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Vergleichen Sie biologische Modelle, Docking-Engines und Berechnungs-Workflows Seite an Seite. Filtern Sie nach Zugangsmodell, Rechenbedarf und Kategorie, um in unter einer Minute zu einer verwertbaren Entscheidungstabelle zu gelangen.
| Attribut | ＋ Werkzeug hinzufügen | |||||
|---|---|---|---|---|---|---|
| Category | AI Drug Discovery | AI Drug Discovery | AI Drug Discovery | AI Drug Discovery | AI Drug Discovery | — |
| Subcategory | Molecular Docking | Research AI Methods | Molecular Property Prediction | Molecular Design | Research AI Methods | — |
| Company | BenevolentAI / DeeplyTough authors | Research / method authors | Luo Lab | Sekijima Lab | Research / method authors | — |
| Access mode | Public code / project terms | Confirm distribution and exact release | Research code or publication | Research code or publication | Confirm distribution and exact release | — |
| Licence conditions | Review code, weights, data and service terms separately | NOT_INDEPENDENTLY_AUDITED | Check code and model weights separately | Check code and model weights separately | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | See source requirements for selected configuration | Version and data dependent | Check selected checkpoint and runtime; no GPU catalog recommendation | Check selected checkpoint and runtime; no GPU catalog recommendation | Version and data dependent | — |
| Biological application | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Research workflow | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Evidence level | Project/provider documentation; no local benchmark | PEER_REVIEWED_METHOD_OR_CONFERENCE | Peer-reviewed primary method | Peer-reviewed primary method | OFFICIAL_DOCUMENTATION | — |
| Commercial eligibility | Not independently confirmed | NOT_INDEPENDENTLY_AUDITED | Unknown, requires audit | Unknown, requires audit | NOT_INDEPENDENTLY_AUDITED | — |
| Price | See project terms; compute costs may apply | Verify access and licence | Check selected model licence | Check selected model licence | Verify access and licence | — |
| Availability ⓘ | See project release and maintenance status | Method paper or official documentation | Public research method/code | Public research method/code | Method paper or official documentation | — |
| Features | Learned comparison of protein binding-site structures, Input: Prepared protein binding-site structures, Output: Pocket representations and similarity comparisons | ADMET-AI scientific method, Molecular SMILES with well-defined compound stereochemistry and relevant assay domain, Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Chemical foundation model for learned molecular representations, property prediction and conditional molecule generation., Molecular features, predicted properties or generated SMILES | Diffusion-based ligand molecule generation constrained by specified pocket and pharmacophore interactions., Generated 3D chemical candidate structures | DiffSBDD scientific method, Protein binding pocket coordinates and desired molecular design context, Diffusion-generated candidate ligands | — |
| Entry type | Research software / framework | Source-scoped research method | Research AI model / method | Research AI model / method | Source-scoped research method | — |
| AI role | Scientific machine learning | ENSEMBLE_ML | Published biomedical AI method | Published biomedical AI method | DEEP_LEARNING | — |
| Input data | Prepared protein binding-site structures | Molecular SMILES with well-defined compound stereochemistry and relevant assay domain | Valid SMILES; trained downstream endpoint or conditioned molecule task | Protein pocket coordinates; interaction constraints | Protein binding pocket coordinates and desired molecular design context | — |
| Output data | Pocket representations and similarity comparisons | Predicted absorption, distribution, metabolism, excretion and toxicity endpoints | Molecular features; predicted properties or generated SMILES | Generated 3D chemical candidate structures | Diffusion-generated candidate ligands | — |
| Validation | Nicht erfasst | Published method scope; no independent BioAtlas execution or benchmark | Requires independent dataset-specific evaluation | Requires independent dataset-specific evaluation | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Intended use | Biological and pharmaceutical research | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Compatibility | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Limitations | A binding-site comparison tool, not a ligand pose generator; legacy dependencies may need maintenance. | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |