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Updates
New models, platform releases, and product enhancements.
Resources
Explore Resources for AI-Enabled Life Science Discovery
Research insights, product updates, practical use cases, webinars, and company news from Vecura.
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News
Company milestones, partnerships, events, and announcements.
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Insights
Research analysis, scientific perspectives, and deep dives.
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Use Cases
Practical examples of AI workflows across life science R&D.
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Webinars
Upcoming sessions and on-demand AI4Life Innovation Talks.
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AI4Life Bootcamp
Hands-on training program for teams putting AI to work in life science discovery.
Latest from Vecura
Use Cases
Molecular Dynamics, Trajectory and Ensemble Analysis on Vecura
Proteins move, and a single structure does not capture that. Vecura provides five related operations for working with protein dynamics: running physics-based simulations, analysing existing trajectories, generating trajectories with learned models, analysing conformational ensembles, and generating ensembles from sequence. Together they support biophysical characterisation, ensemble-based docking, binding kinetics and conformational landscape exploration. The five operations differ mainly in what you start from and how much physical accuracy you need. The selection table below is the fastest route to the right one.
Insights
Making Water Visible: How Generative AI Can Support Protein Structure Research
Water is fundamental to biological systems, yet the individual water molecules surrounding proteins are often difficult and expensive to model. SuperWater, a generative AI framework developed to predict water molecule positions around biomolecular complexes, offers a new approach to this longstanding computational challenge.
MSA Search is now available on Vecura
Updates
Accelerating Protein Structure Prediction: An Introduction to msa-search
Discover how msa-search, a GPU-accelerated service, slashes the compute time of Multiple Sequence Alignments (MSA) from hours to seconds, significantly accelerating AlphaFold2 and ColabFold structure prediction pipelines.