API Capabilities

Find and compare the quality of pockets

Easily source chemical data from across the web and begin finding pockets with minimal lines of code. Continue your exploration with pocket data creation based on crystal structure, novelty of pockets, xyz coordinates, or residue IDs.

protein, pockets_report = pocket_finder_client.find_pockets( protein, num_pockets = 10, pocket_min_size = 30)

Results table

Pocket ID	Color	Drugability Score	Volume	Total SASA	Polar SASA	Polar/Apolar SASA Ratio	Hydrophobicity	Polarity
1	red	0.824	393.000	1215.506	438.612	0.712	30.241	13.000
2	green	0.824	1692.000	2733.433	1309.695	1.006	28.296	34.000
3	blue	0.229	607.000	1289.649	440.678	0.519	22.926	15.000
4	yellow	0.181	219.000	668.375	221.859	0.529	49.727	6.000
5	magenta	0.113	1339.000	3244.177	1523.835	1.046	17.780	31.000
6	cyan	0.088	226.000	975.604	373.147	0.619	28.941	7.000
7	orange	0.085	373.000	1439.165	553.751	0.625	47.778	10.000
8	celeste	0.047	293.000	927.509	321.407	0.586	11.333	14.000
9	purple	0.029	285.000	933.222	387.067	0.709	22.565	13.000
10	brown	0.016	504.000	1643.842	734.301	0.862	2.172	22.000

Visualize docking grid boxes with one line

Use precomputed or custom protein data. Seamlessly validate pocket boundaries and grid box dimensions for docking, with built-in support for mismatched or manually adjusted inputs.

pocket_data.show_box()

Generate docking scores, poses, and reporting

Run docking with a single function call using preprocessed or custom inputs. Generate poses, scores, and interactive visualizations in seconds—ready for analysis, filtering, or export.

report = docking_client.dock(
protein=protein, ligands=ligands, pocket_data=pocket_data,
protinoate_ligands=False,
)

Results table

	SMILES	Ranking Score	Binding Energy	Path To Docked Pose
0	CC(C)Cc1ccc([C@@H](C)C(=O)[O-])cc1	48.139	-7.063	/your-system/...
1	Cn1c(=O)c2c(ncn2C)n(C)c1=O	48.073	-5.230	/your-system/...
2	CC(=O)Oc1ccccc1C(=O)[O-]	47.530	-5.526	/your-system/...

Predict ADMET scores and port to tools of your choice

Predict absorption, distribution, metabolism, excretion, and toxicity properties effortlessly, ready for integration into your pipeline.

for result in report.results:
result.top_ligand.admet_properties()

Tools Included In API

Molecular Data Retrieval & Informatics

Database Integration:
- Protein Data Bank (PDB): Retrieve protein structural data.
- ChEMBL: Access bioactive molecules, drug targets, and assay data.
- UniProt: Search protein sequences and annotations.
- PubChem: Query small molecule information and bioassay data.
- BindingDB: Retrieve protein-ligand affinity data.
- Zinc Db: Large library of purchasable molecules.
- Mcule Express: Online library of chemical compounds for screening purposes.
- AlphaFold Db: Retrieves predicted protein structures from the AlphaFold database.
- Unified Db: Local database integrating ChEMBL and Binding database information.
Intellectual Property & Literature:
- Patent Check: Identify patented molecules via SMILES input.
- Scientific Literature Search: Automate retrieval of research publications.
- Analyze PDF Documents: Extract insights from publications, summarize findings, and retrieve key data.
- Convert Between Molecular Identifiers: Convert between SMILES, CAS, and IUPAC formats.
Additional Tools:
- Web search: General web search for drug discovery–related information.
- Draco 1.0: Converts PDF documents into SMILES representations.

Protein Structure Analysis & Ligand Preparation

Protein Processing:
- Binding Pocket Identification: Detect potential binding sites.
- Protein Structure Alignment: Align protein structures.
Ligand Tools:
- Protonation State Prediction: Estimate protonation states at a given pH.
- Functional Group Identification: Identify molecular substructures.
- Molecular Similarity Search: Find similar molecules to a given input.

Molecular Dynamics and Free Energy Calculations (FEP)

RBFE: Computes relative binding free energies with high accuracy.
ABFE: Calculates absolute binding free energies of ligands to proteins.
Simple MD: Fine‑grained molecular dynamics simulation for structure relaxation and analysis.

