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= PPIIMoL =
= PPIIMoL =


'''PPIIMoL''' is a Python module for [[PyMOL]] that automates the detection of polyproline II (PPII) helices in proteins.
'''PPIIMoL''' is a Python module for [[PyMOL]] that automates the detection of polyproline II (PPII) helices in proteins. It identifies PPII-like φ/ψ angle patterns, screens for plausible non‑canonical Cα–H···O=C contacts, and provides one‑click visualization and export.
It streamlines structural analysis by:


* Identifying characteristic torsional angles (phi and psi) of PPII helices.
This tool was developed as part of a Bachelor's Thesis in Computer Engineering in collaboration with the '''Protein Structure, Dynamics and Interactions by NMR Group''' at the Instituto de Química‑Física “Blas Cabrera” (IQF‑CSIC). The module’s design and validation take as a '''primary reference''' the data and architectonic principles reported by '''Segura Rodríguez & Laurents (2024)'''. See ''Provenance & how to cite'' below.
* Detecting potential non-canonical hydrogen bonds (Cα-H···O=C) relevant to structural stability.
 
* Exporting results for further analysis.
== Scientific background ==
* Providing direct, customizable visualization in PyMOL.
Polyproline II (PPII) helices are extended, left‑handed motifs (≈3 residues/turn) typically enriched in glycine‑ and proline‑rich domains. Although common in several glycine‑rich bundles, they are often unannotated in PDB files. PPIIMoL automates their detection directly in PyMOL to improve speed and reproducibility.


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


== Features ==
== Features ==
Line 20: Line 18:


== 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 (for the GUI)


== Installation ==
== Installation ==
'''Quick method:'''
'''Option A — Single‑file run (no cloning)'''
# Download `PPIIMoL.py` directly from the [https://github.com/silviaenma/PPIIMoL GitHub repository].
# Download `PPIIMoL.py` from the [https://github.com/silviaenma/PPIIMoL GitHub repository].
# In PyMOL, run:
# In PyMOL:
<pre>
<pre>
run /path/to/PPIIMoL.py
run /path/to/PPIIMoL.py
</pre>
</pre>


'''Full repository (optional):'''
'''Option B — Clone 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>
# In PyMOL, run:
Then in PyMOL:
<pre>
<pre>
run PPIIMoL/PPIIMoL.py
run PPIIMoL/PPIIMoL.py
</pre>
</pre>


(Optional) Install permanently as a plugin: 
'''Option C — Install as plugin (optional)'''
* In PyMOL: '''Plugin → Plugin Manager → Install New Plugin'''. 
* PyMOL → '''Plugin → Plugin Manager → Install New Plugin''' → select `PPIIMoL.py` (or the folder) → restart.
* Select `PPIIMoL.py` or the full `PPIIMoL` folder. 
* Restart PyMOL.


== Usage ==
== Usage ==
Once loaded, PPIIMoL opens a Tkinter-based graphical interface. 
When loaded, PPIIMoL opens a Tkinter window with buttons to:
From this window, you can:
* Prepare the structure (remove solvent, add hydrogens)
* Load a PDB file. 
* Detect PPII segments
* Detect PPII helices. 
* Visualize / color segments
* Export results as CSV.
* Export results (CSV, PDB)
* Change visualization colors directly.
 
Outputs are written to a dated folder and objects/selections are created in the PyMOL session.
 
== Figures ==
<!-- Example insertions; replace with your uploaded file names -->
[[File:PPIIMoL_Fig1.jpg|thumb|center|Figure 1 from Segura Rodríguez & Laurents (2024), bioRxiv preprint of "Architectonic principles of polyproline II helix bundle protein domains". Licensed under CC BY‑NC‑ND 4.0.]]
[[File:PPIIMoL_Fig2.jpg|thumb|center|Figure 2 from Segura Rodríguez & Laurents (2024), bioRxiv preprint. Licensed under CC BY‑NC‑ND 4.0.]]
<!-- Add Fig3..Fig8 similarly if desired -->
 
== Provenance & how to cite ==
The algorithm implements the manual workflow used at IQF‑CSIC and was benchmarked on reference domains reported by Segura Rodríguez & Laurents. If you use PPIIMoL in research, please cite:


