Integrated mass spectrometry strategy for functional protein complex discovery and structural characterization.

Area of Science:

• Biochemistry
• Structural Biology
• Proteomics

Background:

• Protein complexes are vital for biological processes.
• Affinity purification-mass spectrometry (AP-MS) identifies protein complexes.
• Validating novel complexes and understanding their mechanisms remain challenging.

Purpose of the Study:

• To review the integration of AP-MS and native top-down mass spectrometry (nTDMS) for protein complex discovery and structural characterization.
• To highlight the complementary role of AI in protein structure prediction for enhancing MS-based approaches.
• To propose a hybrid workflow for investigating protein complex structure-function relationships (SFR).

Main Methods:

• Review of current literature on AP-MS and nTDMS applications in proteomics.
• Discussion on the synergy between nTDMS and AI-driven protein structure prediction.
• Conceptualization of an integrated structural mass spectrometry and AI prediction workflow.

Main Results:

• AP-MS is effective for protein complex discovery.
• nTDMS provides structural insights into protein complexes.
• AI-based protein structure prediction complements nTDMS for detailed structural analysis.

Conclusions:

• Integrating AP-MS and nTDMS facilitates robust discovery and structural characterization of protein complexes.
• The combination of structural mass spectrometry and AI prediction presents a promising future for exploring protein complex SFRs.
• This hybrid approach is expected to advance the understanding and manipulation of biological processes.