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From target pocket characterization to billions of compounds screened with geometric deep learning.
Compare leading AI molecular docking tools, equivariant diffusion models, and generative chemistry platforms. Benchmark DiffDock, EquiBind, GNINA, and Chemistry42 across docking accuracy, screening throughput, and chemical validity.
The previous fixed-template workflow scorer cannot establish comparative scientific suitability. For a task-specific assessment, enter the biological objective, the actual sample/data modalities and method constraints in the offline Decision Lab. Select the reviewed method deliberately and compare it against a mandatory non-AI baseline.
Open scientific Decision LabHistorical workflow templates are examples, not validated executable pipelines, clinical decisions or ranked model recommendations.
| Tool & Organization | License & Terms | GPU / Hardware | Architecture | Input Format | Evidence Level | Catalog |
|---|---|---|---|---|---|---|
| DiffDock MIT CSAIL / Corso et al. | MIT (Open Source) | 1x CUDA GPU (RTX 3090 / A100) | Open Source / Open Weights | PDB receptor + SMILES ligand | Peer-reviewed (ICLR 2023) | View Tool → |
| EquiBind Stärk et al. | MIT (Open Source) | CPU or fast GPU | Open Source | PDB receptor + SDF / Mol2 ligand | Peer-reviewed (ICML 2022) | View Tool → |
| GNINA University of Pittsburgh | GPL v2 (Open Source) | CPU or NVIDIA GPU (CUDA) | Open Source | PDB receptor + Ligand PDBQT | Peer-reviewed (J. Chem. Inf. Model.) | View Tool → |
| Chemistry42 Insilico Medicine | Commercial Enterprise SaaS | Cloud GPU Cluster (Managed) | Proprietary Software | Receptor PDB + Pharmacophore constraints | Clinically validated preclinical pipelines | View Tool → |
| Boltz-2 Biomolecular AI Consortium | MIT (Open Weights) | 1x A100 80GB | Open Source / Open Weights | Receptor PDB + Small-Molecule CIF/SMILES | Preprint (bioRxiv 2024) | View Tool → |
| Chai-1 Chai Discovery | Chai Terms | A100 GPU / Cloud API | Open Weights | Target sequence + SMILES | Preprint (bioRxiv 2024) | View Tool → |
Choose the operational architecture suited to your compute infrastructure, budget constraints, and licensing freedom.
Ideal for academic chemistry departments and research groups screening chemical collections (ZINC20, PubChem) on university clusters.
Rapidly identify putative binding pockets without prior co-crystallized ligand guidance.
Refine binding poses and calculate 3D CNN binding affinity scores (CNNscore and CNNaffinity).
Filter docked hits for Lipinski Rule of 5, Veber parameters, PAINS alerts, and predicted synthetic accessibility.
Select top 20–50 commercially available hit compounds for microscale thermophoresis (MST) or SPR validation.
Built for biotech companies driving hit-to-lead campaigns across the Enamine REAL space (10B+ make-on-demand molecules).
Generate novel chemotypes with desired novelty, metabolic stability, and binding selectivity.
Validate induced-fit pocket adaptation and non-covalent interactions using all-atom foundation models.
Screen hit analogs across Enamine REAL 10-billion space using GPU-accelerated diffusion docking pipelines.
Automate direct PO creation with custom synthesis CROs for 4-week turnaround in vitro profiling.
Examine detailed parameter counts, benchmark scores, input limits, and licensing restrictions in the BioAtlas interactive comparison table.
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