Exploring PyMOL: A Beginner’s Guide to Molecular Visualization

Publication-Quality Images in PyMOL: Step-by-Step Rendering TechniquesHigh-quality molecular images are essential for papers, posters, presentations, and teaching materials. PyMOL is one of the most widely used molecular visualization tools because it combines powerful rendering capabilities with scripting flexibility. This guide covers everything from scene preparation to advanced rendering and post-processing so you can produce publication-ready figures with consistent, clear, and informative visuals.

1. Planning your figure

Before opening PyMOL, decide what message each panel should convey. Ask:

Which structural features (binding site, secondary structure, ligand orientation, electrostatics) are essential?
What level of detail is appropriate (domain-level cartoon vs. atomic sticks)?
What aspect ratios and resolutions are required by the journal or conference?

Create a simple sketch of panels and annotations. Consistent color schemes, labeling styles, and scale bars across a figure set improve readability.

2. File preparation and data quality

Start with high-quality structural data:

Use experimentally derived coordinates (PDB) when possible. Check resolution and R-factors.
For modeled structures, validate geometry and remove or remodel problematic regions.
Clean the structure: remove alternate conformations you don’t want, delete excess solvent or ions not relevant to the figure, and ensure chain IDs and residue numbering are correct.

Save a copy of the cleaned coordinate file to keep your original intact.

3. Loading data and basic scene setup

Open PyMOL and load your structure:

Use descriptive object names for each file to keep the session organized.
Turn off default displays and enable only what you need:
- hide everything, then selectively show cartoon, sticks, spheres, or surfaces. Example sequence:
```
fetch 1abc, async=0 hide everything show cartoon, 1abc show sticks, 1abc and resn LIG 
```
  Set the background to white for publications (or black for posters with bright colors):
```
bg_color white 
```

4. Choosing representations

Combine representations to emphasize different features:

Cartoon for overall fold.
Surface to show shape and binding pockets.
Sticks or spheres for ligands, key side chains, or cofactors.
Mesh for density or to show partial occupancy.

Use transparency strategically to reveal buried features:

set transparency, 0.5, surface_object

Avoid clutter: show only residues within a certain distance of a ligand for close-ups:

select pocket, (br. resn LIG around 5) show sticks, pocket

5. Coloring strategies

Colors guide the eye and communicate meaning. Choose palettes that are colorblind-safe and consistent:

Secondary structure: default cartoon colors or domain-specific palettes.
Ligands: bright, contrasting colors (orange, magenta).
Key residues: use distinct colors for catalytic residues, mutation sites, or interaction hotspots.

Apply semantic coloring via chains, properties, or custom selections:

color slate, chain A color cyan, chain B color orange, resn LIG

For consistent publication aesthetics, define colors in a small palette at the start of your script.

6. Lighting, shading, and material properties

Good lighting adds depth and realism. PyMOL exposes several settings:

Ambient, direct, and specular contributions:


set ambient, 0.2 set direct, 0.8 set specular, 0.5

Shininess and reflectivity:
```
set shininess, 10 set reflect, 0.1 
```
Use ray tracing to compute soft shadows and high-quality shading:
```
set ray_trace_mode, 1 
```
Be mindful: higher-quality lighting increases rendering time.

7. Camera, orientation, and framing

Choose camera viewpoints that communicate structural relationships clearly:

Use rotations in small increments for multiple panels to maintain consistent orientation.
Center and zoom precisely using the orient and zoom commands:
```
orient selection_name zoom selection_name, 1.2 
```
For reproducibility, save the view:
```
get_view # copy the output for later set_view calls 
```
Maintain margins: leave space around the molecule for labels and scale bars.

8. Labels and annotations

Effective labeling is concise and consistent:

Use residue labels only when necessary (e.g., active site residues).

Use font sizes that remain legible at final resolution:


label resi 45 and name CA, "A45" set label_size, 14 set label_color, black

Add arrows, text boxes, and scale bars in post-processing for precise placement (see section on post-processing). PyMOL can produce text labels but fine adjustments are easier in a vector editor.

9. Producing high-resolution images with ray tracing

PyMOL’s ray tracing produces publication-quality output by computing realistic light paths. Recommended workflow:

Increase image size to match journal requirements (e.g., 3000–4000 px for full-page illustrations).

Turn on ray tracing and set sampling for smooth edges:


set ray_trace_fog, 0 set antialias, 2 ray 3000,2000

For faster iterations, use lower resolution previews and only ray-trace final images.
If rendering takes too long, reduce reflections, shadows, or antialiasing.

10. Advanced rendering options

Depth-of-field: create subtle focus effects by enabling focal blur (requires PyMOL build support); use sparingly for emphasis.
Ambient occlusion: simulates soft global shadows—available via plugins or external renderers.
Background gradients: use light gradients to avoid harsh white backgrounds while keeping a publication-friendly look.

If extreme photorealism is desired, export geometry to Blender or a dedicated renderer (OBJ export via PyMOL and import into Blender), then add advanced materials, volumetric lighting, and compositing.

11. Consistent multi-panel figures

For multi-panel figures across experiments:

Use the same camera views and color palette where appropriate.
Save and reuse views and scripts for reproducibility.
Keep scale, font sizes, and line weights consistent.

You can script the generation of multiple views and image sizes to automate figure production:

# pseudo-script example set ray_trace_mode, 1 for view in [view1, view2, view3]:     set_view view     ray 2000,1500     png panel_viewX.png, dpi=300

12. Export formats and DPI

PNG: raster format suitable for most journal submissions; export at 300–600 DPI depending on journal.
SVG/PDF: vector formats are not directly supported for molecular geometry—labels and overlays can be added as vectors in image editors.
TIFF/TIFF LZW: sometimes required by publishers; export from PNG and convert in an image editor to TIFF to preserve quality.

Use the png command to export:

png figure_panel.png, 3000, 2000, dpi=300, ray=1

13. Post-processing and assembly

Post-processing polishes the final figure:

Use an image editor (Affinity Photo, Photoshop, GIMP) or a vector tool (Illustrator, Inkscape) for:
- Adding arrows, labels, scale bars, and panel lettering.
- Adjusting line weights and contrast.
- Assembling multi-panel layouts with precise spacing.
Avoid altering structural colors that could mislead interpretation. Keep changes limited to composition and legibility.

For publication, save the master file and export final versions per journal specs.

14. Automation and reproducibility

Script your entire pipeline in PyMOL scripts (.pml or .py) so figures can be reproduced exactly:

Save session files (.pse) and scripts with comments.
Use version control for scripts and keep a record of the PDB files and rendering parameters.
Consider using headless rendering on a server for large batches.

Example header of a reproducible script:

# Figure 1A rendering script load 1abc.pdb, protein hide everything show cartoon color slate, chain A set ray_trace_mode, 1 set antialias, 2 set ray_trace_fog, 0 set shininess, 10 set bg_color, white set_view ( ... ) ray 3000,2000 png figure1A.png, dpi=300

15. Common pitfalls and troubleshooting

Blurry labels: increase label_size or render at higher DPI.
Pixelated edges: raise antialias or render at larger resolution.
Long render times: reduce reflections, shadow complexity, or antialias; use a render farm if necessary.
Inconsistent colors between panels: define colors once and reuse named colors/selections.

16. Quick checklist before submission

Resolution and DPI meet journal guidelines.
Color palette is accessible and consistent.
Labels are legible and unambiguous.
Scale bars and orientation markers are present where needed.
Figures saved in required formats with original editable masters.

Final note: invest time upfront in scripting and palette definition — it pays off with consistent, reproducible publication figures and much faster iteration.