Doctor Alexei Vagin, who died on 25 March 2023, contributed greatly to the practice of X-ray crystallography for over 50 years. He organized the (sparse) computing services of the protein group at the Moscow Institute of Crystallography during the 1970s and 1980s, then after his move to Western Europe in 1994, made major software contributions for macromolecular structure solution, all now distributed through CCP4.

Alexei was born in 1944 in Perm, the most easterly city in Europe, located in the Urals near the natural borderline between Europe and Asia. His family had been evacuated there during the war, but they returned to Moscow for his education. For his degree he studied applied physics at the prestigious Moscow Engineering Physics Institute, specializing in mathematical techniques and computer programming. He started his scientific career in material science – his first publication in 1966 was concerned with the design of blast furnaces, but soon he became more interested in crystallographic method development and moved to the protein group of the Moscow Institute of Crystallography. He was part of the team that solved the structures of bacterial ribonuclease in 1977, catalase in 1979 and was the key player behind the computational part of the latter project where he applied non-crystallographic symmetry (NCS) for phase improvement. From then on, he was involved in almost all the protein structure analyses in the laboratory, developing and implementing many tools. Unfortunately, most of these developments were never written up as Alexei always considered this part of science too boring, a sentiment to which he was loyal for the most part of his life. His PhD thesis, awarded in 1982, described an improved and faster translation function for use in molecular replacement calculations. He organized the software into BLANC, a comprehensive package with almost all necessary programs and libraries for crystallographic calculations, from experimental phasing to molecular replacement and map calculations. Considering that there was an embargo on computing resources for all of the Soviet Union, and those available to the institute were scarce, he had to come up with and implement clever algorithms that were both fast and used limited amount of RAM.

In 1990 the scientific scene in Moscow changed dramatically. Funding there became tighter and as the Iron Curtain dissolved it was possible for Russian scientists to move to laboratories in the West with better funding and equipment for science. Many laboratories worldwide benefitted greatly from this influx of well trained, motivated young people from the Moscow Institute (especially the York Structural Biology Laboratory!) but it meant Alexei was witnessing the decline of a great institute. In 1994 he joined the exodus, taking an EU-funded position in Brussels as a member of the team working on CRITQUAL. The Biotech contract he joined was entitled: ‘Integrated procedures for recording and validating results of 3D structural studies of biological macromolecules’. It brought together in a complementary manner several established European laboratories working in the field of macromolecular 3D coordinate provision and analysis. The insights provided into each other’s practices, working approaches and problems proved invaluable. This contract was a delight – all the participants were excited by the challenge and the six-monthly face-to-face meetings positively ‘fizzed’. Atomic resolution structures solved in Hamburg revealed that some of the underlying assumptions about protein conformation derived from the existing databases developed in the EBI and Uppsala were sometimes too restrictive, and Alexei in Brussels was able to quickly recast the new insights into a well designed computer readable form to be used within the refinement program framework being developed in York. He found an elegant solution to the problem of describing ‘LINKS’ – between peptides, nucleic acids, and to covalently linked ligands. The restraint formats (mmCIF) he helped design are now accepted as standard.

In 1998 when the Brussels funding was exhausted, he moved to York and re-joined an active crystallographic laboratory, where he stayed until his retirement in 2010. This was a wonderfully productive period for him, and the community of structural biologists continue to benefit from his work. The program SFCHECK developed in Brussels to assess the quality of the agreement between model and experimental data was modified for inclusion in the CCP4 suite. He contributed to further developments of REFMAC, advised laboratory members on programming problems, structure solution and partying. He was a highly sought-after tutor for training workshops, guaranteeing excellent teaching and good fun for all. But his life-long passion was for improving the methodology of molecular replacement. At one period when both Alexei and Jorge Navaza, the author of the AMoRe package, were working in York, it was tremendous fun to hear their on-going debates ranging from ‘what are the best scoring functions?’, to ‘why my fast Fourier routine is faster than yours... ’. In 1997 he published a description of a ‘new’ package, MOLREP, in the Journal of Applied Crystallography before releasing it through CCP4. It was in fact partly a reissue of much work he had done in Moscow, dating back to his 1982 PhD thesis, and partly described in the Russian journal, Kristallografiya.

