QSProteome: A Community-Driven Interactive Platform for Large-Scale Exploration and Evaluation of Predicted Protein...

Area of Science:

• Structural biology
• Computational biology
• Bioinformatics

Background:

• Quaternary protein structure modeling and evaluation are crucial for understanding biological functions.
• Existing resources often lack comprehensive, community-driven refinement capabilities for large-scale protein complex data.

Purpose of the Study:

• To introduce QSProteome, a community-scale platform for modeling, evaluating, and refining quaternary protein structure.
• To provide a dynamic, scalable infrastructure for proteome-scale structural biology research.
• To enable community-led assessment and iterative refinement of protein complex structures.

Main Methods:

• Hosting 35,528 unique modeled protein assemblies from BioCyc and ComplexPortal databases.
• Utilizing interactive 3D visualization, confidence metrics, structural alignments, and functional annotations for each model.
• Implementing a cloud-based server for continuous user uploads and automated processing, including a gamified re-curation workflow.

Main Results:

• QSProteome currently hosts over 35,528 modeled protein assemblies, covering extensive curated complex databases.
• The platform successfully processed and validated over 54,000 models within 14 weeks.
• A community-led assessment of 1,547 ABC transporter complexes was facilitated through the re-curation workflow.

Conclusions:

• QSProteome provides a unified, searchable, and extensible framework for proteome-scale structural biology.
• The platform enhances accessibility and reusability of structural data, fostering discovery and annotation.
• Community engagement through gamified workflows drives iterative refinement and advances collaborative structural biology research.