Difference between revisions of "Part:BBa K4165035"

 
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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), WAP inhibitor (BBa_K4165008), GSGSGS linker (BBa_J18921), TD28rev (BBa_K4165006), GGSGGGGG linker (BBa_K4165019), WWW (BBa_K4165007), GSGSGS linker (BBa_J18921), H1A (BBa_K4165000) and T7 terminator (BBa_K731721).
 
This composite part consists of T7 promoter (BBa_K3633015), lac operator (BBa_K4165062), pGS-21a RBS (BBa_K4165016), 6x His-tag (BBa_K4165020), WAP inhibitor (BBa_K4165008), GSGSGS linker (BBa_J18921), TD28rev (BBa_K4165006), GGSGGGGG linker (BBa_K4165019), WWW (BBa_K4165007), GSGSGS linker (BBa_J18921), H1A (BBa_K4165000) and T7 terminator (BBa_K731721).
 
  
 
===Usage and Biology===
 
===Usage and Biology===
Switch 15 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 15 is used to mediate the activity of HTRA1. It is composed of 3 parts connected by different linkers; an HtrA1 peptide binding PDZ, a clamp of two targeting peptides for tau or amyloid beta, and a catalytic domain inhibitor. Activating HTRA1 upon clamp binding to the target protein 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 seed peptide is considered as an amyloid binding peptide and is proved experimentally to inhibit the aggregations of amyloid beta through cell viability assays with a survival rate values nearly 100%. The H1A peptide was validated 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 accoding to both CAPRI and NCBI protocols.
 +
 
 +
 
  
 
<h2>Sequence and Features</h2>
 
<h2>Sequence and Features</h2>
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===Modeling===
 
===Modeling===
TRrosetta models 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).
+
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.
 +
 
 +
===Dry-lab Characterization===
 +
<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>
 +
 
 +
 
 +
                    Figure 1. A figure which dsecribes our Dry-Lab Modelling Pipeline. By team CU_Egypt 2022.
 +
 
 +
 
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/pep15.png" style="margin-left:175px;" alt="" width="500" /></p>
 +
</html>
 +
 
 +
                    Figure 2. The 3D structure of switch 15 is modeled by TRrosetta. Red: Tau binding peptides,
 +
                                      blue: H1A peptide, cyan: inhibitor and green: linkers
 +
 
 +
 
 +
<p style=" font-weight: bold; font-size:14px;"> Docking </p>
 +
 
 +
<p style=" font-weight: bold; font-size:14px;"> switch 15 vs HtrA1 trimer: </p>
 +
 
 +
<p style=" font-weight: bold; color: red; font-size:14px;"> ΔG = -15.52 </p>
 +
 
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/pep15-htra1.png" style="margin-left:250px;" alt="" width="500" /></p>
 +
</html>
 +
 
 +
                              Figure 3. The 3D structure of switch 15 docked to HtrA1 displayed on Pymol.
 +
 
 +
<p style=" font-weight: bold; font-size:14px;"> Mathematical modeling </p>
 +
<p style=" font-weight: bold; font-size:14px;">Transcription rate and translation rate under T7 promoter </p>
 +
the mathematical modeling was based on our code for the calculation of transcription and translation (you can find it in the code section) beside with the estimated results from the wet lab.
 +
 
 +
<html>
 +
<p><img src="https://static.igem.wiki/teams/4165/wiki/dry-lab/mathematical-modeling/mathematical-modeling/peptide-152.png" style="margin-left:200px;" alt="" width="500" /></p>
 +
</html>
 +
 +
 
 +
                Figure 4. this figure shows the results from the transcription and translation code showing the
 +
                                  variation of mRNA and protein concentrations with time.
 +
 
 +
 
 +
             
 +
 
 +
<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 modelling (ab initio) and template-based modelling. For modelling 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 modelling 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>
 +
<p>We take the top ranked models from the previous steps.</p>
 +
<p style=" font-weight: bold; font-size:14px;">5) Docking</p>
 +
<p>The top models are docked with the protein of intereset (in our case it was the HtrA1 with a BBa_K4165004.</p>
 +
<p style=" font-weight: bold; font-size:14px;">6) Ranking</p>
 +
<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 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>
 +
<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 binded to the same site or not.</p>
 +
<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.</p>
 +
<p style=" font-weight: bold; font-size:14px;">10) Assembly</p>
 +
<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>a<img src="https://static.igem.wiki/teams/4165/wiki/team-members/team-members/new/q8iub5.png" style="margin-left:50px;" alt="" width="150" />b<img src="https://static.igem.wiki/teams/4165/wiki/lh1a.png" style="margin-left:50px;" alt="" width="150" />c<img src="https://static.igem.wiki/teams/4165/wiki/team-members/team-members/new/td28rev-www.png" style="margin-left:50px;" alt="" width="150" /></p>
 +
</html>
 +
        Figure (a,b,c) : 3D structure of  Q8IUB5 Inhibitor , H1A Peptide ,  and TD28rev-GGSGGGG-WWW clamp
 +
                                    used in our assembly of switch 15
 +
 
