How Crystallographers are Preserving Science's Foundation
In the quest to unveil molecular secrets—from viral proteins to quantum materials—crystallographers generate petabytes of raw data. Yet, until recently, >90% of this data vanished after publication, lost to obsolete hard drives or inconsistent archiving. The 69th Annual Meeting of the American Crystallographic Association (ACA) marked a turning point, spotlighting data best practices as the cornerstone of reproducible, collaborative science 1 3 . This article explores how FAIR principles, raw data preservation, and AI integration are transforming structural biology.
Findable, Accessible, Interoperable, Reusable (FAIR) and Fair, Accurate, Confidential, Transparent (FACT) principles are reshaping data ethics:
The PDB and Cambridge Structural Database exemplify decades-long trust, linking publications to underlying data 1 .
Preserves objective observations before subjective processing, enabling future reanalysis 1 .
Demonstrated how archived data reveals errors in metal/ligand modeling, improving PDB-curated models 1 .
"FACT and FAIR with Big Data allows objectivity—the raw data is the ultimate witness" — John Helliwell 1
Preserving raw images isn't just bureaucratic—it's a scientific catalyst:
| Application | Impact | Example |
|---|---|---|
| Reprocessing | Higher-resolution structures from old data | Confirming symmetry, multi-lattice analysis 1 |
| Algorithm Development | Training ground for new software | Detecting diffuse scattering dynamics 1 |
| Error Correction | Identifying modeling inaccuracies | Ligand/electron density mismatches 1 |
Microcrystal Electron Diffraction (MicroED) benefits particularly—raw data archives help address dynamic scattering and bonding-sensitive electron factors 1 .
Storing data is easy; storing usable data is hard. Key breakthroughs include:
Detector geometry, crystal position, and goniometer settings must accompany raw images to permit reprocessing 1 .
A unified standard embraced by light sources, detector manufacturers, and software developers 1 .
Ensures structures can be rederived remotely or decades later 1 .
Leonarski et al.'s high-data-rate crystallography confronts the "big data" deluge 1 :
Process diffraction images at 46 GB/s (10 megapixels at 2.2 kHz) to enable real-time analysis.
Capture ultrafast diffraction patterns.
Pre-filter blank images, reducing load.
Handle integration/refinement mainstream architectures can't support.
| System | Data Rate | Output Latency | Energy Efficiency |
|---|---|---|---|
| Conventional HPC | 8 GB/s | 5 sec/image | 0.4 images/kWh |
| Swiss Light Source Setup | 46 GB/s | 0.1 sec/image | 12 images/kWh |
| Tool/Resource | Function | Example Use Case |
|---|---|---|
| wwPDB OneDep System | Unified deposition/validation | Pre-submission validation of cryo-EM maps 6 |
| Phenix Software Suite | AI-enhanced structure solution | Refining AlphaFold models with experimental data 6 |
| EMPIAR | Raw cryo-EM image archive | Algorithm training (e.g., DeepMainmast) |
| DAQ Score | Deep-learning model validation | Assessing cryo-EM map-model fit accuracy |
Public repositories (PDB, EMPIAR)
Metadata standards (CBF, Gold Standard)
Access controls for unpublished data
Open processing workflows
Five-year predictions from Förster and Schulze-Briese envision:
Combining crystallography, cryo-EM, and MicroED to resolve hydrogen placement, metal charges, and molecular flexibility 1 .
Tools like DeepMASC (automated cryo-EM masking) and NuFold RNA (tertiary structure prediction) accelerate model building .
In situ diffraction under electrochemical/gas flow conditions reveals dynamic material behavior 5 .
The ACA's Best Practices SIG champions a cultural shift: data isn't a byproduct but a communal asset. As Brent Nannenga notes, archiving raw images lets future scientists reprocess them with undiscovered tools—extending a 2025 experiment's value into 2125 1 5 . In crystallography's diamond jubilee era, preserving data isn't just best practice—it's stewardship of tomorrow's discoveries.