Exploring the potential of AlphaFold distograms for predicting binding-induced hinge motions

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• AlphaFold models predict static protein structures, limiting their utility for understanding dynamic biological processes.
• Interpreting flexible regions in low-resolution cryo-electron microscopy (cryo-EM) maps remains a significant challenge in structural biology.

Purpose of the Study:

• To evaluate the potential of AlphaFold-generated distograms for predicting conformational flexibility, specifically binding-induced hinge motions.
• To assess distograms as a model-independent method for interpreting ambiguous hinge regions in cryo-EM data.

Main Methods:

• Analysis of AlphaFold2/3 distograms for the Adenylate Kinase 2 (AK2)/Apoptosis-Inducing Factor Mitochondrion 1 (AIFM1) complex.
• Comparison of distogram predictions with molecular dynamics simulations and experimental cryo-EM data.
• Extension of the analysis to additional biological systems to validate the findings.

Main Results:

• AlphaFold distograms successfully captured the binding-induced hinge motion in AK2, a dynamic feature absent in the static AlphaFold structures.
• The study demonstrated that distograms can identify conformational flexibility even in the absence of explicit structural dynamics.
• The findings were consistent across multiple biological systems, highlighting the general applicability of the method.

Conclusions:

• AlphaFold distograms provide a valuable, structure-free metric for identifying alternative conformational states and hinge motions.
• Distograms can significantly aid in the interpretation of ambiguous densities and flexible regions within low-resolution cryo-EM maps.
• This approach enhances the utility of AlphaFold predictions beyond static structural models for understanding protein dynamics.