Welcome to the first quarterly CryoCloud newsletter of 2026!
Over the past few months, we’ve released major platform updates, published new technical content, launched our new website, and connected with the structural biology community at several events.
Here’s what’s inside:
▸ Upcoming webinar series
▸ Science Spotlight: Automated analysis of the gastric proton pump ▸ CryoCloud algorithms & platform additions
Cryo-EM datasets are growing rapidly, but building the infrastructure and workflows needed for efficient data analysis can still require significant time, investment and expertise. CryoCloud simplifies this by providing a secure, scalable cloud platform that enables cryo-EM data processing in minutes.
Introduction to cryo-EM data processing and getting started with CryoCloud.
📅 April 21 — Industry. Register here. How automation and scalability support high-throughput cryo-EM workflows.
Both sessions include a live platform walkthrough and Q&A.
🔬 Science Spotlight
In January we featured the gastric proton pump–revaprazan complex as our Map of the Month. We have now published the full technical deep dive describing how the dataset was processed using CryoCloud’s fully automated end-to-end cryo-EM workflow.
Reprocessing the EMPIAR-11057 dataset produced:
⚡ 2.6 Å resolution in 43.5 hours of compute time ⚡ 2.4 Å after manual CTF refinement ⚡ Improved ligand density
This clinically relevant membrane protein complex provides a strong benchmark for testing the robustness of automated cryo-EM workflows under real-world conditions. Automation does not replace expertise — it removes repetitive manual steps that limit scalability, consistency and throughput.
Curious to know more about these case studies, or what CryoCloud could do with your own data?You can try the platform yourself, or we can run a benchmark on your dataset to show what’s possible.
📅 Book a call with us using the button below – we’d love to chat!
Our latest platform releases introduced several major improvements to the CryoCloud ecosystem:
⚡ CryoCloud MotionRefine Algorithm (Alpha)
Our GPU-accelerated motion refinement algorithm is now available in alpha release. Early benchmarks indicate 2–3× faster performance, reducing compute time and overall processing costs for particle polishing.
🧬 cryoDRGN-AI Ab Initio now available
In addition to cryoDRGN already supported on the platform, CryoCloud now offers cryoDRGN-AI Ab Initio, enabling neural network-based ab initio reconstruction for challenging cryo-EM and cryo-ET datasets without requiring a starting model.
Other algorithm and platform highlights from Q1 include:
Redesigned project overview interface.
Expanded embedded volume viewers across multiple job types.
Major workflows overhaul, including Advanced Cloning.
Want the full details? We now publish public release notes for every CryoCloud version, covering new features, improvements, and fixes.
We recently attended the Structure-Based Drug Design Summit in San Diego. The meeting brought together structural biologists, computational chemists and drug discovery teams to discuss the future of structure-based drug discovery — from cryo-EM and X-ray crystallography to AI-driven workflows.
Our Co-Founder & CEO,Robert Englmeier, presented how CryoCloud enables automated, high-throughput structure determination at scale.
Thank you to everyone who visited our booth and to the organisers for a fantastic event.
Want to try CryoCloud?
We offer two easy ways to get started:
Free Academic Plan 3 compute hours/month • 500 GB storage Ideal for students and small datasets
30-Day Evaluation Trial 20 compute hours • 2 TB storage • Onboarding & progress check-ins Perfect for labs and companies evaluating CryoCloud for purchase
