Structural information, resolution, and noise in high-resolution atomic force microscopy topographs.

Area of Science:

• Structural Biology
• Biophysics
• Surface Science

Background:

• Atomic Force Microscopy (AFM) provides high-resolution topographs of proteins under near-native conditions.
• Interpreting AFM images is challenging due to imaging mechanism particularities, tip geometry, and tip-sample interactions.
• Quantifying noise, distortions, and the impact of averaging on structural information remains critical.

Purpose of the Study:

• To develop a method for identifying high-quality protein images from AFM data.
• To introduce a novel resolution analysis for AFM topographs.
• To compare the structural information content of single-molecule AFM images versus averaged data.

Main Methods:

• Proposed a selection criterion based on the internal symmetry of imaged proteins to identify high-quality particles.
• Introduced a novel feature-based resolution analysis.
• Analyzed AFM topographs of AqpZ, AQP0, AQP2, and light-harvesting-complex-2.

Main Results:

• High-resolution AFM topographs contain many molecule images with minimal noise and distortions.
• Identified distinct resolution thresholds for structural information in different proteins (e.g., 10 Å for AqpZ).
• Demonstrated that the best single-molecule AFM images provide more accurate molecular representations than ensemble averages.

Conclusions:

• A symmetry-based selection criterion effectively identifies high-quality protein particles in AFM images.
• Feature-based resolution analysis provides a reliable method for assessing AFM data resolution.
• Single-molecule AFM imaging offers advantages over averaging for preserving detailed structural information, particularly in the z-dimension.