Features

Learn what Tamarind can do for you

Features

Learn what Tamarind can do for you

Features

Learn what Tamarind can do for you

Antibody

Enzyme

Peptide

Small Molecule

Design and optimize nanobodies, antibodies, and mini proteins

  • Predict the structures of immune proteins at massive scale and speed
  • Redesign and optimize CDRs for an antigen
  • Predict binding poses of antibody-antigen complexes
  • Optimize and predict sequences for thermostability, solubility, and other developability properties
  • Design de novo nanobody binders for an antigen

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Antibody

Enzyme

Peptide

Small Molecule

Design and optimize nanobodies, antibodies, and mini proteins

  • Predict the structures of immune proteins at massive scale and speed
  • Redesign and optimize CDRs for an antigen
  • Predict binding poses of antibody-antigen complexes
  • Optimize and predict sequences for thermostability, solubility, and other developability properties
  • Design de novo nanobody binders for an antigen

Learn More

Antibody

Enzyme

Peptide

Small Molecule

Design and optimize nanobodies, antibodies, and mini proteins

  • Predict the structures of immune proteins at massive scale and speed
  • Redesign and optimize CDRs for an antigen
  • Predict binding poses of antibody-antigen complexes
  • Optimize and predict sequences for thermostability, solubility, and other developability properties
  • Design de novo nanobody binders for an antigen

Learn More

Web Interface

Web Interface

Run dozens of the cutting edge computational tools with a simple web application at high throughput

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Batch Workflows

Batch Workflows

Starting from structures, sequences, or spreadsheet, compute properties, predict structures, and run all of our tools easily in high throughput

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Pipelines

Pipelines

Connect all of our tools to each other. Ex: generate sequences, filter them by score, then do molecular dynamics

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import requests 
api_key = "#"
base_url = "https://tamarind.bio/api/"

params = {
  "jobName": "myJobName",
  "type": "alphafold",
  "settings": {
    "sequence": "MALKSLVLLSLLVLVLLLVRVQPSLGKE",
	"numModels": 5,
	"numRecycles": 3
  }
}

response = requests.post(base_url + "submit-job", 
headers={'x-api-key': api_key}, json=params)
print(response.text)

API

API

Simple, massively scalable endpoints to leading protein design models and more

Documentation

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