Figure 1. Wayne Hendrickson (front row, center) with former and current members of his research group at the Hendrickson Reunion Symposium, Columbia University, April 2022.

The 2023 Ewald Prize honors Wayne Hendrickson for his many contributions to the field of macromolecular crystallography. His monograph, ‘Facing the phase problem’, is a beautifully written short history of crystallographic phasing, with a focus on experimental phasing. It begins in the early years of crystallography, with the dawning recognition that phase determination is a ‘problem’, and includes the contributions of Paul Ewald, for whom the Prize is named.

Wayne’s interest in the phase problem began when he was a PhD student at Johns Hopkins University in the laboratory of Werner Love. He and fellow PhD student Ed Lattman developed a method to represent the probability distribution for the phase of each reflection as four numbers, known as Hendrickson–Lattman or ABCD coefficients. Their landmark paper (published in Acta Cryst. B, 1970) appeared just after they received PhD degrees. The ABCD coefficients provided a simple means to combine phase information from sources as vastly different as isomorphous replacement, partial models, redundancy in the asymmetric unit, molecular replacement, and anomalous scattering. Phase combination became an essential tool of macromolecular crystallography as researchers tackled more challenging molecular systems that yielded crystals of increasingly poor diffraction quality.

Long before the explosive growth of macromolecular crystallography, Wayne continued his work on the phase problem as a postdoc with Jerome Karle at the US Naval Research Laboratory (NRL). There he sought to apply Karle’s direct-methods phasing to protein crystallography. However, he quickly became intrigued with an idea to solve the phase problem solely from the anomalous scattering of a few atoms in the protein crystal. This led to the famous crambin experiment. In a tour de force of data collection, Wayne recorded diffraction data from a crambin crystal using the Cu Kα emission of a sealed-tube X-ray generator equipped with a four-circle diffractometer and a single-point scintillation detector. The data were punched on paper tape, one reflection at a time, as the tape unspooled onto the floor. Some time during the multi-day experiment, a staff member tasked with cleaning the floor ripped the precious unspooled tape from the punch device but, happily, did not remove it from the lab. Wayne processed the data and developed a method to solve the structure using the anomalous scattering of the six sulfur atoms in crambin. To do this, he started with Jerome Karle’s parameterization of the structure factor equation and formulated an observational equation relating the phase and phase probability for each reflection to the observed anomalous difference. This approach allowed him to combine phase probabilities from anomalous scattering and from the sulfur partial structure (via ABCD coefficients!), yielding a lovely interpretable 1.5 Å electron density map for crambin.

Simultaneous with the crambin success, Wayne and NRL colleague John Konnert developed the first widely used software for crystallographic refinement of protein atomic models. Their major innovation was to include elements of protein stereochemistry (well established bond lengths, angles, etc.) as observations on an equal footing with diffraction data and to refine the atomic models by least-squares minimization. The Konnert and Hendrickson concept of stereochemical details as observables has been in continuous use since then, although today’s software for refinement is far faster and more robust.

To crystallographers working today, Wayne is best known for his role in the breathtaking transformation of protein crystallography into structural biology, which occurred since the turn of the century. Anomalous scattering was prominent in this transformation. Wayne spurred the development of reliably tunable synchrotron beamlines to enhance the weak phasing signal in most anomalous diffraction experiments. He did this by solving novel structures of high biological impact using anomalous diffraction data from tunable beamlines at several synchrotrons. Ever fearless in deploying new technologies to the aid of protein crystallography, he led the development of a cutting-edge tunable beamline for macromolecular crystallography at the Brookhaven synchrotron. Ever motivated to improve crystallographic methods, Wayne developed the multi-wavelength anomalous diffraction method – with the memorable acronym MAD. For MAD, he extended the phasing formulation of the crambin experiment to multi-wavelength data. Arguably of broadest impact, Wayne envisioned a general method to incorporate selenomethionine (SeMet) in recombinant proteins. The ease of introducing an anomalous scatterer that does not interfere with the native structure or the function of a protein was truly transformative. By 2010, SeMet anomalous scattering had become the favored method for experimental phasing in protein crystallography, and so it remains today. When radiation damage from the bright X-ray beams of undulator sources challenged multi-wavelength experiments, MAD was quickly replaced by single-wavelength anomalous diffraction – with the equally memorable acronym SAD.

Wayne also sought to bring the results of protein crystallography to a broad audience at an opportune time. The Protein Data Bank grew by less than 100 entries per year before 1990 and exploded to nearly 700 entries per year in 1993. Correctly anticipating the rapid growth that followed, Wayne was founding editor of Current Opinion in Structural Biology (1991, with Aaron Klug), the annual volume Macromolecular Structures (1991–2000, with Kurt Wüthrich), and Structure (1993, with Carl Brändén).

Wayne’s seminal contributions to macromolecular crystallography and his enthusiasm for protein structure have attracted many talented trainees to his lab. More than 50 current and former lab members (see Fig. 1) and many more friends, collaborators and colleagues gathered at the 2022 Hendrickson Reunion Symposium at Columbia University. The symposium followed a joyous reunion party and featured a full day of talks from several trainees among the many who went on to lead successful research groups in structural biology. The event was a fitting recognition of Wayne Hendrickson as a leading light of macromolecular crystallography, both for his development of seminal methods that now make X-ray crystallography a standard structural biology approach and his mentorship in training the next generation of creative scientists who continue to expand the reach of X-ray crystallography into the biological sciences. His article to accompany the Ewald Prize, published in this issue of IUCrJ (Hendrickson, 2023), is a terrific addition to our field.

