Difference between revisions of "Part:BBa K4165025"

 
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<partinfo>BBa_K4165025 short</partinfo>
 
<partinfo>BBa_K4165025 short</partinfo>
  
This composite part consists of T7 promoter (BBa_K3633015), lac operator (BBa_K4165062), pGS-21a RBS (BBa_K4165016), 6x His-tag (BBa_K4165020), SPINK8 Inhibitor (BBa_K4165010), TD28rev (BBa_K4165006), WWW (BBa_K4165007), H1A peptide (BBa_K4165000) and T7 terminator (BBa_K731721).
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This composite part consists of T7 promoter (BBa_K3633015), lac operator (BBa_K4165062), pGS-21a RBS (BBa_K4165016), 6x His-tag (BBa_K4165020), SPINK8 Inhibitor (BBa_K4165010), TD28rev (BBa_K4165006), GGSGGGGG linker (BBa_K4165018), WWW (BBa_K4165007), H1A peptide (BBa_K4165000) and T7 terminator (BBa_K731721).
  
 
===Usage and Biology===
 
===Usage and Biology===
Switch 5 is used to mediate the activity of HTRA1. Activating HTRA1 requires a conformational change in the linker, eliminating the attached inhibitor from the active site. The conformational rearrangement can be mediated through the affinity clamp for tau and beta-amyloid binding. These clamps are used for stabilizing the inhibitor away from the active site. These two domains (inhibitor and affinity clamp connected with linker1). Additionally, (H1A) binding peptide bound to the PDZ domain and connected to the affinity clamp on the other side with linker3.
+
Switch 5 is used to mediate the activity of HTRA1. It is composed of 3 parts connected by different linkers; an HtrA1 PDZ peptide, a clamp of two targeting peptides for tau or amyloid beta, and a catalytic domain inhibitor. Activating HTRA1 requires a conformational change in the linker, eliminating the attached inhibitor from the active site. The conformational rearrangement can be mediated through the binding of affinity clamp to tau or beta-amyloid. This binding will result in a tension that detaches the inhibitor from the active site.
  
===Modeling===
+
The TD28REV and WWW peptides which are considered as tau binding peptides are proved experimentally to bind with tau inhibit the aggregations of tau aggregations respectively. The H1A peptide was also proven to bind with the PDZ of HtrA1 experimentally. The last part which is the inhibitor which is mainly a serine protease inhibitor, and since our protease is a serine protease, so it will act and inhibit the Protein. The whole construction was similarly proved from literature. The process of assembly of the whole switch was done according to both CAPRI and NCBI protocols.
Rosetta fold model 3  this composite part with a score of 4 out of 6 according to our quality assessment code (you can find the python script file on the programming club page with further explanation of how you can optimize it to your needs).
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===<span class='h3bb'>Sequence and Features</span>===
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<partinfo>BBa_K4165025 SequenceAndFeatures</partinfo>
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===Dry Lab===
 +
The top model is TrRoseeta model and the workflow to reach the model will be described below.
 
<html>
 
<html>
 
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/switch-5.png" style="margin-left:200px;" alt="" width="500" /></p>
 
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/switch-5.png" style="margin-left:200px;" alt="" width="500" /></p>
 
</html>
 
</html>
  
                    Figure 1. The 3D structure of switch 5 modeled by Rosetta_fold
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                      Figure 1.:3D Predicted Structure of Switch 5 Protein by Pymol Visualization.
  
