Discovery-Versus Hypothesis-Driven Detection of Protein-Protein Interactions and Complexes

Area of Science:

• Proteomics
• Molecular Cell Biology
• Systems Biology

Background:

• Protein complexes are essential for cellular functions, acting as molecular machinery.
• Mass spectrometry (MS) is the primary technology for identifying and quantifying protein interactions (interactome).

Purpose of the Study:

• To review the benefits and limitations of various MS-based interactome screening techniques.
• To discuss discovery- versus hypothesis-driven data analysis for large-scale interactome data.
• To provide guidance on selecting appropriate methods for protein-protein interaction studies.

Main Methods:

• Summary and comparison of different MS-based interactome identification approaches.
• Focus on untargeted interactome acquisition, including co-fractionation MS.
• Evaluation of data analysis strategies: discovery-driven vs. hypothesis-driven.

Main Results:

• MS-based methods offer diverse capabilities for interactome mapping.
• Hypothesis-driven, complex- or network-centric analyses are promising for comparative studies.
• Increasing public interactomic data enhances future research potential.

Conclusions:

• Careful selection of MS acquisition and analysis methods is crucial for successful protein-protein interaction studies.
• Hypothesis-driven approaches leverage existing data for deeper insights.
• The field benefits from growing interactomic datasets and refined analytical strategies.