Interactive mockup of Deep Origin Studio. Data shown is illustrative.
Public benchmarks, measured the way anyone else would measure them.
Runs N’ Poses scores docking as test systems move away from the training set. In the hardest 0–20% band, DO Dock holds 55% while the best co-folding model manages 17% and the rest fall below 10%. That band is where a new program actually starts.
The pose you act on is the pose the compound actually adopts — nearly 20 points clear of the next method. Separately, over 90% of predicted poses pass PoseBusters’ physical-validity checks.
Across 81 targets, the compounds ranked highest are overwhelmingly the real binders. That ratio is what turns into roughly a tenth of the wet-lab cycles to reach a true binder.
Absolute binding free energy accurate enough to rank what to make before you commit the bench. Poses feed straight from docking into ABFE with no manual curation in between.
Every method runs on the same shared data, the same managed compute, and the same project view — so a docking pose flows into free energy and a hit set flows into properties without ever leaving Studio.
Predict molecular binding interactions — screen ligands against a protein, generate high-quality poses, and calculate predicted interaction energies.
Dock ligands against an already-docked template, constrained by their maximum common substructure, with free-dock fallback when nothing matches.
Identify druggable binding sites — detect cryptic pockets, analyse cavity properties, and expand your target space.
Predict binding free energies with rigorous alchemical calculations, for accurate absolute compound ranking.
Generate compound libraries through smart R-group expansion and scaffold enumeration, for focused chemical space exploration.
Identify structures in patent PDFs — extract molecules as SMILES and identify Markush structures.
Coming soonFind compounds similar to a query molecule by 2D structural similarity — start from any ligand in your project, or draw your own.
Coming soonCalculate molecular properties — drug-likeness scores, ADME predictions, and physicochemical descriptors.
Coming soonScreen compounds by 3D shape similarity to find bioisosteres and discover scaffold hops.
Coming soonBuild activity prediction models that correlate structure to potency and prioritise synthesis candidates.
Coming soonMap essential binding features — define 3D interaction patterns and guide scaffold design.
6 apps live today, 5 more coming through beta — each one built to put better molecules on your synthesis list, runnable by anyone on your team.
It assumes someone comfortable in front of a screen that looks like a jet cockpit. For a team of five to fifty, that assumption is the whole barrier.
Point-and-click, built for people who are not specialists. The 99% of parameters that should not be touched are hidden by default.
Nothing to procure, size, or maintain. No queue you have to get to the front of.
Poses feed into ABFE with no manual curation in between. The chain that used to need reverse-planning is a few one-click steps.
Studio users and code-first users work side by side in a shared Project. Runs register themselves as they finish, so there is no reconciliation step and nothing gets lost in the gap between two people.
Run it yourself — no waiting on specialists.
Unblock the team without adding headcount. Your experimentalists run the analysis, and go/no-go stops depending on somebody else’s calendar.
Enablement · Speed · SpendBetter molecules — evidence your approach works.
Proof the method picks real binders rather than credible-looking dead ends, including on targets nobody has solved yet. Nothing obvious left unchecked.
Validation · FocusKnow you’re making the right one.
Ask the question the day you have it. Run docking through free energy yourself and get an answer in days, without waiting on an outside lab.
Autonomy · ConfidenceEnterprise deployments, custom integrations and add-on modules are on the full pricing page.