Structural & Visualization Tools

Rendering & Visualization:
- 2D Drawing from SMILES: Generate molecular diagrams.
- Protein Visualization: View proteins in 3D.
- Binding Pocket Visualization: Highlight docking pockets.
- Docking Result Viewer: Inspect ligand poses and interactions.
Structural Analysis:
- Calculate RMSD: Compare molecular conformations and structural changes.
- Mutagenesis Analysis: Identify mutations or structural gaps.

Molecular Property & ADMET Profiling

Descriptors:
- Synthetic Accessibility Score (SAS): Assess molecular complexity.
- Quantitative Estimate of Drug-likeness (QED): Evaluate drug-likeness.
Physicochemical Properties:
- LogP, LogD, LogS: Predict lipophilicity, distribution, and solubility.
- LogP prediction: Estimates the lipophilicity (partition coefficient) of molecules.
- LogS prediction: Predicts the solubility of chemical compounds.
- LogD prediction: Estimates distribution coefficients, accounting for ionization.
- pKa prediction: Predicts the acidity (pKa) values of compounds.
Toxicity Predictions:
- hERG Inhibition / hERG binding: Predict potential binding to the hERG channel, indicating cardiotoxicity risk.
- CYP450 Interaction / CYP binding: Predict binding to cytochrome P450 enzymes and metabolic stability.
- Ames Mutagenicity / Ames mutagenicity: Assess the mutagenic and carcinogenic potential of compounds.
Scoring Engines:
- Togo (pseudo name): Multi‑parameter optimization engine for compound scoring.

Molecular Docking

Docking Simulation & Analysis:
- Standard Docking: Run molecular docking simulations.
- Docking Analysis: Analyze binding energies and interactions.
- Docking Box Visualization: Visualize 3D docking box.
- Ligand/Protein Preparation: Prepare molecules for docking.

Data Processing & Analysis

CSV Dataset Handling:
- Extraction & Processing: Read, clean, and transform molecular datasets.
- Querying: Run SQL-like filters on CSV data.
Batch Pipelines:
- Batch Data Processing: Efficient handling of large molecule datasets.
- Batch Docking: Dock multiple molecules simultaneously.
Workflow Automation:
- File Management: List and retrieve files from working directory.
- Basic Retrosynthetic Engine: Predict simple synthetic routes.

Our Research

Explore our research and analyses of AI and the drug discovery industry below.

Coming soon

Your Whole Drug Discovery Workflow in a Single API

API Capabilities

Find and compare the quality of pockets

Results table

Visualize docking grid boxes with one line

Generate docking scores, poses, and reporting

Results table

Predict ADMET scores and port to tools of your choice

Tools Included In API

Molecular Data Retrieval & Informatics

Protein Structure Analysis & Ligand Preparation

Molecular Dynamics and Free Energy Calculations (FEP)

Structural & Visualization Tools

Molecular Property & ADMET Profiling

Molecular Docking

Data Processing & Analysis

Our Research

Coming soon

Your Whole Drug Discovery Workflow in a Single API

API Capabilities

Find and compare the quality of pockets

Results table

Visualize docking grid boxes with one line

Generate docking scores, poses, and reporting

Results table

Predict ADMET scores and port to tools of your choice

Tools Included In API

Molecular Data Retrieval & Informatics

Protein Structure Analysis & Ligand Preparation

Molecular Dynamics and Free Energy Calculations (FEP)

Structural & Visualization Tools

Molecular Property & ADMET Profiling

Molecular Docking

Data Processing & Analysis

Our Research

Scientific Poster

•

Drug Discovery

Discovering Novel Synthetic Lethal Pairs With Large Scale Cellular Simulations

Updated:

June 7, 2024

Scientific Poster

•

Drug Discovery

Addressing Drug Discovery Challenges with a Multiscale Molecular Modeling Pipeline

Updated:

June 7, 2024

Blog

•

Drug Discovery

We Spill the Beans: Deep Origin's AI- and Physics-Based Models for Drug Discovery

Updated:

May 8, 2024

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Discovering Novel Synthetic Lethal Pairs  With Large Scale Cellular Simulations