{"title":"Expanding insights from in situ cryo-EM","authors":"Joshua Hutchings , Elizabeth Villa","doi":"10.1016/j.sbi.2024.102885","DOIUrl":null,"url":null,"abstract":"<div><p>The combination of cryo-electron tomography and subtomogram analysis affords 3D high-resolution views of biological macromolecules in their native cellular environment, or <em>in situ</em>. Streamlined methods for acquiring and processing these data are advancing attainable resolutions into the realm of drug discovery. Yet regardless of resolution, structure prediction driven by artificial intelligence (AI) combined with subtomogram analysis is becoming powerful in understanding macromolecular assemblies. Automated and AI-assisted data mining is increasingly necessary to cope with the growing wealth of tomography data and to maximize the information obtained from them. Leveraging developments from AI and single-particle analysis could be essential in fulfilling the potential of <em>in situ</em> cryo-EM. Here, we highlight new developments for <em>in situ</em> cryo-EM and the emerging potential for AI in this process.</p></div>","PeriodicalId":10887,"journal":{"name":"Current opinion in structural biology","volume":"88 ","pages":"Article 102885"},"PeriodicalIF":6.1000,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current opinion in structural biology","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959440X2400112X","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The combination of cryo-electron tomography and subtomogram analysis affords 3D high-resolution views of biological macromolecules in their native cellular environment, or in situ. Streamlined methods for acquiring and processing these data are advancing attainable resolutions into the realm of drug discovery. Yet regardless of resolution, structure prediction driven by artificial intelligence (AI) combined with subtomogram analysis is becoming powerful in understanding macromolecular assemblies. Automated and AI-assisted data mining is increasingly necessary to cope with the growing wealth of tomography data and to maximize the information obtained from them. Leveraging developments from AI and single-particle analysis could be essential in fulfilling the potential of in situ cryo-EM. Here, we highlight new developments for in situ cryo-EM and the emerging potential for AI in this process.
期刊介绍:
Current Opinion in Structural Biology (COSB) aims to stimulate scientifically grounded, interdisciplinary, multi-scale debate and exchange of ideas. It contains polished, concise and timely reviews and opinions, with particular emphasis on those articles published in the past two years. In addition to describing recent trends, the authors are encouraged to give their subjective opinion of the topics discussed.
In COSB, we help the reader by providing in a systematic manner:
1. The views of experts on current advances in their field in a clear and readable form.
2. Evaluations of the most interesting papers, annotated by experts, from the great wealth of original publications.
[...]
The subject of Structural Biology is divided into twelve themed sections, each of which is reviewed once a year. Each issue contains two sections, and the amount of space devoted to each section is related to its importance.
-Folding and Binding-
Nucleic acids and their protein complexes-
Macromolecular Machines-
Theory and Simulation-
Sequences and Topology-
New constructs and expression of proteins-
Membranes-
Engineering and Design-
Carbohydrate-protein interactions and glycosylation-
Biophysical and molecular biological methods-
Multi-protein assemblies in signalling-
Catalysis and Regulation