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/registry/dry-lab-modelling-pipeline.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
  
<!-- -->
 
<span class='h3bb'>Sequence and Features</span>
 
<partinfo>BBa_K4165025 SequenceAndFeatures</partinfo>
 
  
 +
                    Figure 2. A figure which describes our Dry-Lab Modelling Pipeline. By team CU_Egypt 2022.
 +
 +
<h1>Switch construction Pipeline</h1>
 +
 +
<p style=" font-weight: bold; font-size:14px;"> 1) Modelling </p>
 +
<p> Since our parts do not have experimentally acquired structures, we have to model them. This approach is done using both denovo modeling (ab initio) and template-based modeling. For modeling small peptides of our system  we used AppTest and Alphafold.</p>
 +
<p style=" font-weight: bold; font-size:14px;"> 2) Structure Assessment </p>
 +
<p>In order to assess the quality of our structures we used the Swiss-Model tool which gives an overall on quality of any 3D structure (For more information: (Link modeling page).</p>
 +
<p style=" font-weight: bold; font-size:14px;"> 3) Quality Assessment </p>
 +
<p>Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.</p>
 +
<p style=" font-weight: bold; font-size:14px;">4) Filtering</p>
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<p>We take the top-ranked models from the previous steps.</p>
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<p style=" font-weight: bold; font-size:14px;">5) Docking</p>
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<p>The top models are docked with the protein of interest (in our case it was the HtrA1 with a BBa_K4165004.</p>
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<p style=" font-weight: bold; font-size:14px;">6) Ranking</p>
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<p>The docking results are ranked according to their PRODIGY results. For more information: (Link Docking page).</p>
 +
<p style=" font-weight: bold; font-size:14px;">7) Top Models</p>
 +
<p>The results that came out from PRODIGY are ranked and the top models are chosen to proceed with to the next step. For more information: (Link Docking page).</p>
 +
<p style=" font-weight: bold; font-size:14px;">8) Alignment</p>
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<p>Docked structures are aligned. This means that the HtrA1- binding peptide complex is aligned with the second complex which
 +
is the HtrA1-inhibitor complex to check whether they bound to the same site or not.</p>
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<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/switches/switch31/picture10.png" style="margin-left:200px;" alt="" width="500" /></p>
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</html>
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 +
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      Figure 3. Aligned structures of HtrA1 binding peptide 1 docked to HtrA1 and inhibitor docked to HtrA1. </p>
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 +
<p style=" font-weight: bold; font-size:14px;">9) Linker length</p>
 +
<p>The linker lengths are acquired by seeing the distance between the inhibitor and the HtrA1 binding peptide which is between both C terminals, N terminals, C- and N- terminal, and N- and C-terminals. linkers range was from 20 to 24 angstroms.</p>
 +
 +
 +
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<p style=" font-weight: bold; font-size:14px;">10) Assembly</p>
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<p>After settling on the linkers lengths, now we will proceed to the assembly step of the whole system which is done using TRrosetta, AlphaFold, RosettaFold, and Modeller.</p>
 +
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/h1a.jpg" style="margin-left:70px;" alt="" width="200" /><img src="https://static.igem.wiki/teams/4165/wiki/inhibitor.png" style="margin-left:70px;" alt="" width="200" /></p>
 +
</html>
 +
 +
<p style=" font-weight: bold; font-size:14px;">11) Structure Assessment</p>
 +
<p>In order to assess the quality of our structures we used the Swiss-Model tool which gives an overall on quality of any 3D structure (For more information: (Link modelling page).</p>
 +
<p style=" font-weight: bold; font-size:14px;">12) Quality Assessment </p>
 +
<p>Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.</p>
 +
<p style=" font-weight: bold; font-size:14px;">13) Ranking</p>
 +
<p>Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.</p>
 +
The switch was modeled by (Alphafold - Rosettafold - tRrosetta) and the top model was obtained from tRrosseta with a score of 4 out of 6 according to our quality assessment code.
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 +
<html>
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<style>
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table, th, td {
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  border:1px solid black; margin-left:auto;margin-right:auto;
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}
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</style>
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<body>
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<table style="width:65%">
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<table>
 +
  <tr>
 +
    <th>cbeta_deviations</th>
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    <th>clashscore</th>
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    <th>molprobity</th>
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    <th>ramachandran_favored</th>
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    <th>ramachandran_outliers</th>
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    <th>Qmean_4</th>
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    <th>Qmean_6</th>
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  </tr>
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  <tr>
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    <td>0</td>
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    <td>4.26</td>
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    <td>1.21</td>
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    <td>99.3</td>
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    <td>0</td>
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    <td>-0.28997</td>
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    <td>-1.7137</td>
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  </tr>
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</table>
 +
</body>
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</html>                     
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                              Table 2: Quality assessment parameters of Switch 3 model.
 +
 +
===Conclusion===
 +
The top model was HtrA1 switch 10 (BBa_K4165030) since it was the best switch fulfilling the criteria of structure assessment, docking, and RMSD.
 +
 +
===References===
 +
1. Goedert, M., & Spillantini, M. G. (2017). Propagation of Tau aggregates. Molecular Brain, 10. https://doi.org/10.1186/s13041-017-0298-7
 +
 +
2. Etienne, M. A., Edwin, N. J., Aucoin, J. P., Russo, P. S., McCarley, R. L., & Hammer, R. P. (2007). Beta-amyloid protein aggregation. Methods in molecular biology (Clifton, N.J.), 386, 203–225. https://doi.org/10.1007/1-59745-430-3_7
 +
 +
4. Seidler, P., Boyer, D., Rodriguez, J., Sawaya, M., Cascio, D., Murray, K., Gonen, T., & Eisenberg, D. (2018). Structure-based inhibitors of tau aggregation. Nature chemistry, 10(2), 170. https://doi.org/10.1038/nchem.2889
 +
 +
5. Romero-Molina, S., Ruiz-Blanco, Y. B., Mieres-Perez, J., Harms, M., Münch, J., Ehrmann, M., & Sanchez-Garcia, E. (2022). PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein–Peptide and Protein–Protein Binding Affinity. Journal of Proteome Research.
 +
 +
6. Stein, V., & Alexandrov, K. (2014). Protease-based synthetic sensing and signal amplification. Proceedings of the National Academy of Sciences, 111(45), 15934-15939
  
