一个近乎刚性的分子、一个共晶体、一个多晶型的小农用化学品、一个高度柔性的多晶型候选药物以及一个多晶型吗啉盐。在聚焦于结构生成方法的这两部分内容的第一部分中,许多晶体结构预测(CSP)方法对于小而柔性的农用化学品化合物表现良好,成功再现了实验观测到的晶体结构,而对于更高复杂度的体系,只有少数团队取得成功。一项粉末X射线衍射(PXRD)辅助实验展示了CSP在从低质量PXRD图谱成功确定晶体结构方面的应用。还探索了CSP在预测可能的共晶体化学计量比方面的应用,展示了多种可能的方法。在整个测试过程中,晶体学无序成为一个重要主题,既是分析的挑战,也是一项重大成就,因为有两个团队首次盲目预测了无序的存在。此外,对预测晶体结构集的大规模比较还表明,一些方法生成的结构集在很大程度上包含相同的晶体结构。