Mol* (/'molstar/) is a modern web-based open-source toolkit for visualisation and analysis of large-scale molecular data
Open Mol* Viewer Viewer Documentation Issues & Feedback
High-performance graphics and data handling of the Mol* Viewer allow users to simultaneously visualise up to hundreds of (superimposed) protein structures, play molecular dynamics trajectories, render cell-level models at atomic detail with tens of millions of atoms, or display huge models obtained by I/HM such as the Nuclear Pore Complex.
Interactive Examples
HIV in blood serum

CellPack model of enveloped HIV capsid with ~13M atoms.

Alpha orbitals and density of Atorvastatin

Alpha orbitals and density of Atorvastatin.


Zika virus assembly and Cryo-EM density.

P-450 Superposition

Superposition and validation annotation of P-450 cytochromes.

Villin trajectory

Villin folding trajectory by Stefan Doerr (doi:10.6084/m9.figshare.12040257.v1).

GAIN domain

GAIN domain tethered agonist exposure (doi:10.1016/j.molcel.2020.12.042). Based on an animation by Ramon Guixà-González.

HIV in blood serum

CellPack model of enveloped HIV capsid in blood serum with 60+M atoms.

Nuclear Pore Complex

IH/M structure of the Nuclear Pore Complex.


Render styles and lighting modes demonstration.

1RB8 Annotated Assembly

Annotated assembly of the phiX174 DNA binding protein (PDB id 1RB8).

SARS-CoV-2 Virion

SARS-CoV-2 Virion. Coarse-grained model by Alvin Yu et al. (doi:10.1016/j.bpj.2020.10.048).

BtuB molecules in a lipid bilayer

BtuB molecules in a lipid bilayer. Coarse-grained model by Matthieu Chavent et al. (doi:10.1038/s41467-018-05255-9).

Join Development on GitHub
The Mol* toolkit provides a comprehensive solution for molecular data delivery, visualization and analysis that can be embedded into a wide range of 3rd party solutions. It includes a customizable plugin for high quality WebGL based molecular data visualization, as well as servers for model and experimental (X-ray, Cryo-EM, etc.) data delivery, efficient BinaryCIF data format support, and other exciting features.
The project is an open collaboration started by
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