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ESMFold - Evolutionary-scale Prediction of Atomic-level Protein Structure with a Language Model

Overview

ESMFold is a Python-based application designed for predicting protein structures using the ESMFold model. This model is an end-to-end single sequence protein structure predictor built on the ESM-2 language model. The code in this repository is inspired by the works of the MetaAI ESM project.

Prerequisites

Before using the ESMFold Protein Structure Predictor, make sure you have the following dependencies installed:

pip install streamlit stmol py3Dmol requests biotite

Usage

  1. Clone the repository:
git clone https://github.com/your-username/ESMFold.git
cd ESMFold
  1. Install dependencies:
pip install -r requirements.txt
  1. Run the application:
streamlit run esmfold_app.py
  1. Open your browser and navigate to the provided URL.

Features

Protein Sequence Input: Enter the protein sequence of interest using the sidebar text area.

Prediction: Click the "Predict" button to initiate the prediction of the protein structure.

3D Visualization: The predicted protein structure is visualized in 3D using the Py3Dmol library. Rotate and zoom functionalities are available.

Confidence Score: The per-residue confidence score (pLDDT) is displayed, indicating the confidence in the prediction.

Download PDB File: Download the predicted protein structure in PDB format.

Additional Information

The ESMFold model is an end-to-end single sequence protein structure predictor based on the ESM-2 language model. The model and this app are inspired by the Meta AI ESMfold. For more information, refer to Meta AI's blog post.

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ESMFold - Evolutionary-scale prediction of atomic-level protein structure with a language model

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