Literature DB >> 31909999

Flexible Fitting of Biomolecular Structures to Atomic Force Microscopy Images via Biased Molecular Simulations.

Toru Niina1, Sotaro Fuchigami1, Shoji Takada1.   

Abstract

High-speed (HS) atomic force microscopy (AFM) is a prominent imaging technology that observes large-scale structural dynamics of biomolecules near the physiological condition, but the AFM data are limited to the surface shape of specimens. Rigid-body fitting methods were developed to obtain molecular structures that fit to an AFM image, without accounting for conformational changes. Here, we developed a method to fit flexibly a three-dimensional (3D) biomolecular structure into an AFM image. First, we describe a method to produce a pseudo-AFM image from a given 3D structure in a differentiable form. Then, using a correlation function between the experimental AFM image and the computational pseudo-AFM image, we developed a flexible fitting molecular dynamics (MD) simulation method by which we obtain protein structures that well fit to the given AFM image. We first test it with a twin experiment; using an AFM image produced from a protein structure different from its native conformation as a reference, we performed the flexible fitting MD simulations to sample conformations that fit well the reference AFM image, and the method was confirmed to work well. Then, parameter dependence in the protocol was discussed. Finally, we applied the method to a real experimental HS-AFM image for a flagellar protein FlhA, demonstrating its applicability. We also test the rigid-body fitting of a molecular structure to an AFM image. Our method will be a general tool for dynamic structure modeling based on HS-AFM images and is publicly available through the CafeMol software.

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Year:  2020        PMID: 31909999     DOI: 10.1021/acs.jctc.9b00991

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  6 in total

1.  Visualizing the functional 3D shape and topography of long noncoding RNAs by single-particle atomic force microscopy and in-solution hydrodynamic techniques.

Authors:  Tina Uroda; Isabel Chillón; Paolo Annibale; Jean-Marie Teulon; Ombeline Pessey; Manikandan Karuppasamy; Jean-Luc Pellequer; Marco Marcia
Journal:  Nat Protoc       Date:  2020-05-25       Impact factor: 13.491

Review 2.  Recent advances in RNA structurome.

Authors:  Bingbing Xu; Yanda Zhu; Changchang Cao; Hao Chen; Qiongli Jin; Guangnan Li; Junfeng Ma; Siwy Ling Yang; Jieyu Zhao; Jianghui Zhu; Yiliang Ding; Xianyang Fang; Yongfeng Jin; Chun Kit Kwok; Aiming Ren; Yue Wan; Zhiye Wang; Yuanchao Xue; Huakun Zhang; Qiangfeng Cliff Zhang; Yu Zhou
Journal:  Sci China Life Sci       Date:  2022-06-14       Impact factor: 10.372

3.  Inferring Conformational State of Myosin Motor in an Atomic Force Microscopy Image via Flexible Fitting Molecular Simulations.

Authors:  Sotaro Fuchigami; Shoji Takada
Journal:  Front Mol Biosci       Date:  2022-04-29

4.  Simulation atomic force microscopy for atomic reconstruction of biomolecular structures from resolution-limited experimental images.

Authors:  Romain Amyot; Arin Marchesi; Clemens M Franz; Ignacio Casuso; Holger Flechsig
Journal:  PLoS Comput Biol       Date:  2022-03-16       Impact factor: 4.475

5.  BioAFMviewer: An interactive interface for simulated AFM scanning of biomolecular structures and dynamics.

Authors:  Romain Amyot; Holger Flechsig
Journal:  PLoS Comput Biol       Date:  2020-11-18       Impact factor: 4.475

6.  Rigid-body fitting to atomic force microscopy images for inferring probe shape and biomolecular structure.

Authors:  Toru Niina; Yasuhiro Matsunaga; Shoji Takada
Journal:  PLoS Comput Biol       Date:  2021-07-20       Impact factor: 4.475

  6 in total

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