MOLREP contained many innovative features that exploited information easily obtained from the experiment. For example, the package was able to analyse the model-free Patterson maps to consider non-crystallographic symmetry (NCS) and pseudo-translation if present. Once a search model was selected, MOLREP then analysed its shape and modified the search procedures to take this into account. In this package, Alexei introduced a translation function which considered all possible symmetry equivalents together. He also improved methods for searching for multiple copies and checked any solutions against the known NCS. Once a possible solution was found, the program checked whether it would pack, and positioned the symmetry copies to give optimal contacts for an assembly. One distinctive feature of Alexei’s approach to software development was a user-centred perspective and he took pains to report results and data analyses with informative graphs and extensive text. MOLREP was an instant hit and is still widely used by crystallographers and electron microscopists. Searching the Protein Data Bank (PDB) for references to it yields the amazing score of 36 223 entries.

Once Alexei was reasonably satisfied with the software, he turned his attention to model selection. A search to match a new sequence against the many structures available in the PDB will often produce many closely related hits. Alexei designed a database, distributed first in the package BALBES, and later as MorDa. This weeded the hits to include only the best model, and then catalogued whether the model structure existed as an oligomer, whether it could be split into flexible domains, and then used this information to design an optimal search strategy.

Alexei will be remembered for his innovative science, and for his interest in and kindness to his many colleagues, both in Moscow and Europe. But of course, he was not just a scientist and the many friends who mourn him remember his humour, his generosity both at work and play, and his wide-ranging conversations. While still in Moscow, he was one of the very few laboratory members with a car, and he was the one who took his colleagues to the airport for their departure to join various crystallographic laboratories in Europe, USA and Australia. He had no children of his own but was very good with those of his friends – one of whom, a grown up artist now, designed the MorDa icon, a wise friendly cat face. He loved Russian culture and his Russian friends, but never Russian politics. He was rather a citizen of the world with a passion for French chanson and movies, and deeply in tune with British black humour which matched his own. He was also profoundly grateful to the NHS which cared for him until his last moments. But his real homeland was the international community of protein crystallography, and that is where he will be remembered with love and gratitude.

This obituary was originally published in Acta Cryst. (2023). D79. 

For a list of papers by Dr Vagin appearing in IUCr journals click here.

The American Association for the Advancement of Science (AAAS) has announced the 2023 winners of eight longstanding awards for outstanding achievements, and we are delighted to report that Sekazi Mtingwa has won this year's AAAS Philip Hauge Abelson Prize. This award recognizes someone who has made significant contributions to the scientific community — whether through research, policy or civil service — in the US. The awardee can be a public servant, scientist or individual in any field who has made sustained, exceptional contributions and other notable services to the scientific community. Dr Mtingwa exemplifies a commitment to service and dedication to the scientific community, research workforce and society. His contributions have shaped research, public policy and the next generation of scientific leaders, according to the award’s selection committee.

As a theoretical physicist, Mtingwa pioneered work on intrabeam scattering that is foundational to particle accelerator research. Today a principal partner at Triangle Science, Education and Economic Development, where he consults on STEM education and economic development, Mtingwa has been affiliated during his scientific career with North Carolina A&T State University, Harvard University, the Massachusetts Institute of Technology and several national laboratories.

Sekazi Mtingwa (second from right) at the World Science Forum in Jordan in November 2017 with fellow speakers in the Thematic Session "Light Sources and Crystallographic Sciences for Sustainable Development" (from left): Juste Jean-Paul Ngome Abiaga (UNESCO), Michele Zema (IUCr), Giorgio Paolucci (SESAME), Maciej Nalecz (UNESCO) and Simon Connell (African Lightsource initiative).

His contributions to the scientific community have included a focus on diversity, equity and inclusion in physics. He co-founded the National Society of Black Physicists, the National Society of Hispanic Physicists, the African Physical Society and the African Lightsource Foundation. He is also co-founder and chair of LAAAMP, the IUPAP/IUCr/ICTP Lightsources for Africa, the Americas, Asia, Middle East and Pacific project. His work has also contributed to rejuvenating university nuclear science and engineering programs and paving the way for the next generation of nuclear scientists and engineers. Mtingwa served as the chair of a 2008 American Physical Society study on the readiness of the U.S. nuclear workforce, the results of which played a key role in the U.S. Department of Energy allocating 20% of its nuclear fuel cycle R&D budget to university programmes.

