Here are some links related to Rosetta:

• Baker Lab
  
• David Baker Profile
  
• HHMI Research News
  
• Rosetta Explained by Grid.org
  
• Rosetta Commons
  
• Rosetta Wiki
  

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Also

Rosetta@home page at Wikipedia

which includes many hyperlinks to related pages (protein folding, drug design etc)

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Best UFO Resources
Wikipedia R@h
How-To: Join Distributed Computing projects that benefit humanity

There are a number of resources available to to Rosetta@home users which provide you with up to date project information.

Please explore our website freely, but be sure to visit the following links as they will provide a detailed understanding of Rosetta@home and make your time here more enjoyable.

1) Dr. David Bakers Rosetta@home Journal, a running log of thoughts and commentary from the project Chief investigator.*
2) Discussion of Rosetta@home Journal (2), where users can chat with Dr. Baker about his log entries and other science related concepts.
3) Rosetta@home Active Work Unit(s) Log, provides descriptions of the Work Units and proteins currently being examined by the project on your computer(s).*
4) Discussion- Proteins and Work Units, where users can discuss the work units described in the work unit log.
5) Rosetta Application Version Release Log, Announcements of new software versions and updates.*
6) Discussion of Release log entries, Discussion and additional information on entries made to the release log.
7) Project Announcement Thread, Where the project provides announcements to the user community that may require user action.*
8) Improvements to Rosetta@home based on user feedback, a place for users to make and discuss general suggestions to the project team.
9) Discuss Rosetta Application Errors and Fixes (all Versions), a place to discuss application specific issues.
10) Rosetta@home FAQ, a collection of "Frequently Asked Questions" with answers about running Rosetta@home on your computer.*
11) Team Thread, a thread where teams can post contact information and recruit new members.
12) Personal Milestones, a place for users to report individual milestones in credit accumulations and competitions.
13) Moderators Contact Point, a place where users can contact forum Moderators for help or to report problems.
14) A letter to Rosetta@home users, a letter prepared by Rosetta@home users inviting increased participation and explaining why additional help is important.
15) Links for REPORTING PROBLEMS, places where users can report problems in different versions of Rosetta.
16) RALPH Home page, the doorway to the Rosetta@home ALPHa test project, where new concepts in protein modeling are tested prior to production use.**
17) A video presentation by Dr. David Baker, this video explains the nature of Rosetta work and the problems facing computational protein prediction.
18) WIKIpedia articles about Rosetta@Home, Many articles on rosetta research.

Retired threads

1) Discussion of Rosetta@home Journal Part (1), History thread of discussions about Dr. Baker's log entries and other science related concepts.
2) Moderators Contact Point - Archive, the history of user contacts with forum Moderators for help or to report problems.

* PLEASE NOTE: Threads listed above with an "*" are reserved for posting by project team members only. All other threads are open to topical user posts.
** NOTE: RALPH@home is NOT a production environment. Software testing is not for everyone. Please read the information provided here and here BEFORE attaching.

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Moderator9
ROSETTA@home FAQ
Moderator Contact

Here is an interesting article that relates to Rosetta:

1,000 Genomes Project: Expanding the Map of Human Genetics

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http://www.sciencedaily.com/releases/2011/05/110501183825.htm

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The Economist
Molecular biology
How to determine a protein’s shape

The Economist
Molecular biology
How to determine a protein’s shape

Very, very interesting. And it just so happens that the next generation of GPU chips will be good at "deep learning". Does this mean that there is a GPU version of Rosetta in our future?

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Science: Software-designed miniproteins could create new class of drugs

Small versions of antibodies bind to virtually any target protein

24 MAR 2022
BY ROBERT F. SERVICE

Scientists have built their own “mini-antibodies” using software that predicts how proteins fold. The advance could enable development of a new class of drugs to fight everything from cancer to COVID-19.

“It’s pretty amazing stuff,” says Steven Mayo, a chemist at the California Institute of Technology who wasn’t involved in the study. The software should also allow researchers to design diagnostic probes that could detect diseases early in the body, adds Tanja Kortemme, a bioengineer at the University of California, San Francisco, also not involved. “It opens up many possibilities.”

Antibodies excel at binding to proteins, such as those on invading microbes, so pharmaceutical companies use them as drugs to battle infections and cancer. But because antibodies are large proteins, they are costly to make and often unstable. Researchers have been working to make miniature versions of these binders that are cheaper and often more stable. But designing them to bind specific targets has been difficult.

When antibodies bind to a target, it’s like a rock climber trying to scale a sheer cliff face, explains David Baker, a computational structural biologist at the University of Washington (UW), Seattle: The surface is mostly smooth with few hand- and footholds. Antibodies are large. So, they can snag many weak holds simultaneously, which collectively allows them to hold firm to a target.

Miniproteins have fewer options. Researchers have tried to overcome this deficiency by identifying hot spots on proteins—strong handholds—and then build miniproteins around that hold. That only works for a handful of targets studied enough that their hot spots have been scoped out, however.

To get around this problem, Baker and his colleagues turned to Rosetta, software they designed to predict protein structures based on their amino acid sequence. To create a map of potential handholds, the team instructed the program to first calculate how tightly specific amino acids would bind to different spots across the surface of a target protein. The software then looked for clusters of neighboring handholds and determined how to build a stable miniprotein that would grab onto as many holds in a cluster as possible. The researchers used the software to construct tens of thousands of virtual minibinders and compared their calculated binding.

Baker and his colleagues tested their strategy on 12 target proteins, including proteins involved in cancer and proteins on the surfaces of viruses such as influenza and SARS-CoV-2. Yeast turned these virtual binders into actual miniproteins. Further modification enabled the team to make these proteins even more sticky. For each of their 12 targets, the researchers wound up with miniproteins that bound as strongly as, if not stronger than, most antibodies do, they report today in Nature.

Because many of the targets play roles in disease, the minibinders show potential as medicines, the researchers say. In July 2021, for example, Baker and his colleagues reported an early example of their method in a preprint. It produced miniproteins that bind to and neutralize the spike protein of SARS-CoV-2, the virus that causes COVID-19. The compounds were then shown to protect genetically engineered mice that express a human version of the protein that the virus latches onto. Clinical trials may begin this year, Baker says.

“We can design proteins to bind to any target,” says co-author Longxing Cao, a postdoc at UW. So miniproteins could not only block disease proteins, he says, but also direct toxic payloads to cancerous tissues, or ferry light-emitting or radioactive diagnostic molecules to cancer or other disease cells, to indicate the progress of treatment.

Still, “There is room for improvement,” Baker says. Despite Rosetta’s predictions, many miniproteins didn’t stick to their target. But the software will continue to make adjustments, he says, so its designs are sure to improve over time.

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Nature article about Alphafold and, to a lesser extent, Rosettafold:
https://www.nature.com/articles/d41586-022-00997-5

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The current few Rosetta tasks in the latest batch are named RosettaVS, so I did a search to see if that signified anything and found this article on Nature from early September 2024

An artificial intelligence accelerated virtual screening platform for drug discovery

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