{"id":803,"date":"2013-01-15T09:25:10","date_gmt":"2013-01-15T14:25:10","guid":{"rendered":"https:\/\/engineering.jhu.edu\/magazine-archive\/?p=803"},"modified":"2017-07-28T10:08:23","modified_gmt":"2017-07-28T14:08:23","slug":"fast-lane-proteins","status":"publish","type":"post","link":"https:\/\/engineering.jhu.edu\/magazine-archive\/2013\/01\/fast-lane-proteins\/","title":{"rendered":"The Fast Lane to Proteins"},"content":{"rendered":"

In recent years, a sophisticated computer program called Rosetta\u2014a protein structure prediction program created by a consortium of laboratories that includes Johns Hopkins University\u2014 has made the task of predicting protein structure quicker and more cost-effective. This is essential to designing new proteins to fight diseases such as HIV, malaria, and cancer. But the level of programming proficiency required can be a barrier for even the most seasoned scientists, much less the typical university student.<\/p>\n

\"Jeff-Gray\"<\/a>
PROTEIN PREDICTIONS: Undergrad Nicholaus Trenton (right) and doctoral student Brian Ross (center) harnessed the power of PyRosetta, developed by Associate Professor Jeffrey Gray (left), to tackle a sticky problem. (Photo by Will Kirk)<\/figcaption><\/figure>\n

As a postdoctoral fellow, Jeffrey Gray<\/a>, an associate professor of chemical and biomolecular engineering<\/a> and F. Stuart Hodgson Faculty Scholar at the Whiting School, wrote algorithms that helped lay the foundation for Rosetta. Now he\u2019s embarked on a project to harness Rosetta\u2019s power in a more accessible programming language (Python) with PyRosetta. \u201cThe long-term goal is to make [Rosetta] part of the toolbox for the life sciences,\u201d he says.<\/p>\n

But Gray has found another important audience: students in his computational protein structure prediction and design class. He recalls, \u201cThe first time I taught [the course], I lectured. We read papers. We did things on the chalkboard. It was exciting. They learned. But it was dry. Students didn\u2019t really get a chance to get their hands on it.\u201d<\/p>\n

Today, Gray\u2019s class is built on PyRosetta<\/a>, allowing students to learn the software from the ground up and even create award-winning projects\u2014as Nicholaus Trenton, a The Fast Lane to Proteins senior majoring in chemical and biomolecular engineering, did earlier this year.<\/p>\n

Trenton teamed up with Hopkins biomedical engineering doctoral student Brian Ross on a project that used PyRosetta to attack a sticky problem: A protein complex called FKRP-rapamycin- FRB is key to the study of cell dynamics because it forms only in the presence of the immunosuppressant drug rapamycin. But the bonding of the protein complex is not easily reversible, making it impossible to track its eventual breakdown using live cell imaging methods.<\/p>\n

Trenton and Ross used PyRosetta to predict 12 mutations of the complex that might lessen the bond with rapamycin without destroying the protein completely, giving researchers a potential map of possibilities for new lab work. Their project won the 2012 Rosetta Design Group Corey Award for undergraduates and beginning graduate students who show \u201ccreativity and boldness in the field of macromolecular structure prediction and design.\u201d<\/p>\n

\u201cThis field is really new,\u201d Trenton says, of mapping proteins and predicting their behavior. \u201cPyRosetta is how everyone is going to be doing this in 10 or 15 years.\u201d<\/p>\n

Gray\u2019s efforts have received funding from the National Institutes of Health and National Science Foundation, and he is planning a series of webcasts on PyRosetta (with some student help) to meet growing demand from researchers.<\/p>\n

PyRosetta\u2019s classroom applications also ensured that Gray received support from Hopkins\u2019 Center for Educational Resources through its Technology Fellowship, which has faculty and students collaborate to develop new resources for Hopkins courses.<\/p>\n

\u201cDissemination of the work is part of the process,\u201d says Richard Shingles, a lecturer in Biology who served as the CER\u2019s curriculum design consultant liaison on PyRosetta. \u201cAs educators, we\u2019re really happy.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

A sophisticated computer program makes predicting protein structure more efficient and cost effective\u2014an important step in combating diseases such as HIV, malaria, and cancer.<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[32],"tags":[],"class_list":["post-803","post","type-post","status-publish","format-standard","hentry","category-currents","issue-winter-2013"],"acf":[],"yoast_head":"\nThe Fast Lane to Proteins - JHU Engineering Magazine<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/magazine-archive\/2013\/01\/fast-lane-proteins\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Fast Lane to Proteins - 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