Team:KAIST-Korea/Project/Modeling
From 2010.igem.org
(→Result : Figures) |
(→Result : Figures) |
||
Line 442: | Line 442: | ||
<br> | <br> | ||
<br> | <br> | ||
+ | <html> | ||
<center><img src="https://static.igem.org/mediawiki/2010/d/d8/Antibody_alignment.jpg"></center> | <center><img src="https://static.igem.org/mediawiki/2010/d/d8/Antibody_alignment.jpg"></center> | ||
+ | </html> | ||
+ | <br> | ||
+ | <br> | ||
===Result Analysis=== | ===Result Analysis=== | ||
The table above shows the result of alignment of 65 single chain antibody for control group and 1 single chain antibody for our real experiment (16A1). Higher core residue and Raw score and lower core RMSD and p-value means more similar. 16A1 antibody shows 26th highest in core residue, 2nd lowest in core RMSD, 13th highest Raw score and 13th lowest p-value. These result means that our 16A1 antibody has higher similarity than average antibodies. | The table above shows the result of alignment of 65 single chain antibody for control group and 1 single chain antibody for our real experiment (16A1). Higher core residue and Raw score and lower core RMSD and p-value means more similar. 16A1 antibody shows 26th highest in core residue, 2nd lowest in core RMSD, 13th highest Raw score and 13th lowest p-value. These result means that our 16A1 antibody has higher similarity than average antibodies. |
Revision as of 09:37, 8 August 2010
Modeling
Single chain antibody structural alignmentProtocolThere are four steps to compare structure of single chain antibody and FGF binding domain of FGFR. First step is taking variable region sequences of antibodies. Next step is combining these variable region sequences with linker sequence to make single chain antibody sequence. Third step is predicting the structure of single chain antibody with structure prediction program like modeler. Final step is to structural align these structures of antibodies with structure of FGF binding domain of FGFR(PDB ID : 1EVT).
Data sourceSingle chain antibody is the combination of variable regions of known antibodies with linker sequence which can bind to the antigens. We need to know the VL and VH sequences to make single chain antibody. The source of these antibody sequences are NCBI, Uniprot and RCSB PDB. NCBI and Uniprot provide the single chain sequence of variable regions (VL and VH) and antigen binding fragments (Fab). RCSB provide the structure of the complexes of antigenbinding fragment which binds to its antigens. But we only need the sequence of variable region. So we get the last 120~150 reside and assume them as the variable region. And data from RCSB contain not only sequence of antibody, but also antigens. S we filter them based on label of files.to get heavy chains and light chains of antibody.
Single chain antibody synthesisWe combine the antibody variable region sequences in order of VH-linker-VL to make single chain antibody sequence. The sequence of linker is GGGGSGGGGS
Structure PredictionWe used the Modeller program to predict the structure of single chain antibody from its sequence. Modeller predict 3D structure of protein with structure of know similar proteins based on homology model. Input file is the sequence of single chain antibody with fasta format and output file is the structure of single chain antibody with pdb format.
Structure AlignmentIn this step, we check the structural similarity between single chain antibodies and FGF binding domain to align the structure of single chain antibody with FGF binding domain of FGFR. The structure of FGF binding domain of FGFR is provided by RCSB PDB(PDB ID : 1EVT) We used Matt structural alignment program to do this job. Matt do the structural alignment which minimize the distance between α-carbon chain of two proteins based on the common structure (α helix). Input file is the structure of single chain antibody with pdb format and output file is the text file which contain the number of amino acids which compose shared structure (Core residue), average distance between alpha carbon chains of two proteins (Core RMSD), the score of similarity which is calculated by Matt(Raw score) and the probability that this similarity is just the product of random(p-value) and pdb files which contain the alignment result of single chain antibody with FGF binding domain of FGFR.
Result : Table
Result : FiguresUsing arranged pdb files and protein 3D structure drawing program - PyMOL, again, we predict structural similarlity between the structure of FGF binding domain and single chain antibodies associated with the table. In order to show the structures clearly, we control the shape setting 'cartoon' and 'chain'. Cyan Color is the structure of FGF binding domain and Green Color is the comparative antibodies. In the result, we can easily see all antibodies' structure are very similar completely or symmetrically.
Result AnalysisThe table above shows the result of alignment of 65 single chain antibody for control group and 1 single chain antibody for our real experiment (16A1). Higher core residue and Raw score and lower core RMSD and p-value means more similar. 16A1 antibody shows 26th highest in core residue, 2nd lowest in core RMSD, 13th highest Raw score and 13th lowest p-value. These result means that our 16A1 antibody has higher similarity than average antibodies. |