API Documentation
Overview
API Key
MCP Server
SDK
CLI
View available tools and configurations
Submit Batch Jobs
/api/submit-batchThe POST API endpoint /submit-batch allows users to submit multiple jobs of the same tool associated together in a batch. You may choose your job type and specify the settings of each individual job within the batch to configure your batch.
Select tool:
Settings
Protein amino acid sequence, use : to separate chains for multimers
Options: ["1", "2", "3", "4", "5"]
Default: 5
Number of Models: Number of models to be used, each generating a different prediction
Default: 3
Number of recycles: Number of times to recycle outputs back through structure prediction process for refined results
Default: 0
Number of models to relax: Number of models to perform amber relaxation for more accurate side chain predictions
Default: True
Use Multiple Sequence Alignment: When MSAs are disabled, AlphaFold will run in single sequence mode.
Options: ["paired", "unpaired", "unpaired_paired"]
Pair Mode: "unpaired_paired" = pair sequences from same species + unpaired MSA, "unpaired" = separate MSA for each chain, "paired" - only use paired sequences.
useMSA must be true for this setting to be used
Options: ["pdb100", "custom", "none"]
Default: pdb100
Template Mode: Choose which template mode to use for your prediction
Custom Template File: One structural template for the prediction (.cif or .pdb). Wire a single structure, or upload one file.
templateMode must be custom for this setting to be used
Initial Guess Structure: Optional PDB/CIF whose atom positions seed the prediction instead of a random start. Useful for refining a known or designed structure.
Random seed: Random seed to be used in structure prediction
Options: ["508:2048", "512:1024", "256:512", "128:256", "64:128", "32:64", "16:32"]
Max MSA: Max # Clusters : Max # Extra Sequences - decrease max_msa to increase uncertainty
useMSA must be true for this setting to be used
Options: ["0.0", "0.5", "1.0"]
Recycle Early Stop Tolerance: Run recycles until distance between recycles is within a given tolerance (0 = never stop early)
Default: False
Score with IPSAE: Use IPSAE scoring function for interprotein interactions
Default: False
Options: ["auto", "alphafold2_ptm", "alphafold2_multimer_v1", "alphafold2_multimer_v2", "alphafold2_multimer_v3", "deepfold_v1", "alphafold2"]
Default: auto
Model Type: Model type to be used. If auto selected, will use alphafold2_ptm for monomer prediction and alphafold2_multimer_v3 for complex prediction (recommended canonical weights). Any of the mode_types can be used (regardless if input is monomer or complex)
HTTP Response Status Codes
| Status code | Description |
|---|---|
| 200 | Batch successfully submitted |
| 400 | Bad request |
| 403 | Forbidden - organization or team budget exceeded |
| 500 | Internal server error |
1import requests
2
3api_key = "insert-api-key-here"
4headers = {'x-api-key': api_key}
5base_url = "https://app.tamarind.bio/api/"
6
7params = {
8 "batchName": "myBatchName",
9 "type": "alphafold",
10 "settings": [
11 {
12 "sequence": "MALKSLVLLSLLVLVLLLVRVQPSLGKETAAAKFERQHMDSSTSAASSSNYCNQMMKSRNLTKDRCKPVNTFVHESLADVQAVCSQKNVACKNGQTNCYQSYSTMSITDCRETGSSKYPNCAYKTTQANKHIIVACEGNPYVPVHFDASV"
13 }, {
14 "sequence": "MALKSLVLLSLLVLVLLLVRVQPSLGKETAAAKFERQHMDSSTSAASSSNYCNQMMKSRNLTKDRCKPVNTFVHESLADVQAVCSQKNVACKNGQTNCYQSYSTMSITDCRETGSSKYPNCAYKTTQANKHIIVACEGNPYVPVHFDASV"
15 }, ...
16 ],
17 "jobNames": ["job1", "job2"...]
18}
19response = requests.post(base_url + "submit-batch", headers=headers, json=params)
20print(response.text)Response Format
Optional Parameters:
projectTag
= "proj_..."
Assign all jobs in the batch to a project by its ProjectId