“I have devoted myself to being an apostle for science for those both at home and abroad who face limited research and training opportunities,” said Mtingwa. “Receiving the highly prestigious Philip Hauge Abelson Prize affirms that I have been successful in this mission. Moreover, it provides me with the armor to press onward to even greater contributions.”

Mtingwa was honoured with a tribute video at the 2023 AAAS Annual Meeting, held in Washington, DC, in March 2023. The prize includes a commemorative plaque and USD 5000.

Three IUCr Journal Poster Prizes were awarded at the annual conference of the British Crystallographic Association (BCA), held at the University of Sheffield, UK, just before Easter 2023. The criteria guidelines were that “The IUCr is pleased to offer a prize for each of the three best posters from an undergraduate, postgraduate or postdoctoral researcher with up to 3 years' experience in distinct areas of crystallography such as structural biology, structural chemistry and applied crystallography”. The judges were Dr Petra Bombicz (Hungary), Professor Bo Brummerstedt Iversen (Denmark), Dr Charlie McMonagle (France) and myself as Chair. There were 58 chemistry posters, 9 in biology, 20 in physics and 1 industrial. The standard of the posters and their science was very high. The prize winners were as follows, in alphabetical order:

Nicholas Funnell of the ISIS Neutron and Muon Facility, Rutherford Appleton Laboratory, Didcot, UK, whose poster was entitled “LMX – a new single-crystal, neutron time-of-flight diffractometer for large-molecule crystallography”.

Lavanya Kumar of the Faculty of Chemistry, University of Warsaw, Poland, whose poster was entitled “Correlating experimental and calculated charge density of halogen-bonded materials”.

Joshua Levinsky of the School of Chemistry, University of Edinburgh, UK, whose poster was entitled “The barocaloric and structural properties of choline-based plastic crystals”. [Barocaloric materials are characterized by strong, reversible thermic responses to changes in pressure and have potential use as refrigerants in cooling systems instead of gases such as hydrofluorocarbons.]

IUCr Poster Prize Awardees, from left: Nick Funnell, Lavanya Kumar and Joshua Levinsky. John Helliwell making the presentations at the conference dinner, held in the University of Sheffield Students’ Union building, to Nick and Joshua. Presentation photographs courtesy of Dr Iain Oswald of the University of Strathclyde.

The prize comprised a copy each of the IUCr’s Little Dictionary of Crystallography 3rd edition and a complimentary three-year membership of the IUCr Associates Programme.

Cryogenic electron microscopy (cryo-EM) of single particles is a powerful technique for the structural determination of biological macromolecules and significant advances in the field have been made over the last two decades (Kühlbrandt, 2014; Nogales, 2016). Improved electron detector technology (McMullan et al., 2016) and data analysis algorithms (Scheres, 2012; Punjani et al., 2017; Grant et al., 2018; Tegunov & Cramer, 2019), as well as specialized microscope software that streamlines data acquisition (Carragher et al., 2000; Mastronarde, 2005) have increased the accessibility of cryo-EM as a method for structure determination. Therefore, the number of protein and protein complex structures determined by single-particle cryo-EM is constantly increasing (see https://www.rcsb.org/stats/growth/growth-em).

For cryo-EM, a protein solution is frozen as a thin layer of vitrified ice that is embedded within a holey support film on an EM grid (Weissenberger et al., 2021). Freezing of cryo-EM grids usually needs to be extensively optimized for ice layer thickness, as well as protein particle concentration and integrity, by repeating cycles of cryo-EM screening and altering sample preparation (Passmore & Russo, 2016; Noble et al., 2018). Once the sample is optimized, a large number of randomly oriented particle images are acquired, classified, aligned and eventually reconstructed to a volume representing the coulomb potential density of the protein particle (Sigworth, 2016).

During cryo-EM grid screening and data acquisition, the microscope operator needs to manually pick suitable regions (squares) based on a grid overview (atlas) and select target holes with suitable ice thickness based on their appearance (Fig. 1). In many cases, ice thickness has to be chosen carefully to avoid broken or preferentially oriented particles (Noble et al., 2018; D’Imprima et al., 2019). Especially for the acquisition of large datasets, manual square and hole selection can be very time-consuming and less experienced operators may have difficulty targeting grid regions that yield high-quality data (Li et al., 2022). Nowadays, data analysis is done ‘on-the-fly’ during acquisition (Thompson et al., 2019), which gives valuable real-time information about data quality, and the microscope operator can adjust target selection based on the outcome. However, such trial-and-error strategies lead to the inefficient use of instruments that are in high demand and are expensive to maintain. Automation of the targeting of squares and holes during cryo-EM screening and data acquisition, therefore, has great potential to increase the throughput as well as the success rate of cryo-EM experiments for researchers of all experience levels.

