{"id":131116,"date":"2021-11-23T10:49:35","date_gmt":"2021-11-23T18:49:35","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2021\/11\/artificial-intelligence-powers-protein-folding-predictions"},"modified":"2021-11-23T10:49:35","modified_gmt":"2021-11-23T18:49:35","slug":"artificial-intelligence-powers-protein-folding-predictions","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2021\/11\/artificial-intelligence-powers-protein-folding-predictions","title":{"rendered":"Artificial intelligence powers protein-folding predictions"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/artificial-intelligence-powers-protein-folding-predictions3.jpg\"><\/a><\/p>\n<p>Rarely does scientific software spark such sensational headlines. \u201cOne of biology\u2019s biggest mysteries \u2018largely solved\u2019 by AI\u201d, declared the BBC. <i>Forbes<\/i> called it \u201cthe most important achievement in AI \u2014 ever\u201d. The buzz over the November 2020 debut of AlphaFold2, Google DeepMind\u2019s (AI) system for predicting the 3D structure of proteins, has only intensified since the tool was made freely available in July.<\/p>\n<p>The excitement relates to the software\u2019s potential to solve one of biology\u2019s thorniest problems \u2014 predicting the functional, folded structure of a protein molecule from its linear amino-acid sequence, right down to the position of each atom in 3D space. The underlying physicochemical rules for how proteins form their 3D structures remain too complicated for humans to parse, so this \u2018protein-folding problem\u2019 has remained unsolved for decades.<\/p>\n<p>Researchers have worked out the structures of around 160,000 proteins from all kingdoms of life. They have been using experimental techniques, such as X-ray crystallography and cryo-electron microscopy (cryo-EM), and then depositing their 3D information in the <a data-label=\"https:\/\/www.rcsb.org\/\" data-track-category=\"body text link\" data-track=\"click\" href=\"https:\/\/www.rcsb.org\/\">Protein Data Bank<\/a>. Computational biologists have made steady gains in developing software that complements these methods, and have correctly predicted the 3D shapes of some molecules from well-studied protein families.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Rarely does scientific software spark such sensational headlines. \u201cOne of biology\u2019s biggest mysteries \u2018largely solved\u2019 by AI\u201d, declared the BBC. Forbes called it \u201cthe most important achievement in AI \u2014 ever\u201d. The buzz over the November 2020 debut of AlphaFold2, Google DeepMind\u2019s (AI) system for predicting the 3D structure of proteins, has only intensified since [\u2026]<\/p>\n","protected":false},"author":578,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3,19,48,6],"tags":[],"class_list":["post-131116","post","type-post","status-publish","format-standard","hentry","category-biological","category-chemistry","category-particle-physics","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/131116","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/578"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=131116"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/131116\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=131116"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=131116"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=131116"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}