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[[Image:Rossetta_match_and_Foldit.png |500px | center]] | [[Image:Rossetta_match_and_Foldit.png |500px | center]] | ||
| - | The main idea behind using these two programs evolves from the recognition that streptavidin contains a special active site which allows it to bind biotin. This active site can be described using the amino acids forming it and their position relative to biotin. Once a description of the active site has been made, it is feed into Rosetta Match which scans a large library of protein | + | The main idea behind using these two programs evolves from the recognition that streptavidin contains a special active site which allows it to bind biotin. This active site can be described using the amino acids forming it and their position relative to biotin. Once a description of the active site has been made, it is feed into Rosetta Match which scans a large library of protein scaffolds. If it finds a scaffold in which your active site will fit, it returns the scaffold along with the position of the active site. After the preliminary matches are done by Rosetta Match, the matches are placed into Fold-It, which provides an easy way to optimize the rest of the surrounding protein. |
====The Trench Work==== | ====The Trench Work==== | ||
| - | The first step in designing our protein was looking at the native biotin-streptavidin interaction and taking measurements between key amino acids and the biotin molecule. From here we entered the constraints into Rosetta where it matched our measurements into proteins from a protein scaffold library. This produced a large set of scaffolds with different ways each one could be used to bind biotin. These scaffolds | + | The first step in designing our protein was looking at the native biotin-streptavidin interaction and taking measurements between key amino acids and the biotin molecule, ie describing the active site. From here we entered the active site constraints into Rosetta Match, where it matched our measurements into proteins from a protein scaffold library. This produced a large set of scaffolds with different ways each one could be used to bind biotin. These scaffolds were screened manually, and the scaffolds that look the most promising were placed into Fold-It. Once in Fold-It, the public had access to our protein design and could tweak and tune the protein to optimize its interaction with biotin. This allows anyone (with or without prior protein knowledge) to optimize our protein scaffold. |
As can be seen below Fold-It uses an easily learned user interface and uses a score board to show the players who is the best folder. | As can be seen below Fold-It uses an easily learned user interface and uses a score board to show the players who is the best folder. | ||
Revision as of 22:16, 20 October 2009
[http://www.fold.it/ Fold-It]
Problem
Streptavidin in its native form exists as a homotetramer, where adjacent subunits interact allowing for a strong interaction with biotin. This interaction is strong (Kd = 1.5E-15 M at pH 5.0) and can withstand most strong denaturing agents1. However when in its monomeric form, streptavidin does not maintain this strong interaction and its usefulness as a strong binder diminishes. For our system we needed a protein that could: be easily displayed on the surface of the cell, specifically bind a ligand, and release this ligand in the presence of biotin. The ability to display a protein on the cell surface is trivial, however there is difficulty in trying to get a protein to be functional on the surface of the cell. In the case of streptavidin the ability of the protein to form tetramers on the cell surface seems to be hindered, due to the poor ability of cells displaying streptavidin to bind biotinylated fluorophore (observed above). From this issue the idea of using a monomeric protein to bind biotin arose.
The Idea
There are engineered forms of streptavidin that have mutations preventing the formation of tetrameric structures. However as mentioned before, as a monomer streptavidin has a weaker affinity to biotin than would be desired. Instead of screening proteins from the literature for ability to bind biotin our group approached the Baker lab at our university. After mentioning our problem, it was recommended that we design a biotin binding protein using the [http://boinc.bakerlab.org/rosetta/ Rosetta Match] software they developed. Rosetta in conjunction with [http://www.folt.it Fold-It] (also developed at the University of Washington) would allow use to design and optimize proteins for binding biotin.
The main idea behind using these two programs evolves from the recognition that streptavidin contains a special active site which allows it to bind biotin. This active site can be described using the amino acids forming it and their position relative to biotin. Once a description of the active site has been made, it is feed into Rosetta Match which scans a large library of protein scaffolds. If it finds a scaffold in which your active site will fit, it returns the scaffold along with the position of the active site. After the preliminary matches are done by Rosetta Match, the matches are placed into Fold-It, which provides an easy way to optimize the rest of the surrounding protein.
The Trench Work
The first step in designing our protein was looking at the native biotin-streptavidin interaction and taking measurements between key amino acids and the biotin molecule, ie describing the active site. From here we entered the active site constraints into Rosetta Match, where it matched our measurements into proteins from a protein scaffold library. This produced a large set of scaffolds with different ways each one could be used to bind biotin. These scaffolds were screened manually, and the scaffolds that look the most promising were placed into Fold-It. Once in Fold-It, the public had access to our protein design and could tweak and tune the protein to optimize its interaction with biotin. This allows anyone (with or without prior protein knowledge) to optimize our protein scaffold.
As can be seen below Fold-It uses an easily learned user interface and uses a score board to show the players who is the best folder.
| Here we see a video of Fold-It, showing one of our biotin puzzles "Hold Me Tightly". The protein is represented as a cartoon model, showing off its secondary structure as well as key amino acid groups. Steric clashes of the amino acid side chains show up as red balls and can also be observed in the video. These steric clashs can be removed with the Shake Function. The Shake function in Fold-It performs coarse sampling of the amino acid conformations, looking for a global-minima. |
| The function we see here is the Mutate function. This allows the user to sample many amino acids at a particular site, or the whole protein. Mutate looks for global-minima while sampling amino acids. As is seen here Alanine is mutated to Asparagine. The blue and white striped band indicates that a hydrogen bond has been formed, which is a favorable interaction between two polar residues. |
| Another nice feature of Fold-It is the ability to select a sphere of amino acids around your ligand, and optimize these amino acids based off of a fine sampling of conformations. Here we see the amino acids surrounding the ligand being selected and having the Wiggle function performed on them. The Wiggle function in Fold-It allows the user to fine tune the protein structure. Finding a local-minima for the amino acid conformations. |
This accessible format has allowed over 100,000 users to help design proteins. Currently we have published protein puzzles on Fold-It and are screening though the top scoring designs. An undergrad in our group will be active throughout the next year testing the designs and looking for biotin binding proteins.
[http://www.fold.it/ Try Fold-It!]
References
- [http://www.ncbi.nlm.nih.gov/pubmed/18287646?ordinalpos=4&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum Haugland RP, "Coupling of antibodies with biotin".]
