Journal
BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS
Volume 1864, Issue 2, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.bbagen.2019.129420
Keywords
Atomic force microscopy; Computational modeling; Gaussian mixture model; Monte-Carlo sampling
Categories
Funding
- JSPS KAKENHI [26119006, 17K07305, 16K07286]
- FOCUS for Establishing Supercomputing Center of Excellence
- RIKEN Dynamic Structural Biology Pioneering Projects
- Grants-in-Aid for Scientific Research [16K07286, 17K07305] Funding Source: KAKEN
Ask authors/readers for more resources
Background: Atomic Force Microscopy (AFM) is an experimental technique to study structure-function relationship of biomolecules. AFM provides images of biomolecules at nanometer resolution. High-speed AFM experiments produce a series of images following dynamics of biomolecules. To further understand biomolecular functions, information on three-dimensional (3D) structures is beneficial. Method: We aim to recover 3D information from an AFM image by computational modeling. The AFM image includes only low-resolution representation of a molecule; therefore we represent the structures by a coarse grained model (Gaussian mixture model). Using Monte-Carlo sampling, candidate models are generated to increase similarity between AFM images simulated from the models and target AFM image. Results: The algorithm was tested on two proteins to model their conformational transitions. Using a simulated AFM image as reference, the algorithm can produce a low-resolution 3D model of the target molecule. Effect of molecular orientations captured in AFM images on the 3D modeling performance was also examined and it is shown that similar accuracy can be obtained for many orientations. Conclusions: The proposed algorithm can generate 3D low-resolution protein models, from which conformational transitions observed in AFM images can be interpreted in more detail. General significance: High-speed AFM experiments allow us to directly observe biomolecules in action, which provides insights on biomolecular function through dynamics. However, as only partial structural information can be obtained from AFM data, this new AFM based hybrid modeling method would be useful to retrieve 3D information of the entire biomolecule.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available