PyMOL

PyMOL
Schrödinger, LLC · Public domain · source
Name	PyMOL
Developer	Schrödinger, Inc.; Warren L. DeLano (originator)
Released	2000
Programming language	C, Python
Operating system	Windows 10, macOS, Ubuntu, Debian, Red Hat Enterprise Linux
License	Proprietary, formerly GNU General Public License

PyMOL PyMOL is a molecular visualization system used for rendering 3D structures of biomolecules. It is employed across research institutions, pharmaceutical companies, and educational settings for visualization, publication-quality graphics, and structural analysis. PyMOL integrates with structural databases, modeling tools, and computational platforms to support workflows in structural biology, medicinal chemistry, and bioinformatics.

Overview

PyMOL provides an interactive environment for viewing and manipulating three-dimensional coordinates from sources such as the Protein Data Bank, enabling users to examine proteins, nucleic acids, and small molecules. It is widely used alongside tools like BLAST, Clustal Omega, MODELLER, Rosetta (software), and GROMACS for integrated structural analysis. Researchers at institutions including Harvard University, Stanford University, Massachusetts Institute of Technology, University of Cambridge, and University of California, San Francisco commonly use PyMOL for figure generation in journals such as Nature, Science, Cell, and PNAS.

Features and Functionality

PyMOL supports high-quality rendering of molecular representations: cartoon, sticks, spheres, surface, and mesh, often used in tandem with tools like VMD (software), Chimera, ChimeraX, MOE (software), and Schrödinger (company). It includes features for ray tracing, ambient occlusion, depth-cueing, and publication-ready image export comparable to graphics from Maya (software), Blender, and Adobe Photoshop. Structural analysis features integrate with databases and resources such as UniProt, Gene Ontology, Pfam, SCOP, CATH (protein structure classification), and InterPro. PyMOL provides scripting in Python and command-line control similar to workflows in R and MATLAB, enabling automation used by groups at European Molecular Biology Laboratory, Max Planck Society, and Weizmann Institute of Science.

History and Development

PyMOL was originally authored by Warren L. DeLano and later maintained and commercialized by entities including DeLano Scientific and Schrödinger, Inc.. Its development intersects with milestones in structural biology such as the launch of the Protein Data Bank and advances from laboratories at Scripps Research, European Bioinformatics Institute, Cold Spring Harbor Laboratory, and Broad Institute. PyMOL’s evolution paralleled the rise of open-source scientific software exemplified by projects like Bioconductor, NumPy, SciPy, and Biopython, and engaged with computational initiatives at National Institutes of Health, Wellcome Trust, and Howard Hughes Medical Institute.

Architecture and Implementation

PyMOL combines a core written in C (programming language), extensions in Python, and OpenGL-based rendering influenced by graphics libraries used in OpenGL, OpenCL, and Vulkan (API). Its plugin architecture allows integration with software such as UCSF Chimera, ChimeraX, MDAnalysis, ProDy, and PyRosetta. PyMOL supports file formats and standards from the Protein Data Bank, mmCIF, PDBML, and small-molecule files used by SMILES-aware tools and cheminformatics libraries like RDKit, Open Babel, and ChemAxon.

Usage and Applications

PyMOL is used for preparing figures for publications in journals like Cellular, Nature Structural & Molecular Biology, Journal of Molecular Biology, and Biochemistry (journal), and in presentations at meetings such as the Gordon Research Conferences, American Chemical Society, Biophysical Society, and European Crystallographic Meetings. It supports workflows in structure-based drug design practiced by companies like Pfizer, Novartis, Merck & Co., GlaxoSmithKline, and AstraZeneca, and academic projects at University of Oxford, Karolinska Institutet, ETH Zurich, and University of Tokyo. PyMOL is used in conjunction with computational chemistry packages including AutoDock, Schrödinger Suite, AMBER (software), CHARMM, and NAMD (software) for docking, molecular dynamics, and conformational analysis. Educational adoption occurs in courses run by Cold Spring Harbor Laboratory, MIT OpenCourseWare, Coursera, and university curricula at Yale University and Princeton University.

Licensing and Distribution

PyMOL’s licensing history spans GNU General Public License origins and subsequent proprietary distribution by Schrödinger, Inc., with academic licensing models similar to those used by MATLAB, Maple (software), and IDV (software). Binary builds are distributed for Windows 10, macOS, and major Linux distributions like Ubuntu and Red Hat Enterprise Linux, and packaging efforts mirror practices used by Debian and Conda ecosystems. Community forks and builds have interacted with licensing debates seen in projects such as ffmpeg and OpenSSL.

Community and Ecosystem

A large community of users contributes scripts, plugins, and tutorials hosted via platforms like GitHub, GitLab, Stack Overflow, and educational sites such as YouTube, Coursera, and edX. Collaborative projects and repositories link to resources maintained by European Bioinformatics Institute, RCSB PDB, Protein Data Bank Japan, and regional infrastructure like ELIXIR. User communities organize workshops and training at conferences like Gordon Research Conferences, Biophysical Society, and meetings at Cold Spring Harbor Laboratory and EMBO. Many research groups across institutions such as Johns Hopkins University, Imperial College London, University of California, Berkeley, University of Toronto, and McGill University publish methods and scripts that extend PyMOL’s capabilities.

Category:Molecular graphics software