References

Hendrickson, W. A. (2023). IUCrJ, 10, 521–543.

 

This article was originally published in IUCrJ (2023). 10, 555–556. 

Crossing the Nullarbor Plain from Perth, Western Australia, on the 1,700 km long Eyre Highway to attend the Crystal 5 meeting at Monash University, Victoria, in August 1967. Left to right: Biswanith Mukajee, Syd Hall and Ted Maslen. Photo credit: Syd Hall, using a time delay on the camera exposure, judging from the shadow of the tripod. Image reproduced from the IUCr photo gallery.

I joined the (then) Society of Crystallographers in Australia (SCA) soon after its formation in 1976 and was privileged to serve as its Honorary Secretary for three terms from 1982. However, work eventually took me away from direct participation in crystallographic research, and I lost touch with the Society. Many years later, after reconnecting, I realized that crystallography and the Society had changed significantly. The original pioneers of the Society, to whom it owed a great debt, were greatly diminished in number, and unless its rich and illustrious history was soon recorded, it would be lost forever. In early 2022, I contacted the then President (Megan Maher) and the Council of the now Society of Crystallographers in Australia and New Zealand and offered to write its history. To my delight, they accepted my offer; some snippets from the resultant manuscript are provided below.

The Society of Crystallographers in Australia and New Zealand (SCANZ) has existed in three configurations over the last 60+ years. The first version is generally recognized as emerging in May 1961 in association with the first ‘open’ (i.e. not just internal institutional) meeting of Australian crystallographers (since dubbed ‘Crystal 1’) at the University of Sydney. This meeting of what later became known as the ‘Bush Crystallographers’ was the initiative of Hans Freeman, then Professor of Chemistry at the University of Sydney. Hans was also central to the movement in 1973 to establish the Society of Crystallographers in Australia (SCA) and was elected as its inaugural President at the Crystal 10 meeting in Richmond, NSW, in April 1976. In acknowledgment of the major and long-term engagement of colleagues from ‘across the ditch’ (aka New Zealand), the name was changed to the Society of Crystallographers in Australia and New Zealand (SCANZ) at the Crystal 21 meeting in Thredbo, NSW, in February 2000. 

The original Bush Crystallographer ‘members’ were a small group of individuals who, for the most part, had learned their trade as postgraduate or postdoctoral students overseas, working with some of the icons of crystallography in the early post-WWII period (inter alia Kathleen Lonsdale, Linus Pauling, Dorothy Hodgkin, Edward W. Hughes and J. Monteath Robertson). Among these, first-generation Australian pioneers in the early 1950s and 1960s may be counted: Hans Freeman (Sydney University); ‘Sandy’ Mathieson, Barrie Dawson and Dave Wadsley (CSIRO); Jack McConnell and Nev Stephenson (University of NSW); Maureen Mackay (La Trobe University); Alan White, Jim Graham and Ted Maslen (University of Western Australia); Bryan Gatehouse (Monash University) and Terry Sabine (Australian Atomic Energy Commission, now ANSTO). 

They established the first tranche of significant crystallography laboratories in Australia and were key players in the organisation of the early Crystal meetings and the formation of the SCA. Their graduate students, in turn, established second-generation groups at other universities and research institutions in Australia and overseas. A corresponding group of New Zealand crystallographers founded major laboratories at Industrial Research Lower Hutt (George Patterson), University of Auckland (F. J. Llewellyn), University of Canterbury (Bruce Penfold) and University of Otago (A. J. Ellis). Fig. 1 shows some of these key players at Crystal 1 at Sydney University in 1961, and Fig. 2 shows several others, probably at Crystal 4 at Lucas Heights in 1966.

 

Throughout its existence, both as a collective and through its individual members, SCANZ has played a very significant role in the development of the crystallography landscape in Australia, New Zealand and overseas. It was a foundation partner in the Federation of Scientific and Technological Societies (FASTS), the political lobby group for increased funding for Australian science and technology; it was a major actor in the push for funding for Australian access to major synchrotron and neutron facilities overseas (the so-called ‘suitcase science’/‘Small Country Big Science’ initiative). Its members were prime movers in the establishment of the Australian National Beamline Facility (ANBF) at the Tsukuba synchrotron in Japan, and they were also key advocates for the establishment of the Australian Synchrotron and the new OPAL research reactor. They also led or participated in many of the technical committees advising on the type and design of beamlines for those facilities. Along with the Crystallographic Society of Japan, the Society was a strong proponent and prime mover in the establishment of the Asian Crystallographic Association (AsCA) in 1987 and, until recently, one of only four Regional Associates of the International Union of Crystallography (IUCr).

Through the Society’s ex officio representative (and other independent members) on the National Committee for Crystallography of the Australian Academy of Science, the Society is (in practical terms) the primary link for Australia’s engagement with the IUCr. Society members have acted as President and Vice-President of the IUCr, served on its Executive Committee, and occupied seats on all 22 Commissions of the IUCr at one time or another, often as Chair. It has been the organiser of two of the IUCr Congresses and General Assemblies held since 1948, the 14th in Perth in 1987 and the 26th in Melbourne in 2023, and it devoted considerable resources to the Australia-wide celebration of the International Year of Crystallography in 2014. It maintains a strong supportive presence (both financial and participatory) in AsCA meetings. 

