AntibodyGPT: Runpod Serverless Antibody Protein Generation API

This repository contains the code for the docker image published to dockerhub.

AntibodyGPT: A Fine-Tuned GPT for De Novo Therapeutic Antibodies

• Web Demo
• Huggingface Model Repository

Antibodies are proteins that bind to a target protein (called an antigen) in order to mount an immune response. They are incredibly safe and effective therapeutics against infectious diseases, cancer, and autoimmune disorders.

Current antibody discovery methods require a lot of capital, expertise, and luck. Generative AI opens up the possibility of moving from a paradigm of antibody discovery to antibody generation. However, work is required to translate the advances of LLMs to the realm of drug discovery.

AntibodyGPT is a fine-tuned GPT language model that researchers can use to rapidly generate functional, diverse antibodies for any given target sequence

Getting Started

You can directly use the published image on docker hub in runpod by referencing:

robertsj32/antibody_generation_runpod:latest

This image is located here:

https://hub.docker.com/repository/docker/robertsj32/antibody_generation_runpod/general

Once the image is published as an endpoint on Runpod you can call the api using the below as reference:

url = f'https://api.runpod.ai/v2/{runpod_id}/run'
        headers = {
            'Content-Type': 'application/json',
            'Authorization': f'Bearer {runpod_secret}'
        }

        # The JSON data payload
        data = {
            'input': {
                "model_name": model_name,
                "target_sequence": target_sequence_input,
                "number_of_sequences": number_of_sequences
            },
            "policy":{
                "executionTimeout": 600000 # 10 minutes in miliseconds -> Stop run away costly GPU jobs.
            }
        }

        # Make the POST request
        response = requests.post(url, json=data, headers=headers)

Prerequisites

• Docker: The application is containerized with Docker, so you'll need Docker installed on your machine. You can download Docker here.

Installation

1. Clone the repository:

   git clone https://github.com/joethequant/docker_protein_generator.git

2. Navigate to the project directory:

   cd docker_protein_generator

3. Build and push to dockerhub: Edit contents to your location.

   build_and_push.sh

License

This project is licensed under the MIT License - see the LICENSE file for details.