DerivaPredict provides an accessible tool to explore potential derivatives with pharmacological activity. It streamlines the process by integrating advanced knowledge-driven and deep-learning algorithms for derivative structure prediction, compound protein affinity estimation, and ADMET property analysis, allowing users to efficiently assess the drug-like potential of novel compounds.
To get started with this project, you'll need to create a virtual environment and install the necessary software packages. Follow these simple steps, even if you're new to coding:
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Install Conda: If you don’t have Conda installed, you can download it from here. Conda is a tool that helps manage different versions of Python and the packages needed for different projects.
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Create a Virtual Environment: Open your terminal (or command prompt) and run the following command to create a virtual environment named
DerivaPredict:
conda create -n DerivaPredict python=3.10
This creates an isolated space where the project’s required tools and packages will be installed, without interfering with your system's Python setup.
- Activate the Environment: Once the environment is created, activate it using the following command:
conda activate DerivaPredict
- Clone the Project Repository: Download the project’s code from GitHub by running the following command:
git clone https://github.com/hcji/DerivaPredict.git
cd DerivaPredict
- Unzip Dependency: If you don't already have 7-Zip installed, download and install it from here.
To make it easier to run 7z commands from anywhere, you can add 7-Zip to your system's PATH:
- Open System Properties > Advanced > Environment Variables.
- Under System Variables, find Path, click Edit, and add the path where 7-Zip is installed (usually C:\Program Files\7-Zip).
Use the following command to unzip the file:
7z e biotransformer.7z
- Install Dependencies: The project relies on certain software libraries, which are listed in a file called requirements.txt. To install them, navigate into the project folder and run:
pip install -r requirements.txt
- Open the GUI:
python NPDS.py
- Refer the following video: