PDBe: enhanced structural data exploration to facilitate discovery

Area of Science:

• Structural biology
• Bioinformatics
• Scientific data visualization

Background:

• The Protein Data Bank in Europe (PDBe) provides open access to experimentally determined macromolecular structures.
• PDBe-Knowledge Base (PDBe-KB) enriches structural data with annotations.
• Macromolecular entry pages are crucial for users accessing structural information.

Purpose of the Study:

• To redesign the PDBe entry pages to improve usability and accessibility of macromolecular structure data.
• To enhance the integration of 3D visualization, annotations, and user-uploaded data.
• To support fundamental and applied research, as well as education in structural biology.

Main Methods:

• Organizing content into logical views for improved navigation.
• Integrating central 3D visualization tools.
• Implementing AI-driven residue-level annotations via literature text mining.
• Refactoring APIs for streamlined annotation access.
• Enabling users to upload and visualize their own residue-level features.

Main Results:

• A redesigned PDBe entry page with enhanced usability and logical content organization.
• Integrated 3D visualization and sequence feature exploration.
• AI-driven residue-level annotations and standardized molecular scenes.
• User-uploaded features can be visualized alongside PDBe-KB annotations.
• Streamlined access to structural data and annotations through refactored APIs.

Conclusions:

• The redesigned PDBe entry pages offer a more accessible, flexible, and scalable framework for interacting with structural data.
• Enhanced features facilitate research, education, and interpretation of both public and private structural information.
• The updates expand the value of PDBe to structural biologists and the broader life sciences community.