 
<!-- Uncomment this to enable Functional Parameter display  
 
<!-- Uncomment this to enable Functional Parameter display  

Latest revision as of 03:48, 14 October 2022


HtrA1 switch 5

This composite part consists of T7 promoter (BBa_K3633015), lac operator (BBa_K4165062), pGS-21a RBS (BBa_K4165016), 6x His-tag (BBa_K4165020), SPINK8 Inhibitor (BBa_K4165010), TD28rev (BBa_K4165006), GGSGGGGG linker (BBa_K4165018), WWW (BBa_K4165007), H1A peptide (BBa_K4165000) and T7 terminator (BBa_K731721).

Usage and Biology

Switch 5 is used to mediate the activity of HTRA1. It is composed of 3 parts connected by different linkers; an HtrA1 PDZ peptide, a clamp of two targeting peptides for tau or amyloid beta, and a catalytic domain inhibitor. Activating HTRA1 requires a conformational change in the linker, eliminating the attached inhibitor from the active site. The conformational rearrangement can be mediated through the binding of affinity clamp to tau or beta-amyloid. This binding will result in a tension that detaches the inhibitor from the active site.

The TD28REV and WWW peptides which are considered as tau binding peptides are proved experimentally to bind with tau inhibit the aggregations of tau aggregations respectively. The H1A peptide was also proven to bind with the PDZ of HtrA1 experimentally. The last part which is the inhibitor which is mainly a serine protease inhibitor, and since our protease is a serine protease, so it will act and inhibit the Protein. The whole construction was similarly proved from literature. The process of assembly of the whole switch was done according to both CAPRI and NCBI protocols.


Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]

Dry Lab

The top model is TrRoseeta model and the workflow to reach the model will be described below.

                      Figure 1.:3D Predicted Structure of Switch 5 Protein by Pymol Visualization.


