Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
Adaptyv is a cloud laboratory platform that provides automated protein testing and validation services. Submit protein sequences via API or web interface and receive experimental results in approximately 21 days.
Adaptyv requires API authentication. Set up your credentials:
export ADAPTYV_API_KEY="your_api_key_here"
Or create a .env file:
ADAPTYV_API_KEY=your_api_key_here
Install the required package using uv:
uv pip install requests python-dotenv
Submit protein sequences for testing:
import os
import requests
from dotenv import load_dotenv
load_dotenv()
api_key = os.getenv("ADAPTYV_API_KEY")
base_url = "https://kq5jp7qj7wdqklhsxmovkzn4l40obksv.lambda-url.eu-central-1.on.aws"
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json"
}
# Submit experiment
response = requests.post(
f"{base_url}/experiments",
headers=headers,
json={
"sequences": ">protein1\nMKVLWALLGLLGAA...",
"experiment_type": "binding",
"webhook_url": "https://your-webhook.com/callback"
}
)
experiment_id = response.json()["experiment_id"]
Adaptyv supports multiple assay types:
See reference/experiments.md for detailed information on each experiment type and workflows.
Before submitting sequences, optimize them for better expression and stability:
Common issues to address:
Recommended tools:
See reference/protein_optimization.md for detailed optimization workflows and tool usage.
For complete API documentation including all endpoints, request/response formats, and authentication details, see reference/api_reference.md.
For concrete code examples covering common use cases (experiment submission, status tracking, result retrieval, batch processing), see reference/examples.md.
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