Difference between revisions of "Part:BBa K3396000"
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+ | <table style="width:65%"> | ||
+ | <table> | ||
+ | <tr> | ||
+ | <th>cbeta_deviations</th> | ||
+ | <th>clashscore</th> | ||
+ | <th>molprobity</th> | ||
+ | <th>ramachandran_favored</th> | ||
+ | <th>ramachandran_outliers</th> | ||
+ | <th>Qmean_4</th> | ||
+ | <th>Qmean_6</th> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>0</td> | ||
+ | <td>182.87</td> | ||
+ | <td>2.72</td> | ||
+ | <td>98.25</td> | ||
+ | <td>0.7</td> | ||
+ | <td>0.75816</td> | ||
+ | <td>1.025826</td> | ||
+ | </tr> | ||
+ | </table> | ||
+ | </body> | ||
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Table 1.: QA scores by SWISS model tool of GST-Docs structure. | Table 1.: QA scores by SWISS model tool of GST-Docs structure. | ||
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+ | <table> | ||
+ | <tr> | ||
+ | <th>cbeta_deviations</th> | ||
+ | <th>clashscore</th> | ||
+ | <th>molprobity</th> | ||
+ | <th>ramachandran_favored</th> | ||
+ | <th>ramachandran_outliers</th> | ||
+ | <th>Qmean_4</th> | ||
+ | <th>Qmean_6</th> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>1</td> | ||
+ | <td>2.53</td> | ||
+ | <td>1.69</td> | ||
+ | <td>85.33</td> | ||
+ | <td>1.33</td> | ||
+ | <td>-1.68577</td> | ||
+ | <td>-1.79068</td> | ||
+ | </tr> | ||
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Table 2.: QA scores by SWISS model tool of His-Docs structure. | Table 2.: QA scores by SWISS model tool of His-Docs structure. |
Revision as of 07:40, 12 October 2022
DocS
The Coch2 module binds DocS (BBa_K3396000) modules constitutively.
Usage and Biology
The DocS[1] module comes from The C. thermocellum scaffoldin and it could recognize and bind tightly to complementary Coh2 modules. The Coh2–DocS pair represents the interaction between two complementary families of protein modules that exhibit divergent specificities and affinities, ranging from one of the highest known affinity constants between two proteins to relatively low-affinity interactions.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000COMPATIBLE WITH RFC[1000]
Contribution by CU_Egypt team 2022
From literature, we found that the yield of expression of Docs is very low so we decided to test it with different tags GST and His to see their effects on its stability and expression yield. Also, we optimized the sequence to be expressed in E-coli. in addition, there is no characterization for Docs on the registry so we expressed and characterized it by different methods such as Agarose gel electrophoresis, SDS PAGE, transformation efficiency, affinity chromatography, and Bradford assay. it's proved by wet lab results that the expression yield of Docs has raised with tagging by GST.
Dry Lab Characterization
1.1. Modeling
Docs has been tagged with GST and His for purification and increasing the yield by the GST tag. then the model designed by several tools to get the best model.
GST-Docs
Figure 1.: Predicted 3D structure of GST-Docs designed by RosettaFold tool displayed by Pymol.
cbeta_deviations | clashscore | molprobity | ramachandran_favored | ramachandran_outliers | Qmean_4 | Qmean_6 |
---|---|---|---|---|---|---|
0 | 182.87 | 2.72 | 98.25 | 0.7 | 0.75816 | 1.025826 |
Table 1.: QA scores by SWISS model tool of GST-Docs structure.
His-Docs
Figure 2.: Predicted 3D structure of His-Docs designed by TRrosetta tool displayed by Pymol.
cbeta_deviations | clashscore | molprobity | ramachandran_favored | ramachandran_outliers | Qmean_4 | Qmean_6 |
---|---|---|---|---|---|---|
1 | 2.53 | 1.69 | 85.33 | 1.33 | -1.68577 | -1.79068 |
Table 2.: QA scores by SWISS model tool of His-Docs structure.
1.2. Docking
Tagged Docs with GST and His has been docked with Coh2 tagged with GST and His by different tools to get the best model. Best docked structures were retrieved from ClusPro and Galaxy web servers according to our ranking code.
GST-Docs VS His-Coh by Cluspro
Figure 3.: Docked structure of GST-Docs VS His-Coh2 designed by Cluspro displayed by Pymol.
GST-Docs VS His-Coh2 by Galaxy
Figure 4.: Docked structure of GST-Docs VS His-Coh2 designed by Galaxy visualized by Pymol.
His-Docs VS GST-Coh by ClusPro
Figure 5.: Docked structure of His-Docs VS GST-Coh2 designed by ClusPro visualized by Pymol.
His-Docs VS GST-Coh2 by Galaxy
Figure 6.: Docked structure of His-Docs VS GST-Coh2 designed by Galaxy visualized by Pymol.
Binding energies of Docs VS Coh2
Table 3.: Binding energies of Docs VS Coh2 tagged with GST and His designed by Galaxy and ClusPro.
All of docking results were ranked using our code for calculating the binding affinity.
1. Functional Parameters
pI: 5.30
M.Wt.: 16751.19 Da
WetLab Results
Results of His-DocS
Transformation of His Doc in DH-5 alpha using pJET cloning vector
Figure 7. Transformed plate of His Doc + pJET
Transformation of His Doc in BL-21 using pGS-21a expression vector
Figure 8. Transformed plate of His Doc + pGS-21a
Comparison between chemical lysis and sonication for His DOC
Figure 9. This graph shows the difference between chemical lysis and sonication for His DOC, after we had the results, we optimized our protocol to use chemical lysis for His DOC
SDS PAGE for induced and non induced samples of His DOC
Figure 10. This figure shows the comparison between induced and non-induced samples of His DOC where well no.2 is the non-induced sample while well no.4 is the induced sample showing that our protein is induced effectively owing to our right choice of IPTG, time interval, and concentration
Results of GST-DocS
Transformation of GST DOC in DH-5 alpha using pJET cloning vector
Figure 11. Transformed plate of GST DOC + pJET
Transformation of GST DOC in BL-21 using pGS-21a expression vector
Figure 12. Transformed plate of GST Doc + pGS-21a
Comparison between chemical lysis and sonication for GST DOC
Figure 13. This graph shows a significant difference between chemical lysis and sonication for GST DOC, after we had the results we optimized our protocol to use chemical lysis for GST DOC
Reference
[1] BARAK Y, HANDELSMAN T, NAKAR D, et al. Matching fusion protein systems for affinity analysis of two interacting families of proteins: the cohesin-dockerin interaction [J]. J Mol Recognit, 2005, 18(6): 491-501.
[2] Kazutaka Sakka, Yuka Sugihara, Sadanari Jindou, Makiko Sakka, Minoru Inagaki, Kazuo Sakka, Tetsuya Kimura, Analysis of cohesin–dockerin interactions using mutant dockerin proteins, FEMS Microbiology Letters, Volume 314, Issue 1, January 2011, Pages 75–80, https://doi.org/10.1111/j.1574-6968.2010.02146.x
[3] Lawrie, J., Song, X., Niu, W., & Guo, J. (2018). A high throughput approach for the generation of orthogonally interacting protein pairs. Scientific Reports, 8. https://doi.org/10.1038/s41598-018-19281-6