Since 1961, its series of regular national meetings (to date, 34 and counting; Fig. 3) and, since 1980, its Newsletters (79 and counting) have provided critical and effective platforms for the exchange and dissemination of scientific information, science politics and personalia, past, present and future in the domestic and international crystallographic domains. 

The Crystal meetings and newsletters continue to provide an important and fertile connection point for professional and student crystallographers in Australia and New Zealand. They have served to celebrate and encourage the achievements of members and to engender a sense of a crystallographic community across both nations. From interviews with some of the early participants in these meetings (and from my own recollections), they were certainly memorable affairs, often showcasing (aside from science) the musical, singing and raconteurial talents of otherwise quite often shy and retiring scientists. Not to be missed, as evidenced by the small groups of crystallography lecturers from the University of Western Australia and their students who were willing to endure a road trip over 3–4 days (with rotating drivers and sparse accommodation) of more than 3,400 km, in part across the Nullarbor Plain on the then unsealed (dirt) Eyre ‘Highway’, from Perth to Melbourne to attend the meetings, and back again (see top photo).

Along with the Crystal and IUCr meetings, SCANZ has organised several significant one-off events, including the Bragg Symposium in Adelaide in 2012 to mark the centenary of the founding of X-ray crystallography by W. Lawrence Bragg (born and educated in Adelaide), a field in which he and his father, William H. Bragg, made pre-eminent contributions recognised by the award of the Nobel Prize for Physics in 1915. Another event was the 1991 dedication ceremony for the ‘A.D. Wadsley X-ray Laboratory’, held at the CSIRO Division of Mineral Products, Port Melbourne, in recognition of David Wadsley's pioneering contributions to crystallography and solid-state chemistry (Fig. 4). Participants included David’s family and many of his friends and colleagues (most of whom were foundation members of the SCA) from around the country and overseas. 

The structure and culture of the Society have gone through several major changes over its 60+ years, from an ad hoc small informal grouping of most of the early crystallographers in Australia funded by local organising institutions to its present position as a formally incorporated entity with active global engagement and a membership of nearly 300 people, around 50% of whom are students. Its financial resource is now more than AUS$2.3M, the investment returns from which allow it to offer travel scholarships to prominent overseas speakers and students to attend national and international meetings. These funds also enable awarding of the Bragg and Mathieson Medals to outstanding mature and early-career researchers at each Crystal meeting.

Diversity and gender equity was introduced in 2020 as a formal policy of the Society, applied in particular to Office Bearers and speaking and session-chair roles at all its meetings. It has also instituted a policy of encouraging young researchers through its Rising Stars Awards at each national meeting, along with an allowance for carer’s provisions.

From its initial focus (typical of the time) on the crystallography of inorganic materials and minerals, the Society has embraced increasing focus on structural biology as humanity responds to the need for greater understanding of the nature and function of molecules essential to life. It is also adjusting to the massive change in the ‘face’ of the science of crystallography over the years, from a unique and important discipline in its own right to a still extremely important but now largely enabling discipline underpinning the broader biological, materials, chemical and physical sciences. Emerging technologies and software, such as cryo-EM and massive protein folding algorithms based on artificial intelligence for the solution of macromolecule structures, are also providing new challenges. 

Although crystallographic data collection and structure solution is now, for most compounds, largely automated, the need for advances in crystallographic science and equipment to deal with ever larger and more complex materials (especially in the biological domain) has ensured that the discipline remains as important and rewarding for researchers as ever. The Society has greatly assisted adaption to these changes through its generous financial support for student attendance at national and international crystallography meetings and its continued commitment to the teaching of crystallography through its Australian Crystallography Schools (in partnership with the Australian Synchrotron), which have operated since 2008. 

As a result of all these actions, the Society’s meetings remain relevant and exciting, and continue to attract the best speakers from home and abroad by showcasing the most relevant and exciting science of the day.

 

Dr Roderick J. Hill DSc FTSE FRACI FAusIMM was Secretary of the SCA 1982–1987. He is a former Chief Research Scientist at CSIRO and PVC for Industry Engagement and Commercialisation at Monash University, Victoria, Australia.

Artificial intelligence has revolutionized many societal and scientific domains, and structural biology benefits from one of its most spectacular breakthroughs. The deep learning algorithm AlphaFold can predict with unparalleled accuracy the three-dimensional structure of folded proteins based solely on their sequence. In 1972, Christian Anfinsen was awarded the Nobel Prize in Chemistry for his groundbreaking work on ribonuclease which demonstrated that all the protein’s folding information is encoded within its sequence. This ignited a surge of experimental and computational investigations into protein folding to unravel what was at the time referred to as the ‘second half of the genetic code’ and understand the mechanisms governing the protein’s pathway towards its final three-dimensional conformation.

