With the completion of the Human Genome Project, we are now capable of predicting what the amino acid sequences of different proteins in the human body will be. However, while we know the order of the amino acids, proteins do not remain in a two-dimensional shapes inside the human body. They "fold" into different three-dimensional shapes for various proteins in order to serve their functions inside the human body. A protein with a distinctive amino acid chain does not simply fold is a random manner, but usually in a specific configuration. Since the forces that act on a protein depend on what the particular amino acid sequence of a protein is, a specific protein will usually fold in the same manner. Due to the complexity of the forces acting upon amino acid sequences large enough to form a protein, it is extremely difficult to predict how the protein will fold, but this knowledge is vital for determining how the protein functions when performing medical research.
The Rosetta@home project utilizes a unique software algorithm in order to predict what the shape of a protein after folding will be. Because of the difficulty of accurately predicting the shape of a protein, very large numbers of simulations need to be made in order to produce the right one. After simulations creating protein structure predictions are produced on individual computers, they are uploaded to a central server where another piece of software determines which of the protein structures uploaded is the most accurate.
The success of this distributed computed project would mean that researchers could quickly and accurately predict the structures of different proteins in order to develop cures for a wide variety of diseases. In the near future, the Baker Laboratory is specifically looking at applying the results of this distributed computing project towards potentially developing treatments for malaria, anthrax, HIV, Alzheimer's disease, and cancer among other applications.
If you would like to assist in this scientifically worthy project while burnishing the reputation of Ars Technica while doing so, you can start by signing up for the project and automatically joining Team Vino Rose in the process. You should then download the BOINC software if you do not already have it, install and start the program, select the "attach to new project" option from the BOINC manager, and then enter the project url (http://boinc.bakerlab.org/rosetta/) along with the the account id you received in the e-mail you received after signing up for the project in order to complete the process. Clients are available for Windows, Linux, and Mac OS X. In case you have further questions or would like additional information about the project, be sure to read the team thread in the Ars Distributed Computing Arcana.
Right now, Team Vino Rose is languishing in 32nd place with 180,426.14 credits and a recent average of 6,979.46, but with an influx of new members, we have a shot at quickly moving up into the top twenty.
Top 5 Team Vino Rose producers
Teams wearing the bullseye
- The Clangers 211,614.78 credits
- Picard 207,097
- Nordlichter 202,128.20
Teams in the rearview mirror
- Seti@Netherlands 175,376.33 credits
- BOINC@AUSTRALIA 156,980.22
- Satellites 142,939.54
Thanks to aegion for putting together this edition of DC.Ars!