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Predicting the placement of biomolecular structures on AFM substrates based on electrostatic interactions
Romain Amyot1,2, Kaho Nakamoto2, Noriyuki Kodera2
1JSPS International Research Fellow, Kanazawa, Ishikawa, Japan.
Frontiers in Molecular Biosciences
|December 14, 2023
Summary
Predicting macromolecular placement on AFM substrates improves biomolecular imaging. This method uses electrostatic interactions to guide sample orientation, enhancing structural analysis and experimental design for techniques like high-speed AFM.
Area of Science:
- Biophysics
- Structural Biology
- Nanotechnology
Background:
- Atomic force microscopy (AFM) visualizes biomolecular dynamics.
- Sample orientation on substrates is crucial but experimentally uncontrolled.
- Inferring orientation from AFM images is challenging due to resolution limits.
Purpose of the Study:
- To develop a predictive method for macromolecular placement on AFM substrates.
- To improve the interpretation of AFM imaging data.
- To aid in experimental design for AFM studies.
Main Methods:
- Modeling electrostatic interactions between sample and substrate.
- Predicting sample orientation and imaging stability.
- Integrating the method into BioAFMviewer software.
Main Results:
- Successfully predicted macromolecular placement for Cas9, aptamer-protein complexes, Monalysin, and ClpB.
- The model accounts for buffer conditions affecting imaging stability.
- Enabled pre-experimental predictions and post-experimental analysis.
Conclusions:
- Electrostatic modeling accurately predicts biomolecular placement on AFM substrates.
- This approach enhances the reliability and interpretability of AFM data.
- The developed tool facilitates advanced AFM-based structural and dynamic studies.