Now, half a century after Anfinsen’s seminal article (Anfinsen, 1973), it appears that a long-awaited milestone has been reached and that one can now correlate a one-dimensional string of amino acids to an accurate three-dimensional structure. However, challenges still persist. The fundamental nature of artificial intelligence lies in its initial training using data that have accumulated over many years, the Protein Data Bank (PDB) in the case of AlphaFold. The PDB suffers from inherent biases: certain families of structures are under-represented due to the limitations of the methods used to solve the protein structures, in particular X-ray crystallization and cryo-electron microscopy (cryoEM). This is typically the case of proteins that exhibit a high conformational flexibility and cannot be described by a single three-dimensional structure. In particular, intrinsically disordered proteins (IDPs) or regions (IDRs) of proteins can adopt a tremendous number of conformations and this high dynamic is inherent to their function. Because of their flexibility, these polypeptides are often invisible in the structures solved by X-ray crystallization or cryoEM. Their flexibility may even preclude protein crystallization or lead to poorly diffracting crystals. In addition, a short disordered segment can undergo an induced folding upon binding to a partner, but may adopt different folds depending on the binding partner and the interface of interaction, further complicating accurate predictions. Therefore, AlphaFold could not train properly on disordered structures, which lack structural homologues in the PDB. Furthermore, AlphaFold uses multiple sequence alignments, while IDRs are very difficult to align because they are poorly conserved. For all these reasons AlphaFold cannot predict for now the 3D structure of long flexible disordered regions with accuracy and provides low confidence scores on these predictions. AlphaFold’s creators even suggest that the low confidence scores can be used as a method to predict protein disorder. Therefore, the single static representation of the structure of proteins containing IDRs provided by AlphaFold cannot convey all their structural and functional properties.

A very interesting strategy to circumvent this difficulty is to integrate AlphaFold predictions with ensemble molecular modelling and experimentally derived constraints, as proposed by Brookes et al. (2023) in their paper entitled AlphaFold-predicted protein structures and small-angle X-ray scattering: insights from an extended examination of selected data in the Small-Angle Scattering Biological Data Bank. Small-angle X-ray scattering (SAXS) is a particularly suitable experimental method for providing such constraints. SAXS data contain all the 3D information on the various conformations adopted by a macromolecule in solution. By calculating the SAXS profile from atomic coordinates and comparing it with experimental SAXS data, it becomes possible to select an ensemble of conformations that collectively contribute to the observed scattering spectrum. These conformers are generated through molecular modelling techniques that allow incorporation of information on the protein flexibility into the predicted structures.

To prove the effectiveness of this strategy, Brookes and co-workers utilized the Small Angle Scattering Biological Data Bank (SASBDB) as an additional resource. They selected monomeric AlphaFold models with a corresponding SASDBD entry, where the single AlphaFold model did not account for the collected SAXS data. The candidate proteins are composed of several folded domains connected by at least one long extended linker of more than 30 amino acids. These linkers are predicted to be unstructured by AlphaFold, with a low confidence score. Brookes and co-workers considered these regions as flexible and generated an ensemble of structures by exploring the conformational space of these regions using a Monte Carlo approach. They then selected the optimal ensemble of conformers and thus reached remarkable agreements with the SAXS data. Hence, by taking into account the conformational heterogeneity of the linkers, guided by the SAXS experimental data, they significantly improved the accuracy of the AlphaFold structural predictions (Fig. 1).

Besides the remarkable improvement in the structural description of the disordered domains, this article is striking for its rigorous analysis of the SAXS data. The authors are long-standing experts in small-angle scattering for structural biology, and they know all the strengths and limits of the technique (Trewhella et al., 2022, 2017). In this new paper, Brookes, Rocco, Vachette and Trewhella explain with a lot of teaching the methodology, quality assessment, pitfalls and difficulties of SAXS data analysis that need to be known before any atomistic modelling, with an emphasis on the specific case of proteins with long IDRs. Their thorough approach and their valuable advice will undoubtedly inspire and guide structural biologists struggling with SAXS experiments on IDPs, enabling them to confidently extract all the relevant information on their favourite protein from their data.

Finally, this paper successfully addressed the limitations of AlphaFold in predicting the structure of proteins with long IDRs, by incorporating adequate conformational flexibility. While AlphaFold has enabled considerable advances in structural biology, its next challenge is to accurately predict the conformations preferentially adopted by IDPs and IDRs. Efforts are currently being made to develop accurate predictions of conformational ensembles using machine learning with reduced computational cost (Zheng et al., 2023). However, the conformational sampling of IDPs or IDRs is extremely sensitive to the environmental conditions, such as pH, temperature, redox conditions, crowding, ligand binding, post-translational modifications etc., and this is the motor of their activity. Experimentally derived constraints accounting for these conditions therefore remain necessary to accurately describe the dynamics and structural preferences that drive the functional properties of an IDP. SAXS, being one of the few experimental techniques that give access to the conformational sampling of proteins in solution, combined with ensemble modelling and AlphaFold predictions offers a promising strategy for adequately describing the structure and dynamics of IDPs and is expected to yield numerous successful advances in the understanding of these proteins.

References

Anfinsen, C. B. (1973). Science, 181, 223–230.

Brookes, E., Rocco, M., Vachette, P. & Trewhella, J. (2023). J. Appl. Cryst. 56, 910–926.

