ArticleStructure (London, England : 1993)2012
Computational reconstruction of multidomain proteins using atomic force microscopy data.
Article in Structure (London, England : 1993), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Decoding full-length factor VIII through the structural and functional lens of its B domain.Blood vessels, thrombosis & hemostasis · 2026Article
- AFM-Fold: Rapid reconstruction of protein conformations from AFM images.Biophysical journal · 2026Article
- Reconstruction of the Flexible IgM Fc Core Using Atomic Force Microscopy Topography and the AFM-Assembly Pipeline.Journal of molecular recognition : JMR · 2026Article
- Estimating Protein Conformational States from High-Speed AFM Images with Molecular Dynamics and Deep Learning.Journal of chemical information and modeling · 2026Article
- Deciphering conformational dynamics in AFM data using fast nonlinear NMA and FFT-based search with AFMFit.Communications biology · 2025Article
- Modeling Conformational Transitions of Biomolecules from Atomic Force Microscopy Images using Normal Mode Analysis.The journal of physical chemistry. B · 2024Article
- BioAFMviewer software for simulation atomic force microscopy of molecular structures and conformational dynamics.Journal of structural biology: X · 2023Review
- Development of hidden Markov modeling method for molecular orientations and structure estimation from high-speed atomic force microscopy time-series images.PLoS computational biology · 2022Article
- Recent advances in RNA structurome.Science China. Life sciences · 2022Review
- Inferring Conformational State of Myosin Motor in an Atomic Force Microscopy ImageFrontiers in molecular biosciences · 2022Article
- Rigid-body fitting to atomic force microscopy images for inferring probe shape and biomolecular structure.PLoS computational biology · 2021Article
- Visualizing the functional 3D shape and topography of long noncoding RNAs by single-particle atomic force microscopy and in-solution hydrodynamic techniques.Nature protocols · 2020Article
- Visualizing the Path of DNA through Proteins Using DREEM Imaging.Molecular cell · 2016Article
- DockAFM: benchmarking protein structures by docking under AFM topographs.Bioinformatics (Oxford, England) · 2013Article
- DOT2: Macromolecular docking with improved biophysical models.Journal of computational chemistry · 2013Article
- Adepth: New Representation and its implications for atomic depths of macromolecules.Nucleic acids research · 2013Article
- A method for integrative structure determination of protein-protein complexes.Bioinformatics (Oxford, England) · 2012Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Classical structural biology techniques face a great challenge to determine the structure at the atomic level of large and flexible macromolecules. We present a novel methodology that combines high-resolution AFM topographic images with atomic coordinates of proteins to assemble very large macromolecules or particles. Our method uses a two-step protocol: atomic coordinates of individual domains are docked beneath the molecular surface of the large macromolecule, and then each domain is assembled using a combinatorial search. The protocol was validated on three test cases: a simulated system of antibody structures; and two experimentally based test cases: Tobacco mosaic virus, a rod-shaped virus; and Aquaporin Z, a bacterial membrane protein. We have shown that AFM-intermediate resolution topography and partial surface data are useful constraints for building macromolecular assemblies. The protocol is applicable to multicomponent structures connected in the polypeptide chain or as disjoint molecules. The approach effectively increases the resolution of AFM beyond topographical information down to atomic-detail structures.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.