Comparing cryo-EM methods and molecular dynamics simulation to investigate heterogeneity in ligand-bound TRPV1

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Cryo-electron microscopy (cryo-EM) is crucial for determining biological macromolecule structures.
• Analyzing molecular heterogeneity in single-particle cryo-EM is an emerging computational challenge.

Purpose of the Study:

• To evaluate and compare five computational methods for detecting heterogeneity in cryo-EM data.
• To develop a tool for quantitatively assessing agreement between different heterogeneity analysis methods.

Main Methods:

• Analysis of a TRPV1 dataset using 3DFlex, 3DVA, cryoDRGN, ManifoldEM, and Bayesian ensemble reweighting.
• Development and application of AnaVox for comparing heterogeneity detection results.
• Integration of Bayesian ensemble reweighting with molecular dynamics simulations.

Main Results:

• Significant molecular heterogeneity was detected in the TRPV1 dataset.
• Each computational method produced distinct results, varying in detected heterogeneity types (compositional, conformational).
• AnaVox enabled quantitative comparison of method outputs, highlighting discrepancies.

Conclusions:

• Current computational methods for cryo-EM heterogeneity analysis show stochasticity and potential bias, challenging routine application.
• The developed AnaVox tool facilitates comparison and validation of heterogeneity findings.
• Future advancements in these tools promise enhanced quantitative biophysical investigations using cryo-EM data.