Trewhella, J., Duff, A. P., Durand, D., Gabel, F., Guss, J. M., Hendrickson, W. A., Hura, G. L., Jacques, D. A., Kirby, N. M., Kwan, A. H., Pérez, J., Pollack, L., Ryan, T. M., Sali, A., Schneidman-Duhovny, D., Schwede, T., Svergun, D. I., Sugiyama, M., Tainer, J. A., Vachette, P., Westbrook, J. & Whitten, A. E. (2017). Acta Cryst. D73, 710–728.

Trewhella, J., Vachette, P., Bierma, J., Blanchet, C., Brookes, E., Chakravarthy, S., Chatzimagas, L., Cleveland, T. E., Cowieson, N., Crossett, B., Duff, A. P., Franke, D., Gabel, F., Gillilan, R. E., Graewert, M., Grishaev, A., Guss, J. M., Hammel, M., Hopkins, J., Huang, Q., Hub, J. S., Hura, G. L., Irving, T. C., Jeffries, C. M., Jeong, C., Kirby, N., Krueger, S., Martel, A., Matsui, T., Li, N., Pérez, J., Porcar, L., Prangé, T., Rajkovic, I., Rocco, M., Rosenberg, D. J., Ryan, T. M., Seifert, S., Sekiguchi, H., Svergun, D., Teixeira, S., Thureau, A., Weiss, T. M., Whitten, A. E., Wood, K. & Zuo, X. (2022). Acta Cryst. D78, 1315–1336.

Zheng, L.-E., Barethiya, S., Nordquist, E. & Chen, J. (2023). Molecules, 28, 4047.

 

This article was originally published in J. Appl. Cryst. (2023). 56, 1313–1314. 

Investigations into charge density focus on deviations from spherical valence density to describe the bonding situation in a specific structure. The Hansen & Coppens (1978) multipole model can be used to describe this aspherity, because this model partitions the electron density in the core, the spherical valence density and the aspherical valence density. This model needs more parameters compared to the independent atom model which uses just spherical atomic form factors. The deviations from spherity are very small compared to the electron density from the core. Therefore, excellent high-resolution data are necessary. The information about the valence density is mainly contained in the low-order data, while high-resolution data are needed to deconvolute aspherical atomic electron density from thermal vibrations. The data need to be of very good quality along the whole resolution range, and especially the low-order data need to be collected with high accuracy.

In recent decades, there have been numerous new developments in the fields of sources and detectors. In terms of detectors, technology has progressed from point detectors to CCD and nowadays energy-discriminating pixel detectors, which greatly reduced the data collection time and which foster spectral purity. The development in sources from sealed tubes to microsources, rotating anodes, MetalJet to synchrotrons radiation supplies more and more beam intensity. There is a strong tradition to examine which of these new developments really provide better data for charge density investigations, e.g. Martin & Pinkerton (1998), Coppens et al. (2005), Jørgensen et al. (2014), Wolf et al. (2015), Graw et al. (2023), Ruth et al. (2023). Higher resolution is not enough, excellent low-order data are also needed, and the question is which combination of hardware leads to reliable statements about the bonding situation in a particular compound.

This tradition continues with the paper of Vosegaard et al. (2023). The authors compare data collected at 100 K from new in-house diffractometers, a Rigaku Synergy-S (Mo and Ag source, HyPix100 detector) and a Stoe Stadivari (Mo source, EIGER2 1M CdTe detector) and an older Oxford Diffraction Supernova (Mo source, Atlas CCD detector) to an investigation with excellent synchrotron data collected at 25 K and λ = 0.248 Å at the BL02B1 beamline at SPring-8 (Vosegaard et al., 2022). As the test structure, melamine was selected.

First, the authors investigate the data quality by comparing figures of merit such as R_int and I/σ. Of course, the SPring-8 data win concerning the highest possible resolution and lowest collection time. However, considering the variation of R_int and I/σ over the whole resolution range, the modern diffractometer Synergy-S and Stadivari can keep up to circa 0.9 Å^-1, while the older Supernova delivers noisier data. This is probably due to the virtually noise-free pixel detectors compared to the older CCD technology. However, all data, even from the Supernova, could be used to a resolution up to at least 1.17 Å^-1.

The derived unit-cell parameters of the four datasets at 100 K differ only a little – with a small feature that the differences between the values derived from the Synergy Mo and Ag as well as those from the Supernova and the Stadivari are smaller than the differences between these two groups.

For the refinements (Volkov et al., 2006), an I < 3σ intensity cutoff was used, leading to a very different amount of used data in the five datasets. Although the data to parameter ratio is larger than 10 in all refinements, I wonder if, especially for the Supernova dataset, overfitting could be excluded (Krause et al., 2017), which the authors had tested for the SPring-8 data but not for the new datasets. All five datasets deliver low R factors (≤ 3.4% for Supernova and < 1.7% for the other datasets) and min/max residuals (≤ ±0.25 e Å^-3 for Supernova and < ±0.15 for the other datasets), DRK plots with the value 1±5% across the whole resolution range (Zavodnik et al., 1999; Zhurov et al., 2008), and Henn–Meindl plots (Meindl & Henn, 2008) with virtually no features.

U_eq values for the heavy atoms agree well, while the values for hydrogen atoms derived from Hirshfeld atom refinement (Capelli et al., 2014; Fugel et al., 2018; Kleemiss et al., 2021) from the Supernova data deviate significantly from those of the other three datasets.

