PPIIMoL: Difference between revisions

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This tool was developed as part of a Bachelor's Thesis in Computer Engineering in collaboration with the CSIC neuroscience laboratory.
This tool was developed as part of a Bachelor's Thesis in Computer Engineering in collaboration with the CSIC neuroscience laboratory.
[[Category:Plugins]]


== Features ==
== Features ==
* 🔍 Automatic detection of PPII segments via phi/psi angle analysis.
🔍 Automatic detection of PPII segments via phi/psi angle analysis.
* 🧬 Identification of Cα-H···O=C interactions relevant to structural stability.
🧬 Identification of Cα-H···O=C interactions relevant to structural stability.
* 📊 Export of results in CSV format for further analysis.
📊 Export of results in CSV format for further analysis.
* 🎨 Direct visualization in PyMOL with customizable color codes.
🎨 Direct visualization in PyMOL with customizable color codes.
* 🖱️ Simple GUI based on Tkinter.
🖱️ Simple GUI based on Tkinter — no commands required; all actions are accessible via buttons.


== Requirements ==
== Requirements ==
* [[PyMOL]] 2.x or newer.
* [[PyMOL]] 2.x or newer.
* Python with [https://docs.python.org/3/library/tkinter.html Tkinter] support enabled (for the GUI).
* Python with [https://docs.python.org/3/library/tkinter.html Tkinter] support enabled (for the GUI).


== Installation ==
== Installation ==
# Download or clone the repository:
'''Quick method:'''
# Download `PPIIMoL.py` directly from the [https://github.com/silviaenma/PPIIMoL GitHub repository].
# In PyMOL, run:
<pre>
run /path/to/PPIIMoL.py
</pre>
 
'''Full repository (optional):'''
# Clone the repository to also get example files and documentation:
<pre>
<pre>
git clone https://github.com/silviaenma/PPIIMoL.git
git clone https://github.com/silviaenma/PPIIMoL.git
</pre>
</pre>
# Start PyMOL and load the module:
# In PyMOL, run:
<pre>
<pre>
run PPIIMoL/PPIIMoL.py
run PPIIMoL/PPIIMoL.py
</pre>
</pre>
# (Optional) Install permanently as a plugin:
* In PyMOL, go to: '''Plugin → Plugin Manager → Install New Plugin'''.
* Select the file `PPIIMoL.py` or the full `PPIIMoL` folder.
* Restart PyMOL to complete installation.
== Example Usage ==
<pre>
# Load the module in PyMOL
run PPIIMoL/PPIIMoL.py


# Load a structure
(Optional) Install permanently as a plugin: 
load 3bog.pdb
* In PyMOL: '''Plugin → Plugin Manager → Install New Plugin'''. 
* Select `PPIIMoL.py` or the full `PPIIMoL` folder. 
* Restart PyMOL.


# Detect PPII helices
== Usage ==
ppii_detect()
Once loaded, PPIIMoL opens a Tkinter-based graphical interface. 
</pre>
From this window, you can:
* Load a PDB file. 
* Detect PPII helices. 
* Export results as CSV. 
* Change visualization colors directly. 


Results will be automatically exported in a folder named with the current date, containing CSV files with detected segments and interactions.
Results are automatically exported to a folder named with the current date, containing CSV files with detected segments and interactions. Detected PPII helices are highlighted in PyMOL according to the selected color scheme.
Detected PPII helices will be highlighted in the PyMOL viewer according to the selected color scheme in the GUI.


== Repository ==
== Repository ==

Revision as of 04:14, 14 August 2025

PPIIMoL

PPIIMoL is a Python module for PyMOL that automates the detection of polyproline II (PPII) helices in proteins. It streamlines structural analysis by:

  • Identifying characteristic torsional angles (phi and psi) of PPII helices.
  • Detecting potential non-canonical hydrogen bonds (Cα-H···O=C) relevant to structural stability.
  • Exporting results for further analysis.
  • Providing direct, customizable visualization in PyMOL.

This tool was developed as part of a Bachelor's Thesis in Computer Engineering in collaboration with the CSIC neuroscience laboratory.

Features

🔍 Automatic detection of PPII segments via phi/psi angle analysis. 🧬 Identification of Cα-H···O=C interactions relevant to structural stability. 📊 Export of results in CSV format for further analysis. 🎨 Direct visualization in PyMOL with customizable color codes. 🖱️ Simple GUI based on Tkinter — no commands required; all actions are accessible via buttons.

Requirements

  • PyMOL 2.x or newer.
  • Python with Tkinter support enabled (for the GUI).

Installation

Quick method:

  1. Download `PPIIMoL.py` directly from the GitHub repository.
  2. In PyMOL, run:
run /path/to/PPIIMoL.py

Full repository (optional):

  1. Clone the repository to also get example files and documentation:
git clone https://github.com/silviaenma/PPIIMoL.git
  1. In PyMOL, run:
run PPIIMoL/PPIIMoL.py

(Optional) Install permanently as a plugin:

  • In PyMOL: Plugin → Plugin Manager → Install New Plugin.
  • Select `PPIIMoL.py` or the full `PPIIMoL` folder.
  • Restart PyMOL.

Usage

Once loaded, PPIIMoL opens a Tkinter-based graphical interface. From this window, you can:

  • Load a PDB file.
  • Detect PPII helices.
  • Export results as CSV.
  • Change visualization colors directly.

Results are automatically exported to a folder named with the current date, containing CSV files with detected segments and interactions. Detected PPII helices are highlighted in PyMOL according to the selected color scheme.

Repository

The project is hosted on GitHub: PPIIMoL on GitHub

License

This project is licensed under the GNU GPLv3.

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