{"id":86194,"date":"2020-09-29T12:59:39","date_gmt":"2020-09-29T17:59:39","guid":{"rendered":"https:\/\/uwm.edu\/news\/?p=86194"},"modified":"2020-09-29T12:59:39","modified_gmt":"2020-09-29T17:59:39","slug":"new-technique-makes-movies-of-molecular-machines-at-work","status":"publish","type":"post","link":"https:\/\/uwm.edu\/news\/new-technique-makes-movies-of-molecular-machines-at-work\/","title":{"rendered":"New technique makes movies of molecular machines at work"},"content":{"rendered":"

If you could see biomolecules, such as proteins, in motion, they would provide clues about the way they carry out all the functions in the human body \u2014 and how those functions could be altered with drugs.<\/p>\n

Researchers, including four at 51ÁÔÆæ, have developed a method of making three-dimensional \u201cmolecular movies,\u201d using an imaging technique called single-particle cryo-electron microscopy (cryo-EM). In this technique, snapshots of tens and often hundreds of thousands of molecules trapped in a thin layer of ice are collected with an electron microscope and then combined into sharper, three-dimensional images by a computer. These images, including those of the COVID-19 virus, are so sharp that individual atoms are just about visible.<\/p>\n

In 2017, Columbia University\u2019s Joachim Frank shared the Nobel Prize in Chemistry<\/a> for developing cryo-EM. But despite its ability to image fine detail, it could capture only still images of biomolecules.<\/p>\n

Now, the 51ÁÔÆæ team, together with collaborators, has developed a technique that extracts even more information hidden in the flood of data from the electron microscope. It has allowed the researchers to compile movies of biomolecules performing their function by combining information from 800,000 snapshots captured by the electron microscope. Partners include teams led by Frank at Columbia, Amedee de George at the City University of New York, and Abhishek\u00a0Singharoy at Arizona State University.<\/p>\n

The new strategy, which involves mathematical techniques of geometric machine learning, was pioneered by Abbas Ourmazd, distinguished professor of physics at 51ÁÔÆæ, and collaborators, particularly physics Professor Peter Schwander.<\/p>\n

The results were published in the current issue of the journal\u00a0Nature Communications<\/a>. The paper\u2019s joint first authors are 51ÁÔÆæ scientists Ali Dashti (now at Amazon) and Ghoncheh Mashayekhi.<\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers, including four at 51ÁÔÆæ, have developed a method of making three-dimensional \u201cmolecular movies,\u201d using an imaging technique called single-particle cryo-electron microscopy.<\/p>\n","protected":false},"author":836,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","uwm_wg_additional_authors":[]},"categories":[174,200],"tags":[],"section":[140,139],"display_categories":[],"related-coverage":[282],"uwmnews-feed":[158,161],"class_list":["post-86194","post","type-post","status-publish","format-standard","hentry","category-news","category-news-in-brief","section-science","section-science-technology","related-coverage-physics","uwmnews-feed-letters-science","uwmnews-feed-hard-science"],"yoast_head":"\nNew technique makes movies of molecular machines at work<\/title>\n<meta name=\"description\" content=\"Researchers, including four at 51ÁÔÆæ, have developed a 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