The derived multipole parameters show the same trend for all five datasets, although the differences for the carbon atom parameters are significant. The derived monopole population even spread between 4 and 4.5 e, indicating slightly negatively charged carbon atoms. However, the Bader charges are more sensible with slightly positively charged carbon with a small spread of 0.2 e and negatively charged nitrogen atoms. In addition, the topological values ρ_BCP and ∇²ρ_BCP are in good agreement except for the Supernova data, where the bond critical point of one weak π–π interaction could not be found.

Overall, it was found that even with conventional diffractometers and good quality crystals of small organic molecules reliable electron densities can be achieved with the multipole model. However, the better the data the more features can be seen: only for the excellent SPring-8 data set hydrogen κ values could be refined, while weak interactions could not be found with the weakest Supernova data.

References

Capelli, S. C., Bürgi, H.-B., Dittrich, B., Grabowsky, S. & Jayatilaka, D. (2014). IUCrJ, 1, 361–379.

Coppens, P., Iversen, B. & Larsen, F. K. (2005). Coord. Chem. Rev. 249, 179–195.

Fugel, M., Jayatilaka, D., Hupf, E., Overgaard, J., Hathwar, V. R., Macchi, P., Turner, M. J., Howard, J. A. K., Dolomanov, O. V., Puschmann, H., Iversen, B. B., Bürgi, H.-B. & Grabowsky, S. (2018). IUCrJ, 5, 32–44.

Graw, N., Ruth, P. N., Ernemann, T., Herbst-Irmer, R. & Stalke, D. (2023). J. Appl. Cryst. 56, 1315–1321.

Hansen, N. K. & Coppens, P. (1978). Acta Cryst. A34, 909–921.

Jørgensen, M. R. V., Hathwar, V. R., Bindzus, N., Wahlberg, N., Chen, Y.-S., Overgaard, J. & Iversen, B. B. (2014). IUCrJ, 1, 267–280.

Kleemiss, F., Dolomanov, O. V., Bodensteiner, M., Peyerimhoff, N., Midgley, L., Bourhis, L. J., Genoni, A., Malaspina, L. A., Jayatilaka, D., Spencer, J. L., White, F., Grundkötter-Stock, B., Steinhauer, S., Lentz, D., Puschmann, H. & Grabowsky, S. (2021). Chem. Sci. 12, 1675–1692.

Krause, L., Niepötter, B., Schürmann, C. J., Stalke, D. & Herbst-Irmer, R. (2017). IUCrJ, 4, 420–430.

Martin, A. & Pinkerton, A. A. (1998). Acta Cryst. B54, 471–477.

Meindl, K. & Henn, J. (2008). Acta Cryst. A64, 404–418.

Ruth, P. N., Graw, N., Ernemann, T., Herbst-Irmer, R. & Stalke, D. (2023). J. Appl. Cryst. 56, 1322–1329.

Volkov, A., Macchi, P., Farrugia, L. J., Gatti, C., Mallinson, P. R., Richter, T. & Koritsanszky, T. (2016). XD2016. https://www.chem.gla.ac.uk/~louis/xd-home/

Vosegaard, E. S., Ahlburg, J. V., Krause, L. & Iversen, B. B. (2023). Acta Cryst. B79, 380–391.

Vosegaard, E. S., Thomsen, M. K., Krause, L., Grønbech, T. B. E., Mamakhel, A., Takahashi, S., Nishibori, E. & Iversen, B. B. (2022). Chem. A Eur. J. 28, e202201295.

Wolf, H., Jørgensen, M. R. V., Chen, Y.-S., Herbst-Irmer, R. & Stalke, D. (2015). Acta Cryst. B71, 10–19.

Zavodnik, V., Stash, A., Tsirelson, V., de Vries, R. & Feil, D. (1999). Acta Cryst. B55, 45–54.

Zhurov, V. V., Zhurova, E. A. & Pinkerton, A. A. (2008). J. Appl. Cryst. 41, 340–349.

 

This article was originally published in Acta Cryst. (2023). B79, 344–345. 

Left: Helen Berman delivering her keynote lecture "What the Protein Data Bank tells us about the past, present and future of structural biology" at the 2008 IUCr Congress in Osaka (photo contributed to the IUCr gallery by the Osaka Local Organizing Committee). Right: Catherine Drennan in the Drennan Research and Education Laboratory at MIT (photo by Kalman Zabarsky).

In recognition of their distinguished and continuing achievements in original research, Helen Berman (Rutgers University, Piscataway, NJ, USA) and Catherine Drennan (MIT, Cambridge, MA, USA) were elected to the US National Academy of Sciences (NAS) in May 2023. The NAS is a private, nonprofit institution that was established under a congressional charter signed by President Abraham Lincoln in 1863. It recognizes achievement in science by election to membership, and — with the National Academy of Engineering and the National Academy of Medicine — provides science, engineering and health policy advice to the federal government and other organizations. Current NAS membership totals approximately 2,400 members and 500 international members, of which approximately 190 have received Nobel Prizes.

Helen M. Berman is Board of Governors Distinguished Professor Emerita of Chemistry and Chemical Biology at Rutgers University. She played a key role in founding the Protein Data Bank (PDB) in 1971 and was the Director of the Research Collaboratory for Structural Bioinformatics (RCSB) PDB, a member of the Worldwide PDB, from 1998 to 2014. In her capacity as Director of the PDB, Professor Berman served as an ex officio member of the IUCr Commission on Biological Macromolecules, and has contributed many articles to IUCr journals.

Catherine (Cathy) L. Drennan is professor of chemistry and biology at the Drennan Research and Education Laboratory at MIT. The Drennan lab combines X-ray crystallography and cryoEM with other techniques to understand enzyme mechanisms, an approach they term “structural metalloenzymology”. Earlier this year, Professor Drennan won the American Society for Biochemistry and Molecular Biology’s 2023 William C. Rose Award for her outstanding contributions to biochemical research and commitment to training younger scientists.

Figure 1. Schematic illustration of X-ray ptychography, where a coherent beam is scanned across the sample. Pixelated detectors record the far-field diffraction pattern, with beyond-optic, high-spatial-resolution information recorded at large scattering angles. This approach benefits tremendously from the historical increase in available coherent flux, which outpaces Moore’s law for integrated circuits. Taking full advantage of these sources requires the development of advanced detectors, such as reported in this issue by Takahashi et al. (2023).

X-ray nanoimaging is advancing quickly towards and beyond 10 nm resolution by scanning focused coherent beams and then collecting and iteratively phasing far-field diffraction data in a method called ptychography (Fig. 1). This yields phase and absorption contrast images and tomograms, sometimes with tensor information [such as magnetic field direction (Donnelly et al., 2017)], beyond the efficiency and resolution limits of X-ray optics.

These rapid advances have been enabled by a steady increase in available coherent X-ray flux, as depicted in the inset of Fig. 1. Recent and noteworthy advancements have been propelled by the use of multi-bend achromat lattices in electron storage rings. Beyond these synchrotron light sources, X-ray free-electron lasers provide even greater coherent flux, but with such intense and spaced-in-time pulses that one must worry about possible destruction of the sample by the first pulse. Both source types are creating another challenge: photons in detector pixels can arrive so quickly that photon-counting circuitry cannot keep up, as the photon-generated voltage ‘spikes’ become difficult to separate from each other in time.

One viable solution to address this detector challenge is to move from photon counting to charge integration, where one simply measures the total charge accumulated in each pixel during a detector ‘frame’ time. With the knowledge of monochromatic illumination, one can then infer the number of detected photons. This was first done in charge-coupled devices or CCDs, where a voltage sequence was used to move per-pixel charge out to a collecting amplifier and digitizer. Through the implementation of multi-row parallelization, this approach has reached frame rates of around a kilohertz. Another approach has involved the utilization of bump-bonding to attach a sensor to per-pixel charge integration circuitry, sometimes with mechanisms to adjust the analog gain during a detector frame with frame rates increasing to several and even tens of kilohertz. This latter approach of using hybrid pixel array detectors (HPADs) has seen widespread application (and commercial availability) first for photon counting but more recently for charge integration as well. Some variants of these detectors even store charge from each pixel for hundreds of frames at megahertz frame rates, with digitization and data transmission occurring in a burst afterwards.

In this issue of Journal of Synchrotron Radiation, researchers (Takahashi et al., 2023) in Japan report an advance both in per-pixel photon arrival rate and in overall detector frame rate by using a single monolithic CMOS chip which both collects the charge (the sensor in HPADs) and incorporates per-pixel charge integration and digitization circuitry (the application-specific integrated circuit in HPADs). This CMOS approach can potentially offer greater flexibility in the choice of pixel size, and can reduce detector fabrication complexity (and perhaps lead to even faster frame rates, and lower cost) by eliminating relatively high capacitance bump-bonding between two chips with different processing requirements. This detector has been demonstrated for nanocrystal imaging at ESRF, an upgraded fourth-generation synchrotron source, with improved performance compared with a photon-counting detector (Grimes et al., 2023). As reported in the paper by Takahashi et al. (2023), this detector is now being used for ptychographic imaging at 10 nm resolution over extended objects. A standout attribute showcased by this detector in this paper is its remarkable ability to record a peak intensity of approximately 250 million photons per pixel per second. This rate outperforms that of traditional photon-counting detectors, which typically encounter limitations around 1 million counts per pixel per second (with some correction possible to handle slightly higher rates).

The development of CMOS detectors with charge integration, and with fast-framing capabilities, will likely prove important as X-ray nanoimaging advances along with the development of X-ray sources with increasing coherent flux.

References

Donnelly, C., Guizar-Sicairos, M., Scagnoli, V., Gliga, S., Holler, M., Raabe, J. & Heyderman, L. J. (2017). Nature, 547, 328–331.

Grimes, M., Pauwels, K., Schülli, T. U., Martin, T., Fajardo, P., Douissard, P.-A., Kocsis, M., Nishino, H., Ozaki, K., Honjo, Y., Nishiyama Hiraki, T., Joti, Y., Hatsui, T., Levi, M., Rabkin, E., Leake, S. J. & Richard, M.-I. (2023). J. Appl. Cryst. 56, 1032–1037.

Takahashi, Y., Abe, M., Uematsu, H., Takazawa, S., Sasaki, Y., Ishiguro, N., Ozaki, K., Honjo, Y., Nishino, H., Kobayashi, K., Hiraki, T. N., Joti, Y. & Hatsui, T. (2023). J. Synchrotron Rad. 30, 989–994.