In this issue of IUCrJ, Kim et al. (2023) present the software toolbox Ptolemy, which uses machine learning to automate the task of selecting target regions in single-particle cryo-EM screening and data collection. The algorithms within Ptolemy were pre-trained using metadata from annotated human operator microscope sessions. Ptolemy first addresses the automatic selection and ranking of suitable squares for data acquisition. To do so, Ptolemy uses a convolutional neural network [CNN, reviewed in Dhillon & Verma (2020)] classifier to predict the ‘collectability’ of squares on an atlas and can reproduce human expert operator selections on samples unknown to the neural network. Ptolemy then automatically finds holes on these squares using a neural network with U-Net (Ronneberger et al., 2015) architecture and 2D lattice restraints for the hole positions. The U-Net not only reproduces human operator selections with high precision, but the probabilities the U-Net assigns for a hole also appear to be suitable measures for the collectability of a hole. Altogether, Ptolemy provides an all-in-one solution for reliable and accurate automatic targeting of squares and holes on single-particle cryo-EM grids. This is a big step towards the full automation of cryo-EM screening and data collection and is readily implemented in the microscope operation software Leginon [for details of the implementation, see Cheng et al. (2023), also published in this issue of IUCrJ].

While Ptolemy uses specifically tailored and tuned CNN and U-Net machine-learning approaches to achieve high accuracy for recognizing and ranking squares and holes, other software have approached the problem of automatic data acquisition in slightly different ways. A conceptually similar approach was taken by SmartScope (Bouvette et al., 2022), which utilized dedicated square and hole finders to select targets for the operator. In comparison to Ptolemy, the SmartScope square and hole recognition procedures are based on an R-CNN with ResNet50 architecture and a YOLOv5 model with CSPNet backbone for square and hole recognition, respectively. It remains to be seen which deep-learning implementation yields better performance in real-life cryoEM imaging sessions. Notably, SmartScope implemented Ptolemy as an alternative to their own square and hole recognition algorithms (Bouvette & Viverette, 2022), so direct comparison will be possible.

A conceptually different approach is taken by cryoRL (Li et al., 2022). Instead of attempting to generate a complete selection of suitable squares and holes prior to cryo-EM imaging, cryoRL treats the selection of imaging targets as a path-planning problem where the algorithm is rewarded when imaging good targets. Currently, a target is considered good when it yields a cryo-EM image with high information content, which inversely correlates with ice layer thickness. However, the thinnest ice layer possible might not be a suitable target for acquiring data of sensitive or very large protein complexes (D’Imprima et al., 2019; Noble et al., 2018). Instead, other results from ‘on-the-fly’ data analysis, like complex integrity, particle number per image or the orientation distribution of particle views in the 3D reconstructions, could represent suitable quality targets.

It seems likely that combining the approaches taken by Ptolemy, SmartScope and cryoRL will lead to very powerful automatic cryo-EM data acquisition tools. Such tools would first generate highly accurate initial collectability rankings of squares and holes, whereas the process of data collection would be guided by sample-specific ‘on-the-fly’ decision-making that is based on data analysis results.

Acknowledgements

The author thanks Rebecca Thompson and James Walshe for critical reading of the manuscript.

References

Bouvette, J., Huang, Q., Riccio, A. A., Copeland, W. C., Bartesaghi, A. & Borgnia, M. J. (2022). eLife, 11, e80047.

Bouvette, J. & Viverette, E. (2022). External plugin installation – SmartScope documentation. https://docs.smartscope.org/docs/v0.7/.

Carragher, B., Kisseberth, N., Kriegman, D., Milligan, R. A., Potter, C. S., Pulokas, J. & Reilein, A. (2000). J. Struct. Biol. 132, 33–45.

