Vanalyzer: An Automated Tool for Analyzing Vanadate-Binding Sites in the PDB

Vanalyzer is an open-source Python-based tool designed to perform statistical analysis of vanadate-binding sites across proteins in the Protein Data Bank (PDB). With the growing collection of protein structures in the PDB, Vanalyzer helps researchers extract biological insights by evaluating the structural properties of vanadate-binding interfaces and geometries. It offers an easy-to-use solution for comparing binding sites across various proteins and enzyme classes.

Features

• Automated Statistical Analysis: Automatically analyzes vanadate-binding sites from a selection of PDB structures.

• Geometry assignment: Automatically assigns the most suitable geometry (tetrahedral or trigonal bipyramidal) to each vanadate-binding site by calculating angles between coordinating atoms. The geometry is determined by comparing the calculated angles to theoretical values and selecting the best-fitting atoms.

• Detailed Structural Analysis: Evaluates angles, distances for best-fitting atoms and distributions of amino acids at vanadate-binding interfaces based on assigned geometry.

• Class-Specific Analysis: Focused analysis across different enzyme classes for targeted insights.

• Open-Source: Fully open-source Python tool for easy integration and further development.

• Multi-Platform Support: Includes both Python script and precompiled executables for Linux and Windows.

Repository Structure

This repository contains the following files and directories:

• Vanalyzer.py: Source code of the Vanalyzer tool (Python script).

• Vanalyzer: A precompiled Linux executable of the Vanalyzer tool.

• Vanalyzer.exe: A precompiled Windows executable of the Vanalyzer tool.

• requirements.txt: Requirements file detailing a list of Python packages to be installed by pip, when using pip install.

• Vanadate Dataset: A folder containing a dataset of 58 unique PDB structures for analysis.

• Output: A folder with the expected output files (CSV and PNG), for each enzyme class and their combinations.

• Vanalyzer Demonstration.mp4: A video demonstration showing how to use the tool, including selecting the dataset path, choosing enzyme classes to analyze and generating output CSV and PNG files.

Installation

Installing the Python Version

1. Clone the repository:

   git clone https://github.com/your-username/Vanalyzer.git

   cd Vanalyzer

2. Install the required Python packages:

   pip install -r requirements.txt

Using the Executable Versions

Alternatively, if you don’t want to install Python and the dependencies manually, you can use the precompiled executables provided in this repository:

• Linux: Download the Vanalyzer executable and run it from your terminal.

• Windows: Download the Vanalyzer.exe file and run it on your Windows machine.

Usage

1. Prepare your dataset:

   Ensure you have a folder with the PDB files you wish to analyze.

2. Run the tool:

   • Execute the following command:

     python Vanalyzer.py

   • Click the “Browse for data directory” button to choose the folder containing your dataset.

   • Choose at least one of the eight enzyme classes (EC) using checkboxes. For convenience, there are three buttons:

     • Select All: Selects all eight classes (seven EC + "Other").

     • Select None: Clears the current selection.

     • Select All except ‘Other’: Selects only the seven traditional enzyme classes, excluding "Other".

   • Click the “Analyze” button to initiate the automatic statistical analysis for the selected dataset.

3. Output:

   The tool outputs angles, distances, and amino acid distribution graphs that are saved into the working directory as PNG files. In addition, CSV files that contain detailed results (raw data) of statistical analysis (angles, distances, and amino acid distributions) performed for selected vanadate-binding structures.

Example

For a demonstration, watch the Vanalyzer Demonstration.mp4 video included in the repository. It shows how to:

• Select the dataset path.

• Choose specific enzyme classes for analysis.

• Perform statistical analysis on selected data.

• Overview of generated CSV and PNG output files.

Contributing

We welcome contributions to Vanalyzer! If you would like to contribute, please fork the repository, create a new branch, and submit a pull request with your changes. Be sure to follow best practices and include tests for new functionality.

License

Vanalyzer is released under the MIT License. See the LICENSE file for more details.