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.
* '''Software''' — Rodríguez Fernández, S. E. ''PPIIMoL: automated detection of polyproline II helices in PyMOL''. GitHub: https://github.com/silviaenma/PPIIMoL (GPL‑3.0).
* '''Primary reference (journal)''' — Segura Rodríguez, C. M., & Laurents, D. V. (2024). ''Architectonic principles of polyproline II helix bundle protein domains''. ''Archives of Biochemistry and Biophysics'', 741, 109981. [https://doi.org/10.1016/j.abb.2024.109981 DOI]
* '''Figures source (preprint license)''' — bioRxiv preprint of the above article, licensed under CC BY‑NC‑ND 4.0 (attribution required; no derivatives).


== Repository ==
== Repository ==
The project is hosted on GitHub: [https://github.com/silviaenma/PPIIMoL PPIIMoL on GitHub]
* [https://github.com/silviaenma/PPIIMoL PPIIMoL on GitHub]


== License ==
== License ==
This project is licensed under the [https://www.gnu.org/licenses/gpl-3.0.html GNU GPLv3].
PPIIMoL is released under the [https://www.gnu.org/licenses/gpl-3.0.html GNU GPLv3].


[[Category:Plugins]]
[[Category:Plugins]]

Revision as of 04:49, 14 August 2025

PPIIMoL

PPIIMoL is a Python module for PyMOL that automates the detection of polyproline II (PPII) helices in proteins. It identifies PPII-like φ/ψ angle patterns, screens for plausible non‑canonical Cα–H···O=C contacts, and provides one‑click visualization and export.

This tool was developed as part of a Bachelor's Thesis in Computer Engineering in collaboration with the Protein Structure, Dynamics and Interactions by NMR Group at the Instituto de Química‑Física “Blas Cabrera” (IQF‑CSIC). The module’s design and validation take as a primary reference the data and architectonic principles reported by Segura Rodríguez & Laurents (2024). See Provenance & how to cite below.

Scientific background

Polyproline II (PPII) helices are extended, left‑handed motifs (≈3 residues/turn) typically enriched in glycine‑ and proline‑rich domains. Although common in several glycine‑rich bundles, they are often unannotated in PDB files. PPIIMoL automates their detection directly in PyMOL to improve speed and reproducibility.


Features

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


Requirements

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

Installation

Option A — Single‑file run (no cloning)

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

Option B — Clone repository (optional) 

git clone https://github.com/silviaenma/PPIIMoL.git

Then in PyMOL: 

run PPIIMoL/PPIIMoL.py

Option C — Install as plugin (optional)

  • PyMOL → Plugin → Plugin Manager → Install New Plugin → select `PPIIMoL.py` (or the folder) → restart.

Usage

When loaded, PPIIMoL opens a Tkinter window with buttons to:

  • Prepare the structure (remove solvent, add hydrogens)
  • Detect PPII segments
  • Visualize / color segments
  • Export results (CSV, PDB)

Outputs are written to a dated folder and objects/selections are created in the PyMOL session.

Figures

Figure 1 from Segura Rodríguez & Laurents (2024), bioRxiv preprint of "Architectonic principles of polyproline II helix bundle protein domains". Licensed under CC BY‑NC‑ND 4.0.
Figure 2 from Segura Rodríguez & Laurents (2024), bioRxiv preprint. Licensed under CC BY‑NC‑ND 4.0.

Provenance & how to cite

The algorithm implements the manual workflow used at IQF‑CSIC and was benchmarked on reference domains reported by Segura Rodríguez & Laurents. If you use PPIIMoL in research, please cite:

  • Software — Rodríguez Fernández, S. E. PPIIMoL: automated detection of polyproline II helices in PyMOL. GitHub: https://github.com/silviaenma/PPIIMoL (GPL‑3.0).
  • Primary reference (journal) — Segura Rodríguez, C. M., & Laurents, D. V. (2024). Architectonic principles of polyproline II helix bundle protein domains. Archives of Biochemistry and Biophysics, 741, 109981. DOI
  • Figures source (preprint license) — bioRxiv preprint of the above article, licensed under CC BY‑NC‑ND 4.0 (attribution required; no derivatives).

Repository

License

PPIIMoL is released under the GNU GPLv3.

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