Trusted Science. Delivered the Way You Need.
The Orion®
The Orion®
Antibody Discovery Suite
Analyze Sequence and Engineer Antibodies In Silico
OpenEye's Orion® antibody discovery suite empowers scientists with 2D and 3D antibody modeling tools, speeding up their therapeutic discovery process.
The suite includes biomodeling tools, Specifica's state-of-the-art antibody sequence analysis tool called AbXtract™, and open-source tools like ImmuneBuilder for antibody structure prediction. Discover potent antibody leads while minimizing liabilities. Contact us to learn more.
CDR loop ensemble generation followed by molecular dynamics simulation using Orion cloud modeling platform
With the Orion Antibody Discovery Suite, you get innovative science to help you:
- Analyze millions of sequences. Uncover more leads from your NGS data. Increase the number of clonotype leads five- to ten-fold compared to random colony screening.
- High throughput structure generation from sequence. Predict 3D structure at scale with machine learning method. Available automated (or customizable) workflows to streamline your research.
- Cluster to get diverse leads. AI based clustering on sequence space or cluster based on CDR focussed 3D conformation.
- Refine your 3D model or structure. Rapidly generate ensemble structures to model CDR-loop regions and sample conformational space.
- Improve developability.
Identify antibodies with desired properties to reduce liabilities.
Orion's antibody discovery suite provides convenient turn-key solutions with:
- Easy-to-use workflows. Access ready-to-use Orion workflows (Floes) or integrate your own in-house or third-party tools.
- Web convenience. Conduct antibody modeling research directly from your web browser.
- Seamless collaboration. Efficiently manage files, share data, and collaborate in real-time with your colleagues.
OpenEye’s novel 3D structure-based clustering can take antibody structures from your data and cluster them based on the CDR surface patches without the limitations of sequence length requirements. This clustering method is useful, for example, in finding diverse antibodies that bind to the same epitope and potentially studying off-target effects.