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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.
ℹ️ Diese Werkzeuge umfassen mehrere Kategorien (AI Drug Discovery, Drug Discovery & Chemistry, Single-cell, Spatial & Cytometry, Laboratory Automation & Intelligent Instruments). Leistungs-Benchmarks, Skalierung und Bewertungsmetriken unterscheiden sich je nach Domäne; bewerten Sie passend zu Ihrem Workflow.
| Attribut | ＋ Werkzeug hinzufügen | ||||
|---|---|---|---|---|---|
| Category | AI Drug Discovery | Drug Discovery & Chemistry | Single-cell, Spatial & Cytometry | Laboratory Automation & Intelligent Instruments | — |
| Subcategory | Molecular Docking | Molecular Docking | Single-cell Models | Laboratory Automation | — |
| Company | DiffDock authors and contributors | Scripps Research Institute | Bo Wang Lab | Opentrons | — |
| Access mode | Public code / project terms | Open Source | Public research code | Supplier quotation | — |
| Licence conditions | Review the linked release, model weights, datasets and service terms separately | Apache 2.0 | Code and checkpoint terms must both be checked | Confirm selected software, model, service and data terms | — |
| Compute requirements | Consult linked installation guidance; workload dependent | Multi-core CPU (GPU-accelerated version available via QuickVina/Vina-GPU) | Version and workload dependent; not independently benchmarked | Configuration and workload dependent; not locally benchmarked | — |
| Biological application | Nicht erfasst | Virtual screening of compound libraries and binding mode prediction | Nicht erfasst | Nicht erfasst | — |
| Research workflow | Nicht erfasst | Input receptor PDBQT and ligand PDBQT -> output binding poses and energy scores | Nicht erfasst | Nicht erfasst | — |
| Evidence level | Project or provider documentation; no local performance benchmark | Peer-reviewed research with >25,000 scientific citations | Project documentation; no local benchmark | Provider or project documentation | — |
| Commercial eligibility | Not independently confirmed | Permissive open source release | Confirm exact code, weights and data terms | Not independently confirmed | — |
| Price | See project terms; compute costs may apply | Free Open Source | See access and licence terms | Confirm current access and pricing | — |
| Availability ⓘ | See project access and maintenance status | Available on GitHub and Scripps website | Public research code | Confirm model availability with supplier | — |
| Features | Diffusion-based protein-ligand docking, Input: Protein structure or sequence and ligand SMILES or structure, Output: Candidate binding poses and confidence scores | High-speed multi-threaded molecular docking of flexible small-molecule ligands, Support for flexible receptor side chains and macrocyclic ligands, Python bindings (AutoDock-Vina Python package) for automated screening pipelines, Extensively integrated with open-source computational chemistry workflows | Foundation models for single-cell omics, Documented research workflow | Liquid-handling automation with AI-agent-compatible API, Documented biological or scientific workflow | — |
| Entry type | Research software / model | Open Source Software | Research software / model | Hardware / instrument | — |
| AI role | Scientific machine learning | Empirical & Algorithmic Docking | Machine-learning software | Infrastructure for AI workflows | — |
| Input data | Protein structure or sequence and ligand SMILES or structure | Nicht erfasst | Single-cell expression data | Validated protocols, labware and samples | — |
| Output data | Candidate binding poses and confidence scores | Nicht erfasst | Cell representations and task-specific predictions | Executed liquid-handling workflow | — |
| Validation | Evaluate on representative data; no clinical suitability established | Nicht erfasst | Evaluate on representative held-out data | Nicht erfasst | — |
| Type | Nicht erfasst | Molecular docking software | Nicht erfasst | Nicht erfasst | — |
| Intended use | Biological and pharmaceutical research | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Compatibility | Nicht erfasst | Nicht erfasst | Nicht erfasst | Nicht erfasst | — |
| Limitations | The repository defaults to DiffDock-L; a docking pose is not evidence of binding affinity. | Nicht erfasst | Nicht erfasst | API compatibility does not imply autonomous scientific reasoning; protocols require review and equipment validation. | — |
| Manufacturer | Nicht erfasst | The Scripps Research Institute | Nicht erfasst | Nicht erfasst | — |
| Integration evidence | Nicht erfasst | https://vina.scripps.edu | Nicht erfasst | Nicht erfasst | — |
| Laboratory handoff | Nicht erfasst | Identified hits ordered from commercial vendors (Enamine, ChemBridge) for in vitro validation | Nicht erfasst | Nicht erfasst | — |