 

This article was originally published in J. Synchrotron Rad. (2023). 30, 859-860. 

Doing protein crystallography is easier than it has ever been thanks to advances in mechanics automation and software methods, but there is one step that remains tricky: obtaining crystals. Teaching the complete protein crystallography workflow requires having or growing crystals. And while some proteins do crystallize quite predictably within the time frame of almost any course, they are at this point almost devoid of the exhilaration that comes with stepping into the unknown. In this issue of Acta Cryst. F, Structural Biology Communications, a group led by Professor Krystle J. McLaughlin (Assistant Professor of Chemistry at Vassar College, New York, USA) shows how deposited but uninterpreted protein models from structural genomics consortia can be harnessed in undergraduate teaching to give students real-world research experience. The three leading authors on the article (Moorefield et al., 2023) were undergraduate students at her course, and produced all the biochemical data and structure interpretation work presented there.

Professor McLaughlin is passionate about making the protein crystallography experience accessible to undergraduate students with a special focus on minorities currently underrepresented in research, all through the CURE (Course-based Undergraduate Research Experience) programme (McLaughlin, 2021). In the context of a biochemistry course underpinned by BASIL teaching modules (https://www. basilbiochem.org), McLaughlin got in touch with the Seattle Structural Genomics Center for Infectious Disease (SSGCID, funded by NIAID, NIH) in the USA to identify suitable targets for study. A good match right from the outset, the SSGCID specializes in microbial proteins, and wants to partner up with structural biologists to provide useful context to their structures. With their depositions currently sitting at 1656 structures (Fig. 1), they are sure to continue providing targets for generations of students to come. The SSGCID provided pure protein for the students to analyse; moreover, they would have supplied plasmids too, should they have been required for the study.

Several undergraduate student groups took part in the course, but the one integrated by Moorefield, Konuk and Norman (lead authors on the article) managed to get the best data on the activity of their target enzyme, a family I inorganic pyrophosphatase from Legionella pneumophila. The ultimate deliverable of the research course was to produce a draft article in the style of Structural Biology Communications, which they did – McLaughlin fact-checked the draft and made some minor corrections prior to submission.

There are a number of important side-effects from this study. The importance of providing a controlled but meaningful research experience to undergraduate students comes across as critical to help avoid the disappointment some graduate researchers experience after starting a PhD; crucially, it might give students sitting on the fence a welcome push towards STEM research – this could be helpful in motivating students from disfavoured backgrounds who may feel discouraged by the current scarcity of visible role models. Underrepresentation of minorities is a problem that is most evident after the formative stage of career progression; bringing the first article event of scientific life forward by a few years – as opposed to doing it at the middle or end of a PhD – can only help increase diversity at the other end of the undergraduate-to-graduate gap. When asked about the aspirations of the three lead authors, McLaughlin (Fig. 2) sounded positively optimistic.

The model presented here provides an excellent blueprint for establishing more collaborations between academia and any of the 52 structural genomics centres that have deposited structures in the Protein Data Bank, 15 of which are named in Fig. 1. However, this is just one way young researchers can contribute: another one could be submitting topical reviews by graduate/masters students who routinely survey the literature in support of their research project; or short software methods papers from those scripting workflows at their labs.

I should like to emphasize that Structural Biology Communications is open for business when it comes to processing submissions including undergraduate/masters students, and will handle and showcase their research the best it can. Finally, I would like to thank outgoing Section Editor Janet Newman (University of New South Wales, Australia), who championed the idea of encouraging younger authors to contribute their articles to this journal, and edited McLaughlin’s manuscript.

References

McLaughlin, K. J. (2021). Struct. Dyn. 8, 020406.

Moorefield, J., Konuk, Y., Norman, J. O., Abendroth, J., Edwards, T. E., Lorimer, D. D., Mayclin, S. J., Staker, B. L., Craig, J. K., Barett, K. F., Barrett, L. K., Van Voorhis, W. C., Myler, P. J. & McLaughlin, K. J. (2023). Acta Cryst. F79, 257–266.

 

This article was originally published in Acta Cryst. (2023). F79, 274–275. 

The Royal Swedish Academy of Sciences has decided to award the Gregori Aminoff Prize in crystallography 2024 to Hao Wu (Boston Children’s Hospital, Harvard Medical School, MA, USA) for her discoveries by crystallography of the assembly mechanisms of large oligomeric signaling complexes in innate immunity, a paradigm-shifting concept in signal transduction.

The innate immune system provides the body with its first line of response to dangerous bacteria, viruses and hazardous substances, and consists of proteins on the cells’ surface and inside them. Once the system is activated, large protein complexes are built for the purpose of neutralising the attacking organisms. Professor Wu has used protein crystallography and cryoEM to establish how these protein complexes form, as well as their structures. Her research has led to an entirely new and improved understanding of how the innate immune system functions.

“Professor Wu is a master at identifying important biological issues and solving them using advanced structural and biochemical methods. Her discoveries may be of huge importance in understanding the causes of inflammatory diseases, their progression and treatment,” says Björn Dahlbäck, professor emeritus at Lund University and a member of the Prize Committee at the Royal Swedish Academy of Sciences.

The Gregori Aminoff Prize in crystallography recognises a documented individual contribution to the field of crystallography, and has been awarded to Swedish and foreign researchers since 1979. See previous laureates here.