Automated multiconformer model building for X-ray crystallography and cryo-EM

Area of Science:

• Structural biology
• Computational biology
• Biophysics

Background:

• Biomolecules exist in multiple functional conformational states.
• Traditional methods like X-ray crystallography and cryo-EM yield ensemble-averaged data.
• Current models often represent only a single conformation, missing structural complexity.

Purpose of the Study:

• To address the need for modeling structural ensembles that accurately reflect experimental data.
• To introduce enhanced qFit software for automated modeling of protein conformational heterogeneity.
• To improve the representation of biomolecular structural diversity.

Main Methods:

• Enhancements to the qFit automated computational strategy.
• Incorporating protein conformational heterogeneity into models built into density maps.
• Utilizing superior Rfree and geometry metrics for validation.

Main Results:

• qFit produces multiconformer models that capture conformational heterogeneity.
• Algorithmic improvements lead to superior Rfree and geometry metrics.
• Models are compatible with standard model building and refinement software.

Conclusions:

• qFit reduces the difficulty of creating multiconformer models.
• This facilitates the development of new hypotheses on macromolecular dynamics and function.
• Enables more accurate representation of biomolecular structural diversity.