Team:Brown/Project Histamine Sensor
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The DNA for the top design was synthesized by GeneArt AG. We are in the process of testing the protein’s ability to bind histamine. | The DNA for the top design was synthesized by GeneArt AG. We are in the process of testing the protein’s ability to bind histamine. | ||
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+ | <p><img src="https://static.igem.org/mediawiki/2009/f/f6/MRBP.png" width="392" height="254"> <img src="https://static.igem.org/mediawiki/2009/2/2d/Ligandbindingprotein.png" width="371" height="252"></p> | ||
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In normal E. coli cells, ribose binding to RBP forms a ribose-RBP complex that interacts with the periplasmic domain of Trg, which in turn activates an intracellular cascade that induces chemotaxis. | In normal E. coli cells, ribose binding to RBP forms a ribose-RBP complex that interacts with the periplasmic domain of Trg, which in turn activates an intracellular cascade that induces chemotaxis. |
Revision as of 23:02, 21 October 2009
Histamine Sensor
During the allergic response, the concentration of histamine in the extracellular fluid of the nasal cavity increases. To initiate a response; therefore, a histamine sensor is necessary.
Because natural histamine receptors exist only in eukaryotic cells as G-coupled protein receptors, they are unusable for our prokaryotic system. Therefore we have set out to engineer our own receptor. This novel receptor will sense extracellular concentrations of histamine and initiate an intracellular cascade, signaling cells to respond appropriately to the increase in histamine concentration.
To engineer a novel histamine receptor, we are mutating two existing prokaryotic chemoreceptors so that they bind histamine rather than their wild type ligands.
Re-engineering Chemoreceptor #1: Ribose Binding Protein
We modified ribose binding protein (RBP), which normally binds ribose in the periplasmic space of Escherichia coli, to bind histamine. Our computational approach to accomplish this task was modeled after that taken in Looger et al., "Computational design of receptor and sensor proteins with novel functions" (2003). Using Rosetta macromolecular modeling software, we modified the program's existing Enzyme Design Function (such as that used in Röthlisberger et al "Kemp elimination catalysts by computational enzyme design" (2008)) to enable the re-design of RBP, a non-enzymatic protein. The successful modification of RBP would result in its ability to bind histamine.
How we designed the protein:
AR-Need pictures!! Throw in pic of RBP and ribose. Then have an ala mutated pocket. Then have a pic of histamine in the naked pocket and finally one of the top choices with histamine in the pocket. Use the same angle and cutaway of the pocket in every case.
1) Took the PDB file for the crystal structure of RBP cocrystallized with ribose (2DRI). Removed water molecules and added missing hydrogens.
2) Used UCSF Chimera to geometrically search for all van der Waals interactions between ribose and RBP in the crystal structure. Identified the amino acids responsible for these interactions as those most likely present in the ligand binding pocket of RBP.
3) Used UCSF Chimera to mutate all the identified residues in RBP to alanine (which has neutral chemical properties, and almost no side chains), thereby effectively creating a "blank" version of RBP, one that has no specific binding pocket for any ligand (removing its binding affinity for ribose).
4) Used Rosetta's Ligand Docking mode on a cluster of 100 servers to replace ribose in the alanine-mutated RBP (polyala RBP) with a 3D structure for histamine. AR-throw in a link to the computer cluster at Brown
5) To isolate histamine's lowest energy conformation in RBP, used Monte Carlo minimization to find the relative orientations of both components that minimize steric contacts while still keeping histamine roughly within the original ligand binding pocket. Generated 10000 PDB files of histamine docked to the polyala RBP.
6) Sorted the 10000 docked PDB files by their interface energies between ligand and protein. Selected the top 2500. AR-put in part of Excel spreadsheet with all the sortable criteria, just show top 10 or whatever...
7) Took the top 2500 and input them into the Rosetta Enzyme Design mode. Specified the residues mutated to alanine as those to re-design. Used Rosetta Design’s probabilistic simulated annealing algorithm to find the particular residues that minimize total energy between protein and ligand (minimized energy indicates a stable state, favoring binding). Final designs are not guaranteed to yield the lowest possible energy conformations. However, by doing thousands of designs in parallel, we increased the likelihood of isolating mutations that result in histamine binding.
8) Sorted through the output designs using several criteria: predicted interface energies between the protein and histamine, amount of hydrogen bonding between the protein and histamine (H-bonds are very good for ligand binding), and predicted folding ability of protein.
The DNA for the top design was synthesized by GeneArt AG. We are in the process of testing the protein’s ability to bind histamine.