Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

By David Sehnal, Sebastian Bittrich, M. Deshpande, Radka Svobodová Vareková, Karel Berka, V. Bazgier, S. Velankar, Stephen K. Burley, Jaroslav Koca, Alexander S. Rose. Nucleic Acids Res., 2021

1,008 citations recorded by the source corpus.

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Subfields: Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/907ef41207725aa09880e4477e03a85b8c96b7b9

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In Materials Chemistry

1. Ben M. Webb
2. Jianlin Cheng
3. Andrej Sali
4. Yang Zhang
5. Mallur Srivatsan Madhusudhan
6. Jinbo Xu
7. Torsten Schwede
8. Roland L. Dunbrack

In Molecular Biology

1. Yang Zhang
2. Jianlin Cheng
3. Ben M. Webb
4. Jinbo Xu
5. Andrej Sali
6. Johannes Söding
7. Peer Bork
8. Paul D. Thomas

Citations in the corpus

• Geometric Transformers for Protein Interface Contact Prediction (2021, background): “Figure 1: A Mol* (Sehnal et al. (2021)) visualization of interacting protein chains (PDB ID: 3H11).”
• InterPro: the protein sequence classification resource in 2025 (2024, positive): “In our previous publication, we reported the integration of the Mol* 3D molecular viewer ( 41 ) to enable users to visualise predicted structures, which are colour-coded by the predicted local distance difference test (pLDD T), a per -residue confidence measure.”
• InterPro in 2022 (2022, positive): “The 3D structure of the model is displayed in the Mol* Viewer (24) and the residues are coloured using the predicted Local Distance Difference Test (pLDDT) score (25), with a gradient going from blue (high confidence) to red (low confidence).”
• AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences (2023, methodology): “We improved the visualisation of non-consecutive regions and the interactivity between the PAE viewer and the 3D molecular graphics viewer, Mol* ( 23 ) (Figure 5 ).”
• RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning (2022, methodology): “Finally, a standalone implementation of Mol* (https:// www.rcsb.org/3d-view) is available for visualizing and analyzing 3D structures not accessible within RCSB.org.”
• FerrDb V2: update of the manually curated database of ferroptosis regulators and ferroptosis-disease associations (2022, methodology): “Integrating external gene resources For genes with protein products, three-dimensional (3D) protein structures are from the AlphaFold Protein Structure Database (https://alphafold.ebi.ac.uk/) (23).”
• PDBe-KB: collaboratively defining the biological context of structural data (2021, background): “The superposed coordinates are made available on the aggregated views of proteins, where clustered, superposed PDB chains can be displayed using the interactive 3D molecular viewer, Mol* (47), by clicking on the ‘view structure clusters’ buttons.”