structural biology – Lightsources.org

OpenBind’s first data and model release marks a milestone for AI enabled drug discovery

2026/05/062026/05/07

The UK‑led OpenBind initiative has reached a major milestone with the announcement of the release of its first publicly available dataset and predictive AI model, a groundbreaking step toward accelerating the discovery of new medicines using artificial intelligence. The release showcases how engineering the production of AI-ready data is not only feasible but essential to evolving AI tools for scientific fields, which all suffer from a lack of data. With this OpenBind release, both high‑quality, standardised experimental data, and a newly trained predictive model, OpenBind v1, will become freely accessible to researchers worldwide, for immediate use in therapeutic discovery and to drive the next generation of AI models.

While AI has introduced a step‑change in predictive accuracy for protein structures, its impact on drug discovery has remained muted, limited above all by the global shortage of reliable experimental data measuring in atomic detail how molecules of drug discovery bind to disease‑related proteins. OpenBind aims to fill this critical gap. Led by Diamond Light Source, the collaboration of structural biologists and AI specialists – supported in its foundation phase by the Department for Science, Innovation and Technology (DSIT) – is the first initiative to generate these essential datasets at industrial scale, openly and continuously, and designed specifically for AI.

This first release demonstrates that OpenBind’s pipeline is now operational, having generated 800 high-quality measurements in only seven months – in the past, such large datasets took years to be produced and released. This integrated operation combines automated chemistry, robust binding measurements and high throughput crystallography at Diamond’s XChem Fragment Screening facility with an engineered data release process and AI model training using UK’s Isambard-AI compute cluster. It lays the groundwork for transformative progress in drug discovery, with future data tranches planned to address global‑health challenges such as COVID‑19, malaria, dengue, Zika, and cancer, where rapid development of new treatments remains vital.

Read more on the Diamond website

Image credit: Stuart March – DNDi

From Sequence to Structure: A Fast Track for RNA Modeling

2025/05/152025/05/15

In Biology 101, we learn that RNA is a single, ribbon-like strand of base pairs that is copied from our DNA then read like a recipe to build a protein. But there’s more to the story. Some RNA strands fold into complex shapes that allow them to drive cellular processes like gene regulation and protein synthesis, or catalyze biochemical reactions. We know that these active molecules, called non-coding RNAs, are present in all life forms, yet we’re just starting to understand their many roles – and how they can be harnessed for applications in environmental science, agriculture, and medicine.

To study – and potentially modify – the functions of non-coding RNAs, we need to determine their structure. Scientists from Lawrence Berkeley National Laboratory (Berkeley Lab) and the Hebrew University of Jerusalem have developed a streamlined process that predicts the structure of an RNA molecule down to the atomic level. Members of the research community can come to Berkeley Lab’s Advanced Light Source (ALS) user facility knowing nothing more than the molecule’s nucleotide sequence and get a structure, or they can do it themselves using the team’s open-source software.

“We were looking at the bigger picture with structure prediction, like how we can go from A to Z rather than working on A, B, and D. That’s what we try to do at Berkeley Lab, make it user friendly,” said Michal Hammel, a staff scientist in Berkeley Lab’s Molecular Biophysics and Integrated Bioimaging (MBIB) division. Hammel co-developed the process, called SOlution Conformation PrEdictor for RNA (SCOPER), with MBIB colleague Scott Classen and Hebrew University collaborators Dina Schneidman-Duhovny and Edan Patt.

A paper describing SCOPER was recently published in Biophysical Journal.

Historically, it has ranged between difficult to impossible to accurately determine the three-dimensional atomic blueprint of a folded RNA because they rarely convert into a neat crystalline form to be imaged with X-ray crystallography. And because the twists and folds of the RNA strand move around as the molecule functions, there are actually multiple correct structures.

In recent years, artificial intelligence (AI) tools like AlphaFold have become very accurate at generating protein structure predictions based on amino acid sequence, making life a lot easier for scientists worldwide and greatly accelerating the pace of drug discovery. These algorithms have been expanded to RNA structures, but the accuracy remains middling. Getting a reliable model currently involves combining the outputs of multiple computational tools and imaging data. It’s a long process, and still fraught with uncertainty.

