NGL – a molecular graphics library for the web

Interactive visualization and annotation of large macromolecular complexes on the web is becoming a challenging problem as experimental techniques advance at an unprecedented rate. Integrative/Hybrid approaches are increasing being used to determine 3D structures of biological macromolecules by combining information from X-ray crystallography, NMR spectroscopy, and cryo-electron microscopy with data from diverse complementary experimental and computational methods. The wealth, size and complexity of available and future structures make scalable visualization and annotation solutions more important than ever. The web can provide easy access to the resulting visualizations for all interested parties, including colleagues, collaborators, reviewers and educators. Herein, we utilize the web-based NGL library to provide 3D visualization of experimental and computational data integrated with general molecular graphics.
The NGL library has a versatile API to control every aspect from data loading, processing, rendering and user-interaction. A distinguishing feature of NGL is its scalability to system with a million atoms and more. Further, the library supports many file formats for small molecules, macromolecular structures, molecular dynamics trajectories, maps for crystallographic, microscopy and general purpose volumetric data. Annotations can be loaded from text, json, msgpack or xml files. A wide array of customizable representations is available. Molecular data can be displayed as balls, sticks, cartoons, surfaces and labels or with specialized representations such as hyperballs and ropes. Volumetric data can be rendered as isosurfaces, point clouds or volume slices. Additional file parsers and data representations can be added through a plugin system.
The NGL library allows developers to create custom visualization solutions for specialized or novel 3D data derived from bioinformatics calculations and biophysical/biochemical experiments. The resulting interactive visualizations enable spatial understanding and exploratory analyses. Furthermore, these web-based tools simplify data exchange and foster collaborative analysis.