API Documentation
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)
MSA File (a3m): Optional MSA in a3m format. When set, it replaces the generated alignment. For several protein chains, upload the a3m the MSA tool writes in complex mode (paired and unpaired blocks together), with the chains in the same order as in your complex. For one protein chain, upload that chain's own a3m. The MSA step is skipped unless PDB100 templates are on (the default), in which case it still runs to find the template hits.
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