Cheng, A., Kim, P. T., Kuang, H., Mendez, J. H., Chua, E. Y. D., Maruthi, K., Wei, H., Sawh, A., Aragon, M. F., Serbynovskyi, V., Neselu, K., Eng, E. T., Potter, C. S., Carragher, B., Bepler, T.& Noble, A. J. (2023). IUCrJ, 10, 77–89.

Dhillon, A. & Verma, G. K. (2020). Artif. Intell. 9, 85–112.

D’Imprima, E., Floris, D., Joppe, M., Sánchez, R., Grininger, M. & Kühlbrandt, W. (2019). eLife, 8, e42747.

Grant, T., Rohou, A. & Grigorieff, N. (2018). eLife, 7, e35383.

Kim, P. T., Noble, A. J., Cheng, A. & Bepler, T. (2023). IUCrJ, 10, 90–102.

Kühlbrandt, W. (2014). Science, 343, 1443–1444.

Li, Y., Fan, Q., Cohn, J., Demers, V., Lee, J. Y., Yip, L., Cianfrocco, M. A. & Vos, S. M. (2022). bioRxiv, 2022.06.17.496614.

Mastronarde, D. N. (2005). J. Struct. Biol. 152, 36–51. McMullan, G., Faruqi, A. R. & Henderson, R. (2016). Methods Enzymol. 579, 1–17.

Noble, A. J., Dandey, V. P., Wei, H., Brasch, J., Chase, J., Acharya, P., Tan, Y. Z., Zhang, Z., Kim, L. Y., Scapin, G., Rapp, M., Eng, E. T., Rice, W. J., Cheng, A., Negro, C. J., Shapiro, L., Kwong, P. D., Jeruzalmi, D., des Georges, A., Potter, C. S. & Carragher, B. (2018). eLife, 7, e34257.

Nogales, E. (2016). Nat. Methods, 13, 24–27.

Passmore, L. A. & Russo, C. J. (2016). Methods Enzymol. 579, 51–86.

Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. (2017). Nat. Methods, 14, 290–296.

Ronneberger, O., Fischer, P. & Brox, T. (2015). arXiv, 150504597.

Scheres, S. H. W. (2012). J. Struct. Biol. 180, 519–530.

Sigworth, F. J. (2016). Microscopy (Oxf). 65, 57–67.

Tegunov, D. & Cramer, P. (2019). Nat. Methods, 16, 1146–1152.

Thompson, R. F., Iadanza, M. G., Hesketh, E. L., Rawson, S. & Ranson, N. A. (2019). Nat. Protoc. 14, 100–118.

Weissenberger, G., Henderikx, R. J. M. & Peters, P. J. (2021). Nat. Methods, 18, 463–471.

This article was originally published in IUCrJ (2023). 10, 4-5.

Disordered crystal structures constitute about 28% of the entries in the Cambridge Structural Database (Groom et al., 2016). It is always exciting when a new data set comes off the diffractometer and one hopes for a rapid refinement of what is expected to be a routine structure determination, but then the discovery of disorder ruins one’s day when one realises that considerable time and effort will be needed to arrive at an optimal structure model. Sometimes the disorder is only present in a solvent molecule or counterion, e.g. a tumbling PF₆^– anion, where it is not so critical to develop a 'perfect’ model, but nonetheless, every improvement in the disorder model for such species usually improves the agreement factors and the precision of the atomic coordinates for all components in the structure, thereby leading to more precise geometric parameters, even in the non-disordered main component. For many analyses, the geometric parameters are the most tangible results of interest, so obtaining their best precision is important.

In crystal structures where the molecule or fragment of interest is disordered, the disorder might have no consequences for the understanding of the chemical species present, such as conformational variations in the puckering of a five-membered ring or in the orientation of a terminal –CF₃ group. In such cases, modelling the disorder is often, but not always, relatively straightforward.

At the other extreme, the challenge of dealing with extensive, subtle or even full-molecule disorder often requires much effort, because the positions of many atoms from the various disorder components are almost overlapping and it can be tricky to set up the best combination of restraints and/or constraints to allow the refinement to work smoothly while maintaining the correct chemical and geometrical logic of the species present. Full-molecule disorder can occur when the topology and polarity of the compound is such that the molecule can slot into its space in the crystal structure without caring about which way around it sits. A similar scenario can occur when more than one chemical species with similar topology is present in the crystal and they occupy the same crystallographic site; a mixture of diastereoisomers is one such example. Of course, these topological considerations are not necessarily limited to (entire) molecular species. Whether it is a molecular or an extended structure, a part of the asymmetric unit, such as a single ligand, might also fit into its cavity in more than one orientation or conformation.

