David A Agard, Gregory R Bowman, William DeGrado, Nikolay V Dokholyan, Huan-Xiang Zhou
{"title":"蛋白质结构预测问题的最终解决:关键创新和下一个前沿。","authors":"David A Agard, Gregory R Bowman, William DeGrado, Nikolay V Dokholyan, Huan-Xiang Zhou","doi":"10.12703/r-01-0000020","DOIUrl":null,"url":null,"abstract":"<p><p>The protein structure prediction problem is solved, at last, thanks in large part to the use of artificial intelligence. The structures predicted by AlphaFold and RoseTTAFold are becoming the requisite starting point for many protein scientists. New frontiers, such as the conformational sampling of intrinsically disordered proteins, are emerging.</p>","PeriodicalId":73016,"journal":{"name":"Faculty reviews","volume":"11 ","pages":"38"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815721/pdf/facrev-11-38.pdf","citationCount":"0","resultStr":"{\"title\":\"Solution of the protein structure prediction problem at last: crucial innovations and next frontiers.\",\"authors\":\"David A Agard, Gregory R Bowman, William DeGrado, Nikolay V Dokholyan, Huan-Xiang Zhou\",\"doi\":\"10.12703/r-01-0000020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The protein structure prediction problem is solved, at last, thanks in large part to the use of artificial intelligence. The structures predicted by AlphaFold and RoseTTAFold are becoming the requisite starting point for many protein scientists. New frontiers, such as the conformational sampling of intrinsically disordered proteins, are emerging.</p>\",\"PeriodicalId\":73016,\"journal\":{\"name\":\"Faculty reviews\",\"volume\":\"11 \",\"pages\":\"38\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815721/pdf/facrev-11-38.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Faculty reviews\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12703/r-01-0000020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Faculty reviews","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12703/r-01-0000020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solution of the protein structure prediction problem at last: crucial innovations and next frontiers.
The protein structure prediction problem is solved, at last, thanks in large part to the use of artificial intelligence. The structures predicted by AlphaFold and RoseTTAFold are becoming the requisite starting point for many protein scientists. New frontiers, such as the conformational sampling of intrinsically disordered proteins, are emerging.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
