{"title":"A structural biology compatible file format for atomic force microscopy","authors":"Yining Jiang, Zhaokun Wang, Simon Scheuring","doi":"10.1038/s41467-025-56760-7","DOIUrl":null,"url":null,"abstract":"<p>Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. Unfortunately, atomic force microscopy (AFM) has so far failed to interface with these structural biology methods, despite the recent development of localization AFM (LAFM) that allows extracting high-resolution structural information from AFM data. Here, we build on LAFM and develop a pipeline that transforms AFM data into 3D-density files (.afm) that are readable by programs commonly used to visualize, analyze, and interpret structural data. We show that 3D-LAFM densities can serve as force fields to steer molecular dynamics flexible fitting (MDFF) to obtain structural models of previously unresolved states based on AFM observations in close-to-native environment. Besides, the .afm format enables direct 3D or 2D visualization and analysis of conventional AFM images. We anticipate that the file format will find wide usage and embed AFM in the repertoire of methods routinely used by the structural biology community, allowing AFM researchers to deposit data in repositories in a format that allows comparison and cross-verification with data from other techniques.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"10 1","pages":""},"PeriodicalIF":15.7000,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-56760-7","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Cryogenic electron microscopy (cryo-EM), X-ray crystallography, and nuclear magnetic resonance (NMR) contribute structural data that are interchangeable, cross-verifiable, and visualizable on common platforms, making them powerful tools for our understanding of protein structures. Unfortunately, atomic force microscopy (AFM) has so far failed to interface with these structural biology methods, despite the recent development of localization AFM (LAFM) that allows extracting high-resolution structural information from AFM data. Here, we build on LAFM and develop a pipeline that transforms AFM data into 3D-density files (.afm) that are readable by programs commonly used to visualize, analyze, and interpret structural data. We show that 3D-LAFM densities can serve as force fields to steer molecular dynamics flexible fitting (MDFF) to obtain structural models of previously unresolved states based on AFM observations in close-to-native environment. Besides, the .afm format enables direct 3D or 2D visualization and analysis of conventional AFM images. We anticipate that the file format will find wide usage and embed AFM in the repertoire of methods routinely used by the structural biology community, allowing AFM researchers to deposit data in repositories in a format that allows comparison and cross-verification with data from other techniques.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.