Radial Doubles Down on Dynamic Structural Biology with ‘Prism'

Last summer, Astera's life science division, Radial,launcheda project aiming to reimagine how biologists study protein motion experimentally. Proteins are in constant motion, and this motion drives their function. But today, much of structural biology only captures static snapshots, representing the most common form a protein adopts. This is why we can predict a protein's fold but still cannot predict whether a mutation will break a protein or how a drug may affect its target. These answers exist in protein motion. We set out to push the limits of the structural biology data we collect and to carefully evaluate which data types might actually be most useful for understanding motion in the first place. The pilot project, calledDiffUse, focused on one data modality: X-ray crystallography. We proposed that a certain type of X-ray scattering called diffuse scattering, long considered background noise in measurements of three-dimensional protein shapes, might be a key signal for reconstructing how individual proteins move. Assessing the value of X-ray diffuse scattering wasn't just a data-collection problem. It was a simultaneous experimental and computational challenge: new data goes to waste without quality computational models to make sense of it, and machine learning models can't interpret motion from data formats not designed to prioritize it. DiffUse began by asking which parts of the structural biology pipeline must change before diffuse scattering can turn protein motion into usable structural information. However, X-ray diffuse scattering is only one potential data type that could inform us about how proteins move. Given theprogressthe project and team have made, we are expanding to more modalities: DiffUse is becomingPrism. Prism is tackling a more ambitious goal: making protein motion measurable, actionable, and predictable. This will establish a new foundation for structural biology, changing what AI can know about proteins and transforming how we discover drugs, engineer biology, and understand disease. A year ago, we committed $5M to seed DiffUse and have deployed $4.3M of that budget so far. Today we are re-committing $20M over the next three years to Prism. We started DiffUse because of a deep conviction that understanding and predicting protein motion is a key unsolved problem in biology, with clear real-world impact. Consider Gleevec, the first cancer drug designed to hit a specific molecule. Developed in the 1990s for chronic myeloid leukemia, it targets BCR-ABL, a rogue kinase and one of more than 500 structurally similar kinases in the human body. Yet Gleevec binds BCR-ABL thousands of times more selectively than its relatives. How did Gleevec get so selective? Clever experiments and good fortune: pharma chemists iterated with high-throughput screens, throwing every ligand at the wall to find the best candidate. But it turned out that the motion of BCR-ABL proteins was what actually allowed the selectivity to happen. Proteins aren't static. They wiggle and jiggle, alternating between multiple conformations. The most common form may seem the most important, but the transient shapes often hide the most druggable targets. Structural biology at the time couldn't see this; it was still mapping static structures. Now we can. Better experimental tools and machine learning are revealing the 'grammar' of protein dynamics — which regions flex, which sites shift, where new drug pathways emerge. But to do this systematically, or to deliver the right data for AI to learn these lessons, we can't tackle this one protein at a time, one technique at a time, or one part of the pipeline at a time. We have to re-establish the foundation of structural biology. This will allow us to design biology instead of stumbling into it. Prism's work to rebuild dynamic structural biology could help engineer more Gleevecs. The team envisions our work enabling the design of proteins based on dynamics data from the start, and unlocking new — and ultra-selective — drug targets. This has been a year of experimentation at DiffUse, with a few key open questions we set out to de-risk before expanding the project. 1) Does X-ray crystallography data contain useful, repeatable dynamics measurements? Yes. DiffUse had a clear hypothesis to test — that crystallography data contains reproducible hidden motion signals that we can collect at scale and now make sense of with modern AI. In the past year, DiffUse has supported that hypothesis with reproducible signals of protein dynamics; we have established a new kind of hybrid centralized-distributed team; and we have begun engaging the broader community to help shift the tide from a static picture of protein forms to a more holistic understanding of how dynamic forms create function. Earlier this year, the DiffUse teamshowedthat diffuse scattering is reproducible across different detector systems, beam profiles, and facilities. This ability to quantitatively measure the same ensembles consistently across different physical setups gives us confidence that any member of the structural biology community can eventually collect data. Another key learning from this year is that our existing data is an underused resource. While new data collected with methods optimized for diffuse scattering will be valuable, the data already sitting in the PDB can be mined for this information as well. Byreanalyzing50+ years of existing PDB structures, we uncovered latent information on conformational heterogeneity just sitting in the PDB. We believe that signals from other structural, functional, and sequence data will also be important for revealing the full spectrum of conformational ensembles and ultimately fully describing protein motion. Prism will now widen the scope to multiple types of structural biology data, beyond crystallography. We imagine future models that can predict the function and movements of any protein based only on its sequence, or design drug candidates with selectivity we would consider rare today. This will require collecting and analyzing many different types of data. What data, in what combination, and in what quantity, is an open question in itself, and a focus of Prism. 2) Does a hybrid centralized-distributed organizational structure work well to advance this type of science? Yes, but this is still an ongoing experiment. Over the past year, we have hired dedicated full-time scientists to the project to stay laser-focused on getting the effort off the ground. They started testing the hypothesis, building professional-grade software, and — just as importantly — managing a unique collaboration with academia. We have also assembled a group of world-class academic and national-lab team members who are generating protein ensemble measurements across multiple sites and inventing new ways to collect and use that data. This flexibility in structure allows us to experiment in new areas, demonstrate data reproducibility, and ultimately engage the scientific community, whom we will need as true partners to co-develop the large-scale version of dynamic structural biology. From day one, James Fraser (UCSF), Nozomi Ando (Cornell), Mike Wall (Los Alamos National Lab), James Holton (LBNL, UCSF), and Steve Meisburger (CHESS) have been key team members driving forward our work on X-ray diffuse scattering. Today, we are announcing the addition of cryo-EM as the second structural biology data modality at Prism, led by Joey Davis from MIT. This may seem obvious, but our key takeaway from this year is to recruit great people who are aligned on mission and strategy from day one. This has been particularly important given our commitment to sharing all our work as soon as it is ready, outside of journals. Luckily, the scientists most willing to experiment in how they share their work are also the ones most creative in their scientific approach. We are still looking for more scientists who want to redesign dynamic structural biology in the open and move fast on tools, methods, infrastructure, and, above all, biology that matters. In collaborative projects like this, team members need to feel ownership over their individual contributions and see how their work fits into the bigger picture. The mix of a new organizational structure, fantastic people, and aligned scientific goals is making it possible to tackle a scientific problem this large. As Prism grows, we will continue to evaluate what the best structure is to advance our mission, with the willingness to evolve. 3) Are there more effective open science approaches that increase the utility of our work? Yes, and we are continuing to try new approaches! The world around us and scientific research are changing far too fast for traditional scientific publishing to keep up. We believe scientists need to share their work in a way that allows others to learn from it, build on it, and use it on a timeline that keeps pace with modern science. That is the 'impact factor' of our times. One major uncertainty when seeding DiffUse was what might result from getting distributed academics to work together as one team, committed to sharing all our science openly, outside of journals. We have been pleased to see this ongoing experiment pay off. The distributed team is not only making progress on their scientific goals, but also setting a new standard for open science in structural biology. They have continually publishedblogs,open-sourced code, andposted data and analysesto our open publishing server,The Stacks, as soon as their work is ready for feedback and reuse. A key part of our success is having scientists willing to experiment with new ways to communicate and share their science. Doing something new brings about a lot of unknowns. Discussing these openly as a group has led us to think about more creative solutions. We aim to share more details on this publicly in the coming months. We have learned that one bottleneck to putting out a wide diversity of outputs at the speed we are generating them is knowing where and when to share work, and having editing support. People want to share their work differently, but often don't know how, when, or where to. To address this gap, we hired a Data Steward at Radial, and arehiringa science writer to support all our scientists, including those across Prism. 4) Can we better engage with the ecosystem to enable more testing and adoption? Yes, but this is a work in progress. From day one, our goal has always been community engagement. Rebuilding the foundations of dynamic structural biology will only be impactful if we build methods, tools, infrastructure, data, and models that the entire scientific community can contribute to and build upon. Community engagement starts with people. This summer, we brought together many leaders across dynamic structural biology at theConformational Ensembles Workshop. There, we presented our detailed plans for Prism and asked for community feedback and involvement. This feedback helped us reprioritize efforts, as explained further in ourvision for Prism. We have also focused on building and quickly releasing useful tools for the community. For example, we releasedSampleworks, an open-source, modular software for integrating experimental structural biology data, structure predictors (like AlphaFold), and guidance to improve the modeling of conformational ensembles. We have filled a major gap in the structure prediction space by releasingWaterFlow,a state-of-the-art method for placing water molecules around protein structures, allowing us to better understand how water molecules contribute to structure. We also recently sharedPLUG, an open-source, modular framework for constructing leakage-controlled protein function benchmarks, enabling more rigorous evaluation of protein function models. We developed all of these methods openly, allowing the community to build on them before the official release. Ultimately, ourpolicyof continually putting all our work out in public as quickly as possible is to enable rapid testing, reuse, and feedback. But we are always looking for ways to better engage with the ecosystem, and we welcome your ideas. 5) Can we find the right leader to expand and lead this? Yes! DiffUse began as a truly collaborative effort, with a small core group of founding scientists setting the early vision and strategy together. We always knew that a longer-term, expanded effort such as Prism would require true leadership. This could have been a very hard role to fill, and yet the obvious choice was right in front of us. Earlier this summer, Stephanie Wankowicz transitioned out of her role as a faculty academic collaborator at Vanderbilt and joined Radial full-time as Prism's first Scientific Program Director, setting the project's overall scientific vision and strategy. Stephanie is a relentless researcher, and her drive is infectious. Most structural biologists know that protein conformational dynamics are important. But Stephanie is a rare scientist who has done the experimental, computational, and leadership work to move the field toward dynamics. She not only has the ambitious vision of a world where we can observe, predict, and act on how proteins move, but she can also execute it. She began her research career studying clinical cancer genomics and computational biology at the Broad and Dana-Farber before moving into structural biology. Bothat the Broadand as a graduate student at UCSF, Stephanie committed herself to the open science movement, advocating for industry labs and publishers tolead by example. She understands the big picture in a way that an unconventional multidisciplinary effort like Prism needs. Prism is rebuilding the foundation of structural biology to transform how we discover drugs, engineer biology, and understand disease. We want to hear if this approach to doing science resonates with you. The full-time Prism team has expanded from two to ten full-time researchers. We are growing. And we also want our wider network of like-minded researchers — in academic labs or industry — to help this effort grow with us. If you're excited by our vision for the future of dynamic structural biology, whether as a biologist, computational scientist, or hardware developer, get in touch about ouropen roles. Or if you have an idea to collaborate on, reach out! We would love to hear from you and exchange ideas about the future of biology.