What it is
Schrödinger combines rigorous physics — free-energy perturbation (FEP+), molecular dynamics and quantum mechanics — with machine learning to predict binding affinity and prioritize molecules at scale. It is a bridge between the physics-first and data-first traditions and supplies software across the pharma industry.
Evidence trail
BioAtlas keeps the path from source to decision visible. A connection records provenance; it does not imply that evidence is sufficient for every context.
Model passport
How Schrödinger Platform represents biology
Category is navigation. These fields describe the model-specific computational transformation and deliberately override broad category defaults.
Biological scale
Modalities & tasks
Registry, claims and frontier intelligence
Version history not yet curated
1 version record · release year not yet normalized. Model-family identity remains separate from capability and access changes.
Explore version lineage →0 normalized claims
No task, dataset, split and metric claim has been normalized for this record yet.
Open claim intelligence →1 connected frontier
Structure + affinity · Recent preprint
Inspect research horizon →Connected research frontiers
These records describe active research directions, not guaranteed capabilities of this model. Evidence stages and unresolved questions are preserved separately.
Joint structure and binding-affinity reasoning
Isomorphic Labs · MIT · Open community · 2026-03-06Can one model predict both the bound geometry and the energetic ranking needed to prioritize compounds?
Evidence boundary and unresolved questions
Recent independent evaluations report that strong global correlations may not preserve ranking among top compounds, where lead-selection decisions occur.
- Can models rank close analogues within a chemical series?
- How well do they extrapolate across assays, protonation states and target families?
- Can uncertainty identify when physics or experiment should take over?
binding affinity · ranking · virtual screening · free energy · uncertaintyOpen frontier record →Inputs and outputs
Inputs
Molecular structures and simulation systemsOutputs
Affinity estimatesMolecular trajectoriesPrioritized compoundsScientific and technical profile
Scientific principles
Technology
Scientific lineage
These are transparent concept matches—not claims that one scientist alone caused this model. Each connection is based on the model’s recorded domain, scientific principles, technical terms or an explicit lineage link.
Multiscale modelling of chemical systems
Martin Karplus, Michael Levitt & Arieh WarshelQM/MM, molecular dynamics, free-energy methods and physics–ML hybrid platforms descend directly from this multiscale strategy.
Cooperative ligand binding
Archibald V. HillDose–response curves, receptor occupancy, multisite binding and systems pharmacology still use Hill-type models.
Intermolecular forces and excluded volume
Johannes D. van der WaalsModern force fields, docking scores, molecular dynamics and ligand–protein packing depend on these non-covalent interactions.
Gibbs free energy and chemical equilibrium
J. Willard GibbsBinding affinity, conformational stability, solvation, phase behavior and free-energy calculations all inherit this framework.
Statistical mechanics and the Boltzmann distribution
Ludwig BoltzmannConformational ensembles, molecular simulations, temperature scaling, sampling and energy-based generative models rely on this statistical view.
Atomic structures of biologically important molecules by X-ray crystallography
Dorothy Crowfoot HodgkinStructure-based drug design depends on the experimental structural tradition she helped establish.
Evaluation evidence
BioAtlas has not yet extracted a structured benchmark claim for this record.
Known limitations
- Independent reproducibility is limited by proprietary access.
- A structured benchmark claim has not yet been extracted for this record.
- Outputs require task-specific scientific and experimental validation.
Milestones
Publicly traded; software used industry-wide.
Runs its own co-founded biotech pipeline too.