 +
<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>
 +
 
 +
<html>
 +
<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
 +
}
 +
</style>
 +
<body>
 +
<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>1</td>
 +
    <td>4.23</td>
 +
    <td>1.21</td>
 +
    <td>98.56</td>
 +
    <td>0.72</td>
 +
    <td>1.034211</td>
 +
    <td>0.034805</td>
 +
  </tr>
 +
</table>
 +
</body>
 +
</html>
 +
 
 +
<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>
 +
<p style=" font-weight: bold; font-size:14px;">14) Alignment</p>
 +
<p>The docked structures are then aligned and compared to the basic parts which are docked with protein of interest (HtrA1). The structures with least RMSD are chosen.</p>
  
  
 
<html>
 
<html>
<p><img src="https://static.igem.wiki/teams/4165/wiki/parts-registry/15.png" style="margin-left:200px;" alt="" width="500" /></p>
+
<style>
 +
table, th, td {
 +
  border:1px solid black; margin-left:auto;margin-right:auto;
 +
}
 +
</style>
 +
<body>
 +
<table style="width:65%">
 +
<table>
 +
  <tr>
 +
    <th>RMSD Before Docking</th>
 +
    <th>RMSD After Docking </th>
 +
  </tr>
 +
  <tr>
 +
    <td>1.31</td>
 +
    <td>10.14</td>
 +
  </tr>
 +
</table>
 +
</body>
 
</html>
 
</html>
  
                                Figure 1. The 3D structure of switch 15 modeled by TRrosetta
 
  
<!-- -->
+
===Refernces===
 +
1. Lu, J., Cao, Q., Wang, C., Zheng, J., Luo, F., Xie, J., ... & Li, D. (2019). Structure-based peptide inhibitor design of amyloid-β aggregation. Frontiers in molecular neuroscience, 12, 54.
  
 +
2. 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.
  
 +
3. 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  
 
===Functional Parameters===
 
===Functional Parameters===
 
<partinfo>BBa_K4165035 parameters</partinfo>
 
<partinfo>BBa_K4165035 parameters</partinfo>
 
<!-- -->
 
<!-- -->

Latest revision as of 21:00, 13 October 2022


HtrA1 Switch number 15

This composite part consists of T7 promoter (BBa_K3633015), lac operator (BBa_K4165062), pGS-21a RBS (BBa_K4165016), 6x His-tag (BBa_K4165020), WAP inhibitor (BBa_K4165008), GSGSGS linker (BBa_J18921), TD28rev (BBa_K4165006), GGSGGGGG linker (BBa_K4165019), WWW (BBa_K4165007), GSGSGS linker (BBa_J18921), H1A (BBa_K4165000) and T7 terminator (BBa_K731721).

Usage and Biology

Switch 15 is used to mediate the activity of HTRA1. It is composed of 3 parts connected by different linkers; an HtrA1 peptide binding PDZ, a clamp of two targeting peptides for tau or amyloid beta, and a catalytic domain inhibitor. Activating HTRA1 upon clamp binding to the target protein 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 seed peptide is considered as an amyloid binding peptide and is proved experimentally to inhibit the aggregations of amyloid beta through cell viability assays with a survival rate values nearly 100%. The H1A peptide was validated 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 accoding 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
    INCOMPATIBLE WITH RFC[25]
    Illegal NgoMIV site found at 379
    Illegal AgeI site found at 115
  • 1000
    COMPATIBLE WITH RFC[1000]

Modeling

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.

Dry-lab Characterization


                   Figure 1. A figure which dsecribes our Dry-Lab Modelling Pipeline. By team CU_Egypt 2022.


                    Figure 2. The 3D structure of switch 15 is modeled by TRrosetta. Red: Tau binding peptides, 
                                      blue: H1A peptide, cyan: inhibitor and green: linkers


Docking

switch 15 vs HtrA1 trimer:

ΔG = -15.52

                             Figure 3. The 3D structure of switch 15 docked to HtrA1 displayed on Pymol.

Mathematical modeling

Transcription rate and translation rate under T7 promoter

the mathematical modeling was based on our code for the calculation of transcription and translation (you can find it in the code section) beside with the estimated results from the wet lab.


               Figure 4. this figure shows the results from the transcription and translation code showing the 
                                 variation of mRNA and protein concentrations with time.



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 modelling (ab initio) and template-based modelling. For modelling 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 modelling 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 intereset (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 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 binded to the same site or not.

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.

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.

abc

        Figure (a,b,c) : 3D structure of  Q8IUB5 Inhibitor , H1A Peptide ,  and TD28rev-GGSGGGG-WWW clamp 
                                    used in our assembly of switch 15

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.

cbeta_deviations clashscore molprobity ramachandran_favored ramachandran_outliers Qmean_4 Qmean_6
1 4.23 1.21 98.56 0.72 1.034211 0.034805

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.

14) Alignment

The docked structures are then aligned and compared to the basic parts which are docked with protein of interest (HtrA1). The structures with least RMSD are chosen.


RMSD Before Docking RMSD After Docking
1.31 10.14


Refernces

1. Lu, J., Cao, Q., Wang, C., Zheng, J., Luo, F., Xie, J., ... & Li, D. (2019). Structure-based peptide inhibitor design of amyloid-β aggregation. Frontiers in molecular neuroscience, 12, 54.

2. 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.

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