A mixed-crystal full-molecule disorder situation is described in this issue of Acta Crystallographica Section C by Parkin et al. (2023). The authors revisit the product of an organic reaction published by some of the same authors (Mohamed et al., 2016), which at the time was described as the meso isomer of (E,E)-1,10-[1,2-bis(4-chlorophenyl)ethane1,2-diyl]bis(phenyldiazene) disordered across a crystallographic centre of inversion. Some unusual geometry subsequently noticed in the original model prompted the reevaluation. The new interpretation of the data leads to the conclusion that the crystal structure is more likely to be a three-component superposition of the meso form with, additionally, the S,S and R,R enantiomers. Such a superposition is feasible given the spatial similarities of the isomers. The matter is made more complicated by the question of whether or not the true space group is Cc or the centrosymmetric C2/c.

While the motivation of Parkin et al. (2023) is to improve on the original interpretation of the structure, the means of getting there is presented in a clear and instructive way. The article is thus a good learning example for dealing with a highly disordered structure and for what some people call ‘forensic crystallography’. Not only do the authors contend with modelling the disorder, but also deduce which chemical compounds are most likely to be present and address the space-group ambiguities. Usually, this sort of problem requires many trial refinements and, in general, practitioners should not feel reluctant to try out various ideas before settling on their final model. The problem is approached from both crystallographic and chemistry points of view. That is, the models for each of the disordered components have to be geometrically logical, as it is unlikely that such organic molecules would be geometrically distorted. The models should also account for the observed electron-density distribution; the presence of Cl atoms in these molecules makes their disordered positions stand out more clearly, thereby giving a starting point for developing the models, which understandably require a significant array of restraints and constraints. As with many complex disorder problems, there is probably not a unique way to select restraints and constraints to arrive at an acceptable model. The authors themselves state: ‘it is unlikely that any two crystallographers would settle on the same combination of constraints/restraints’. Finally, the chemical origin of the enantiomers and meso isomer has to be understood – originally only the presence of the meso compound had been assumed. This highlights the importance of critical and logical thinking and a good dialogue between the crystallographer and the scientist(s) producing the substances and interpreting the other spectroscopic data, if they are not the same person. These comments are not intended as a criticism of the original work – sometimes another pair of eyes and a different viewpoint reveal things that the others have not noticed.

Coincidentally, this issue of the journal reports another disordered mixed-crystal structure where the disorder is a consequence of the superposition of two diastereoisomers, one of which is additionally conformationally disordered, at the same crystallographic site in the crystal, treatment of which requires a three-component disorder model, although full-molecule disorder is probably not present (Linden et al., 2023).

Anecdotally, I was recently contacted by a young crystallographer who was struggling with the interpretation of a disordered structure that looked somewhat like the expected synthesis product, but was strange in other respects, especially some excessively long bonds. After discussing the synthesis of the material, we concluded that the crystal was a mixed-crystal composed of unreacted starting material and product, and the two species had crystallized randomly at the same crystallographic site. It was then possible to develop an appropriate disorder model for the structure, albeit still with some non-ideal geometry. I suggested that if it was at all possible still, some additional attempts at carefully optimizing the reaction and/or work-up and separation procedures might allow one to obtain the product in a more pure form. Indeed, the desired pure product was obtained subsequently and a clean crystal structure ensued, thus obviating the need to continue with or attempt to publish the mixed-crystal structure. Of course, the separation or purification of mixtures can sometimes be extremely difficult, but if tweaks to the procedures have not yet been tested, further attempts might be more fruitful than trying to continue with a messy, inferior quality, or even ambiguous, mixed-crystal structure determination.

Small-molecule crystallographers are fortunate today to have some excellent tools available to assist with the modelling of disorder. While the program SHELXL (Sheldrick, 2015) has long had an extensive array of restraint and constraint instructions (SADI, SAME, DFIX, DANG, SIMU, DELU and RIGU, to name just a few), manually developing the initial disorder model was sometimes cumbersome. Nowadays, the Olex² software (Dolomanov et al., 2009), as one example, has excellent and clever tools in the Graphical User Interface (GUI), which allow one, after a little practice, to split, drag and rotate fragments conveniently in order to obtain a good starting approximation to the disorder and then apply the appropriate restraints and/or constraints. The GUI of ShelXle (Hübschle et al., 2011) can be used in a similar way. Olex² also has a fragment database, which can be used to help model common fragments or solvent molecules. Excellent YouTube tutorials demonstrating many of the features of both of these programs, not just disorder handling, are available online.

