Modeling Flexible Protein Structure With AlphaFold2 and Crosslinking Mass Spectrometry

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Predicting protein structures with multiple conformations is challenging.
• Experimental methods like crosslinking mass spectrometry (XL-MS) provide structural constraints.
• AlphaFold2 (AF2) generates accurate protein structure predictions but may not capture all conformational states.

Purpose of the Study:

• To develop and validate a computational pipeline integrating AF2 and XL-MS for modeling multi-conformational proteins.
• To introduce novel scoring functions, monolink probability (MP) and crosslink probability (XLP), for assessing predicted protein models using XL-MS data.
• To demonstrate the pipeline's effectiveness in identifying distinct protein conformations.

Main Methods:

• Generated protein structure ensembles using AlphaFold2.
• Developed MP and XLP scores based on residue depth to evaluate predicted conformations against XL-MS data.
• Benchmarked MP and XLP scores on decoy structures and applied them to model open and closed conformations of C3, luciferase, and glutamine-binding periplasmic protein.

Main Results:

• The MP and XLP scores outperformed existing scoring functions in identifying correct protein structures.
• The pipeline successfully identified correct conformations for three proteins (C3, luciferase, glutamine-binding periplasmic protein) in five out of six cases using XL-MS data.
• Monolinks, assessed by the MP score, were crucial for identifying the open conformation of glutamine-binding periplasmic protein, especially when considering monolink occupancy.

Conclusions:

• The integration of AF2 with XL-MS provides a powerful approach for modeling protein conformational dynamics.
• The developed MP and XLP scoring functions offer reliable metrics for assessing the quality of predicted protein models.
• This pipeline demonstrates the complementarity of computational predictions and experimental data in structural biology.