SCOPER has simplified it significantly. Say you want to study a new RNA: First, put the nucleotide sequence into one of the open-source, AI-based structure prediction tools available today. Then, take your sample to a small angle X-ray scattering (SAXS) facility for characterization. Better yet, let Hammel and his colleagues at the ALS’s SAXS beamline get that data for you.

Take the SAXS data and predicted structures, and put them through SCOPER’s pipeline. The first step uses an existing program to generate possible flexible arrangements of the RNA from the predicted static structures. Next, a new machine learning program, developed and trained on existing atomic structures by Patt, refines the structures by adding the placements of magnesium ions. Inside cells, positively charged magnesium ions interact with negatively charged RNAs to keep them folded stably. Their presence also helps elucidate structure when using SAXS.

Next, SCOPER generates simulated SAXS data representing the theoretical structures and compares them with the real-world SAXS data to determine which structure is correct.

Read more on ALS website

Image: These renderings show RNA structures that were used to evaluate the accuracy of the new SCOPER process. The AI-generated initial structure predictions based on sequence (blue) is pictured with the refined predicted structure generated by SCOPER (red), which includes the placement of magnesium ions (violet).

Credit: Michal Hammel/Berkeley Lab

Researchers study molecular bindings to develop better cancer treatments

2023/04/192023/04/20

A research team based in Winnipeg is using the Canadian Light Source (CLS) at the University of Saskatchewan to find new, cutting-edge ways to battle cancer.

Dr. Jörg Stetefeld, a professor of biochemistry and Tier-1 Canada Research Chair in Structural Biology and Biophysics at the University of Manitoba, is leading groundbreaking research into how netrin-1 — a commonly found molecule related to cell migration and differentiation — creates filaments and binds to receptors in cells.

As netrin-1 is considered the key player for the migration of cancer cells, Stetefeld said this research could inform new cancer treatments.

“If you understand how netrin binds these receptors, you are sitting in the driver’s seat to develop approaches to block this interaction,” he said. “Why do we want to block it? Because if you block this interaction, you kill the cancer cell.”

Earlier research published in 2016 led to the development of new antibody treatments in Europe for combating breast cancer, said Stetefeld. He hopes this new research, which was published in the journal Nature, can lead to better drugs and treatments as well.

Read more on the CLS website

#SynchroLightAt75 – From the Ribosome to CRISPR

2022/10/112022/10/12

Structural Biology at the ALS: From the Ribosome to CRISPR

Since the first protein crystallography beamline came online here in 1997, thousands of protein structures have been solved at the Advanced Light Source (ALS). One of the earliest high-profile structures was that of the full ribosome complex, where all the proteins necessary for life are produced based on RNA blueprints. The results reinforced the impression that the ribosome is a dynamic molecular machine with moving parts and a very complicated mechanism of action. More recently, the ALS has contributed to a greater understanding of programmable CRISPR proteins such as Cas9. In contrast to earlier genome-editing tools, Cas9 transforms the complicated and expensive process of gene editing into something simpler and more routine, like applying a genetic plug-in. In 2020, Jennifer Doudna and Emmanuelle Charpentier were awarded the Nobel Prize in Chemistry for “the development of a method for genome editing.”

Antibody rigidity regulates immune activity

2022/07/132022/07/15

Scientists at the University of Southampton have gained unprecedented new insight into the key properties of an antibody needed to stimulate immune activity to fight off cancer, using the ESRF’s structural biology beamlines, among others.

The interdisciplinary study, published in Science Immunology, revealed how changing the flexibility of the antibody could stimulate a stronger immune response. The findings have enabled the team to design antibodies to activate important receptors on immune cells to “fire them up” and deliver more powerful anti-cancer effects. The researchers believe their findings could pave the way to improve antibody drugs that target cancer, as well as automimmune diseases.

