https://github.com/AbhiLegend/DrugDisOpenVINO

https://github.com/AbhiLegend/DrugDisOpenVINO

Last synced: about 18 hours ago
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• Host: GitHub
• URL: https://github.com/AbhiLegend/DrugDisOpenVINO
• Owner: AbhiLegend
• Created: 2023-11-19T06:52:51.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2023-11-19T07:35:00.000Z (12 months ago)
• Last Synced: 2024-08-01T21:47:33.818Z (3 months ago)
• Language: Jupyter Notebook
• Size: 4.57 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-openvino - Drug Discovery “Lipophilicity” using OpenVINO toolkit - Finding Lipophilicity of peptides, proteins and molecules. (Table of content / Miscellaneous)

README

        
---

title: DrugDOpenV

emoji: 🐨

colorFrom: red

colorTo: yellow

sdk: streamlit

sdk_version: 1.28.2

app_file: app.py

pinned: false

license: mit

---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

To run the provided Python script using Streamlit, follow these steps:

### 1. Set Up Your Environment

Clone the repo

Create anaconda environment enable

run the command

pip install -r requirements.txt

```

Note: RDKit might require a specific installation process, especially on certain operating systems. Ensure you follow the official RDKit installation guidelines.

### 2. Prepare Your Script

`.

- Ensure that the model file (`lipophilicity_openvino.xml`) is accessible at the specified path in your script or update the `model_path` variable to the correct path where your model is stored.

### 3. Run the Streamlit App

- Open a terminal or command prompt.

- Navigate to the directory where your script is located.

- Run the script using Streamlit. For example, if your file is named `lipophilicity_app.py`, you would run:

```bash

streamlit run app.py

```

- Streamlit will start a local web server and provide you with a URL (usually `http://localhost:8501`).

### 4. Interact with the App

- Open the provided URL in a web browser.

- You'll see the Streamlit interface with the title "Lipophilicity Prediction App".

- Use the dropdown menu to select a SMILES string.

- Click the 'Predict Lipophilicity' button to see the prediction and the visual representation of the molecule.

### Additional Considerations

- Ensure that your environment supports all the necessary libraries and dependencies. For example, RDKit and OpenVINO have specific requirements for installation.

- If you plan to share this app or deploy it, consider using Streamlit sharing or another cloud service that supports Python and the required libraries.

- Be mindful of the computational resources required for running the model, especially if deploying this app for broader use.

Running a Streamlit app is generally straightforward and provides a powerful way to create interactive data appl