Further discourses on many aspects of obtaining the best results from a crystal structure determination, including the handling disordered structures, can be found in Vinaya et al. (2023), Clegg (2019) and Linden (2020).

References

Clegg, W. (2019). Acta Cryst. E75, 1812–1819.

Dolomanov, O. V., Bourhis, L. J., Gildea, R. J., Howard, J. A. K. & Puschmann, H. (2009). J. Appl. Cryst. 42, 339–341.

Groom, C. R., Bruno, I. J., Lightfoot, M. P. & Ward, S. C. (2016). Acta Cryst. B72, 171–179.

Hübschle, C. B., Sheldrick, G. M. & Dittrich, B. (2011). J. Appl. Cryst. 44, 1281–1284.

Linden, A. (2020). Acta Cryst. E76, 765–775.

Linden, A., Bucher, C. B., Gubler, R., Villalgordo, J. M. & Heimgartner, H. (2023). Acta Cryst. C79, 104–111.

Mohamed, S. K., Younes, S. H. H., Abdel-Raheem, E. M. M., Horton, P. N., Akkurt, M. & Glidewell, C. (2016). Acta Cryst. C72, 57–62.

Parkin, S., Glidewell, C. & Horton, P. N. (2023). Acta Cryst. C79, 77–82.

Sheldrick, G. M. (2015). Acta Cryst. C71, 3–8.

Vinaya, Basavaraju, Y. B., Srinivasa, G. R., Shreenivas, M. T., Yathirajan, H. S. & Parkin, S. (2023). Acta Cryst. E79, 54–59.

This article was originally published in Acta Cryst. (2023). C79, 69–70. 

It is with great sadness that we learn of the passing of Dr Olga Kennard. Her long, successful life was full of many achievements, including founding the Cambridge Structural Database (CSD) which is now a fundamental resource that supports the global development of new drugs and materials that benefit us all, is used in chemistry education and contributes to the advancement of science. In this obituary for Dr Kennard we celebrate and recognize her many achievements in the scientific community.

Born in Hungary, Dr Kennard moved to the UK in 1939 just before the outbreak of the Second World War. After graduating from the University of Cambridge in 1944, she joined the Cavendish Laboratory under Lawrence Bragg as an assistant to Max Perutz in the Department of Physics.

After completing the first X-ray structure at the Laboratory (albeit on a very small structure), Dr Kennard moved to London in 1948 and then to the Chemistry Department at Cambridge University in 1962. At this point it was difficult to solve larger structures with crystallography and very unusual for crystallographers to be in a chemistry department. Crystallographers often experienced suspicion from more traditional chemists who thought this ‘upstart subject’ was taking over their territory.

Dr Kennard persevered and persuaded the department to purchase a diffractometer, the first to be used for small-molecule studies. With a small but gradually increasing group, supported by the Medical Research Council, Dr Kennard and colleagues worked on a variety of medical compounds including antibiotics and (excitingly) the structure of adenosine triphosphate.

As the volume of structural data increased, Dr Kennard along with Dr J. D. Bernal had a vision that the collective use of data would lead to new knowledge and generate insights:

‘We [J. D. Bernal and I] had a passionate belief that the collective use of data would lead to the discovery of new knowledge which transcends the results of individual experiments’ (Dr Olga Kennard).

This vision led to the founding of the CSD in 1965. From its humble beginnings, the CSD now contains over 1.2 million small-molecule organic and metal–organic crystal structures and is continually growing. Big-data learnings from the collective results are used globally to advance scientific research into pharmaceuticals, functional materials, catalysts and more in both commercial and academic research.

During her 1995 J. D. Bernal lecture, Dr Kennard had no doubt as to the future value of the database:

‘I think that the great ocean of truth is still in front of us and we will continue to discover new aspects of this truth’ (Dr Olga Kennard).