In the study, the team investigated antibody drugs targeting the receptor CD40 for cancer treatment. Clinical development has been hampered by a lack of understanding of how to stimulate the receptors to the right level. The problem being that if antibodies are too active they can become toxic. Previous research by the same team had shown that a specific type of antibody called IgG2 is uniquely suited as a template for pharmaceutical intervention, since it is more active than other antibody types. However, the reason why it is more active had not been determined. What was known, however, is that the structure between the antibody arms, the so called hinges, changes over time.

This latest research harnesses this property of the hinge and explains how it works: the researchers call this process “disulfide-switching”. In their study, the team analysed the effect of modifying the hinge and used a combination of biological activity assays, structural biology, and computational chemistry to study how disulfide switching alters antibody structure and activity.

Read more on the ESRF website

Image: Flexibility of the monoclonal antibody F(ab) arms is conferred by the hinge region disulphide structure

Credit: C. Orr

#SynchroLightAt75 – Photon Factory at the dawn of structural biology using SR

2022/05/272022/05/27

The Photon Factory opened its first dedicated protein crystallography beamline with a Weissenberg camera in the mid-1980s. Prof. Ada Yonath, who was awarded the Nobel Prize in Chemistry in 2009 for her work on the structure-function analysis of ribosomes, was working at the Photon Factory at this time. The cryo-crystallography developed at the time led to the successful structural analysis.

Read more about the 2009 Nobel Prize in Chemistry and KEK’s Photon Factory here: KEK feature article

Image: Cryo-cooling system developed by Prof. Ada Yonath installed at the Photon Factory

Credit: Photo courtesy of Prof. Noriyoshi Sakabe

Cecilia Rocchi’s #My1stLight

2022/05/232022/05/23

#My1stLight memory at the SOLEIL synchrotron in Paris (PROXIMA-1 beamline) during my first year of PhD! So fascinated by the robotic arm, the collector of loops in liquid nitrogen and to see the place where our crystals diffract (although not always ^^’’) and the coveted three-dimensional structures born. I will never forget it! 😊

You never forget the first time, it was a real adventure. I ‘shot’ the crystals we had transported from Lyon with X-rays, and I also remember very well the first time I saw a high-resolution diffraction: even though it was not ‘my’ sample I was so happy! Since then, my adventure with structural biology has become a real love affair ♥

Image: Cecilia Rocchi on the PROXIMA -1 beamline at SOLEIL

Great minds think alike!

2021/12/202021/12/20

Marion Flatken from BESSY II & Luisa Napolitano from Elettra give advice to those at the start of their careers

Our #LightSourceSelfies campaign features staff and users from 25 light sources across the world. We invited them all to answer a specific set of questions so we could share their insights and advice via this video campaign. Today’s montage features Marion Flatken from BESSY II, in Germany, and Luisa Napolitano from Elettra, in Italy. Both scientists offered the same advice to those starting out on their scientific journeys: “Be curious and stay curious”. Light source experiments can be very challenging and the tough days can lead to demotivation and self-doubts. In these times, it is good to seek out support from colleagues, all of whom will have experienced days like this. Even if you think you can’t succeed with your research goals, try because it is amazing what can be achieved through hard work, tenacity and collaboration.

Be curious and stay curious!

2021/12/152021/12/15

Luisa Napolitano is a staff scientist working in the structural biology lab at the Elettra Sincrotrone in Trieste, Italy.

In her #LightSourceSelfie, Luisa talks about switching from cellular biology to structural biology and how proud moments come when you solve a structure that you have been working on for years.

Her fantastic lab tour explains how the equipment enables you to prepare proteins for a range of experimental techniques, including crystallography, electron microscopy, SAXS and NMR. Luisa also explains why it is so valuable to have a structural biology lab located at the synchrotron where beamline staff are on hand to give you advice about your research.

Finally Luisa touches on the way her work as a scientist is helping to inspire her 9 year old son. She offers this advice to younger peers, “Be curious and stay curious! Don’t be afraid and try, even if you think something is too much for you. Try it because you never know. It was like me when I started in structural biology at the beginning, I was scared but at the end of the story I like structural biology a lot, and I don’t think I will change my field of action anymore.”