Dockground: Expanding the Resource to Protein-DNA Complexes.

Area of Science:

• Structural Biology
• Computational Biology
• Molecular Biology

Background:

• Protein-DNA interactions are fundamental to essential cellular processes like replication, transcription, and DNA repair.
• Experimentally determining the structures of protein-nucleic acid complexes is challenging due to their instability, resulting in limited available data.
• Computational modeling is vital for understanding biomolecular mechanisms and predicting molecular interactions.

Purpose of the Study:

• To expand the Dockground resource to include protein-DNA complexes, enhancing knowledge of macromolecular interfaces.
• To provide a data resource for developing and improving structure-based modeling techniques for macromolecular interactions.
• To offer new features including automatic weekly updates and a user-friendly web interface for protein-DNA complex data.

Main Methods:

• Expansion of the Dockground database to incorporate protein-DNA complexes.
• Implementation of automatic weekly update procedures for the resource.
• Development of a user-friendly web interface for searching, analyzing, and downloading complex data.

Main Results:

• The Dockground resource now comprehensively covers protein-protein, protein-RNA, and protein-DNA interactions.
• New automated updates and an enhanced web interface improve accessibility and utility for researchers.
• The resource's utility was demonstrated by benchmarking AlphaFold3 predictions against the protein-DNA complex data.

Conclusions:

• The expanded Dockground resource significantly advances the study of macromolecular interactions, particularly protein-DNA complexes.
• This resource is essential for computational modeling, aiding in the understanding and potential modulation of key cellular processes.
• Dockground serves as a valuable, publicly accessible data repository for the structural biology and computational modeling communities.