Dr Kennard went on to lead the CCDC until 1997 and authored over 140 structures during her career. One of her first structures with coordinates was published back in 1963 and was a chlorobenzoate salt (CSD refcode MSCBZO). Her more recent examples include a uridine structure, which was published in 1991 (CSD refcode JOSCAV).

Dr Kennard’s huge contribution to crystallography was recognized by many prestigious awards, prizes and elections to learned societies.

In 1987 she was elected a Fellow of the Royal Society and, in recognition of her work, there is the Royal Society Olga Kennard Research Fellowship in crystallography.

An OBE for ‘Services to Scientific Research on the Structure of Biological Molecules’ followed in 1988.

In 1993 Dr Kennard was elected a member of the Academia Europaea, and a Doctor of Law honoris causa was awarded to her by the University of Cambridge in 2003.

She won the Gmelin–Beilstein Memorial Medal in 2007, awarded by the German Chemical Society for scientists and scholars who have made an outstanding contribution to the history of chemistry, chemistry literature or chemical information.

In 2020 Dr Kennard was awarded the twelfth Ewald Prize by the International Union of Crystallography (IUCr) for ‘her invaluable pioneering contribution to the development of crystallographic databases, in particular the Cambridge Structural Database (CSD), which as she early foresaw, has led to the discovery of new knowledge which transcends the results of individual experiment’.

Recognition for Dr Kennard’s huge contribution to structural science continued right up to the end of her life with the award by the Royal Swedish Academy of Sciences of the Gregori Aminoff Prize for 2023 for establishing a crystallographic database. Dr Kennard was due to receive the award at the Aminoff Prize Symposium at the end of March.

This obituary is an edited version of that originally published by the Cambridge Crystallographic Data Centre (https://www.ccdc.cam.ac.uk/discover/news/celebrating-dr-olgakennard-1924-2023/). 

The IUCr 2023 organisers would like to acknowledge and thank the more than 1600 authors who responded to the Call for Abstracts (see the geographical distribution below), and all those who have taken advantage of early-bird registration.

Due to the size and capacity of the venue, we are happy to report that we have extended the space and are now in a position to accept additional submissions for Poster presentations. Therefore, the Organising Committee now invites prospective authors to submit poster abstracts for the Congress by 31 May. 

We are also excited to release some details regarding the IUCr 2023 Social program. For the duration of the Conference, daily morning, lunch and afternoon tea breaks are included in your registration fee. The traditional Welcome Function on Tuesday 22 August will be hosted at the Melbourne Convention and Exhibition Centre amongst our valued sponsors and exhibitors. We plan to provide some Australian treats and fine beverages on this occasion.

Rounding off the social program and celebrating the near end of the Conference on Monday 28 August, we will host the Gala dinner event “A Night at the Museum” at the famous Melbourne Museum. This is an event not to be missed. We promise this will be something special and includes access to the Dynamic Earth Exhibit, which is befitting for a dynamic crystallography group. All social functions, plus catering and transfers, are included in your registration. Please note that standard registration ends on 23 June but if you submit a poster and register by 31 May, you will receive the early bird rate!

For a chance to win a complimentary full registration, why not enter the Photo 51 - IUCr 2023 Photographic Competition? For the Coffee Category, we invite you to take a picture of yourself that best represents coffee OR art & culture in your hometown. We encourage you to think a little differently, have fun and be creative. Entries, which will be judged by the Melbourne Convention Bureau, will close on 15 June. Good luck!

Key dates 

After an enforced break of three years, we are delighted to announce that the IUCr Crystal growing competition for schoolchildren is back!

The competition is open to all schoolchildren (maximum age 18) and aims to introduce students to the exciting, challenging and sometimes frustrating world of growing crystals. This initiative was originally launched in 2014 as part of the celebrations for the International Year of Crystallography.

The winners of the 2023 edition of the IUCr Crystal growing competition will be those who most successfully convey their experiences to the panel of judges in a video report. Each contribution should clearly show or mention the experimental work carried out by the participants during the growing of their single crystals (compounds and methods used are free of choice). Furthermore the contribution should reflect in a creative way on the experimental work and theoretical background and/or applications.

Videos submitted to local competitions during 2022 may be also submitted to the IUCr competition.

The winning contributions in each category will receive 'Young crystal growers' certificates and medals.

Important dates

Closing date for submissions: 19 November 2023

Notification of winners and launch of 2024 edition: 29 January 2024

For more information, please visit the competition web page.