                   Figure 2. A figure which describes our Dry-Lab Modelling Pipeline. By team CU_Egypt 2022.

Switch construction Pipeline

1) Modelling

Since our parts do not have experimentally acquired structures, we have to model them. This approach is done using both denovo modeling (ab initio) and template-based modeling. For modeling small peptides of our system we used AppTest and Alphafold.

2) Structure Assessment

In order to assess the quality of our structures we used the Swiss-Model tool which gives an overall on quality of any 3D structure (For more information: (Link modeling page).

3) Quality Assessment

Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.

4) Filtering

We take the top-ranked models from the previous steps.

5) Docking

The top models are docked with the protein of interest (in our case it was the HtrA1 with a BBa_K4165004.

6) Ranking

The docking results are ranked according to their PRODIGY results. For more information: (Link Docking page).

7) Top Models

The results that came out from PRODIGY are ranked and the top models are chosen to proceed with to the next step. For more information: (Link Docking page).

8) Alignment

Docked structures are aligned. This means that the HtrA1- binding peptide complex is aligned with the second complex which is the HtrA1-inhibitor complex to check whether they bound to the same site or not.


     Figure 3. Aligned structures of HtrA1 binding peptide 1 docked to HtrA1 and inhibitor docked to HtrA1. </p>

9) Linker length

The linker lengths are acquired by seeing the distance between the inhibitor and the HtrA1 binding peptide which is between both C terminals, N terminals, C- and N- terminal, and N- and C-terminals. linkers range was from 20 to 24 angstroms.


10) Assembly

After settling on the linkers lengths, now we will proceed to the assembly step of the whole system which is done using TRrosetta, AlphaFold, RosettaFold, and Modeller.

11) Structure Assessment

In order to assess the quality of our structures we used the Swiss-Model tool which gives an overall on quality of any 3D structure (For more information: (Link modelling page).

12) Quality Assessment

Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.

13) Ranking

Using the code created by us (CU_Egypt 2022), we use the JSON files created from the structure assessment step in Swiss-Model to rank all the models For more information: (Link software page) under the name of Modric.

The switch was modeled by (Alphafold - Rosettafold - tRrosetta) and the top model was obtained from tRrosseta with a score of 4 out of 6 according to our quality assessment code.

cbeta_deviations clashscore molprobity ramachandran_favored ramachandran_outliers Qmean_4 Qmean_6
0 4.26 1.21 99.3 0 -0.28997 -1.7137

                              Table 2: Quality assessment parameters of Switch 3 model. 

Conclusion

The top model was HtrA1 switch 10 (BBa_K4165030) since it was the best switch fulfilling the criteria of structure assessment, docking, and RMSD.

References

1. Goedert, M., & Spillantini, M. G. (2017). Propagation of Tau aggregates. Molecular Brain, 10. https://doi.org/10.1186/s13041-017-0298-7

2. Etienne, M. A., Edwin, N. J., Aucoin, J. P., Russo, P. S., McCarley, R. L., & Hammer, R. P. (2007). Beta-amyloid protein aggregation. Methods in molecular biology (Clifton, N.J.), 386, 203–225. https://doi.org/10.1007/1-59745-430-3_7

4. Seidler, P., Boyer, D., Rodriguez, J., Sawaya, M., Cascio, D., Murray, K., Gonen, T., & Eisenberg, D. (2018). Structure-based inhibitors of tau aggregation. Nature chemistry, 10(2), 170. https://doi.org/10.1038/nchem.2889

5. Romero-Molina, S., Ruiz-Blanco, Y. B., Mieres-Perez, J., Harms, M., Münch, J., Ehrmann, M., & Sanchez-Garcia, E. (2022). PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein–Peptide and Protein–Protein Binding Affinity. Journal of Proteome Research.

6. Stein, V., & Alexandrov, K. (2014). Protease-based synthetic sensing and signal amplification. Proceedings of the National Academy of Sciences, 111(45), 15934-15939