by Michele Brignoli, Track « Chemoinformatics and Physical Chemistry », Milan-Strasbourg, 2025
Molecular visualization is essential for gaining a deep understanding of molecular interactions and properties. Among the various tools available, PyMOL [1] stands out as one of the most versatile and powerful platforms for visualizing molecular structures. It is available in both a free, open-source version and a more feature-rich paid version, which includes access to advanced visualization capabilities. Numerous online tutorials and resources support new users in exploring both basic and advanced functionalities, from generating high-resolution molecular images to creating animations of dynamic molecular interactions.
The software is especially valuable for visualizing binding sites and analyzing biomolecular interactions (Figure 1), making it a crucial asset in rational drug design [2] by highlighting hydrogen bonds, hydrophobic contacts, and other key residues. PyMOL also integrates external tools and plugins, enhancing its functionality for advanced tasks like conformational analysis and molecular dynamics visualization.
With Python scripting, users can streamline workflows, execute complex manipulations, and automate routine tasks. This scripting capability empowers users to create complex visualizations, develop custom plugins, and tailor the software to meet specific research needs. Additionally, an active community of users contributes a wealth of scripts, plugins, and tutorials, offering robust support for both beginners and advanced users alike [3].
The latest versions of PyMOL include enhanced features such as real-time collaboration and integration with machine learning models. With its ongoing development and strong community support, PyMOL is positioned as one of the foundational tool for future innovations in molecular visualization and structural analysis. Its accessibility, precision, and versatility make it an invaluable resource for a wide range of users, from students to professional researchers in structural biology and computational chemistry. Therefore, I think that PyMOL is becoming indispensable in scientific research across bioinformatics and chemoinformatics disciplines.
References:
[1] The PyMOL Molecular Graphics System, Version 3.0 Schrödinger, LLC.
[2] Shuguang Yuan et al. "Using PyMOL as a platform for computational drug design." Wiley Interdisciplinary Reviews: Computational Molecular Science, 7 (2017). https://doi.org/10.1002/wcms.1298.
[3] Magnus Kjaergaard et al. "A Semester-Long Learning Path Teaching Computational Skills via Molecular Graphics in PyMOL." The Biophysicist (2022). https://doi.org/10.35459/tbp.2022.000219.