Difference between revisions of "Team:UI Indonesia/Model"

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<div class="column full_size judges-will-not-evaluate">
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<h3>★  ALERT! </h3>
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  body,h1,h2,h3,h4,h5,h6 {font-family: "Lato", sans-serif;}
<p>This page is used by the judges to evaluate your team for the <a href="https://2018.igem.org/Judging/Medals">medal criterion</a> or <a href="https://2018.igem.org/Judging/Awards"> award listed below</a>. </p>
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  body, html {
<p> Delete this box in order to be evaluated for this medal criterion and/or award. See more information at <a href="https://2018.igem.org/Judging/Pages_for_Awards"> Instructions for Pages for awards</a>.</p>
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<h1> Modeling</h1>
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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      background-image: url("https://static.igem.org/mediawiki/2018/0/07/T--UI_Indonesia--bacteria.jpg");
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<h3> Gold Medal Criterion #3</h3>
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<p>
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      min-height: 400px;
Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.  
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  }
<br><br>
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The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
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</p>
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  .bgimg-5 {
Please see the <a href="https://2018.igem.org/Judging/Medals"> 2018
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Medals Page</a> for more information.  
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</p>
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</div>
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<div class="column two_thirds_size">
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<h3>Best Model Special Prize</h3>
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To compete for the <a href="https://2018.igem.org/Judging/Awards">Best Model prize</a>, please describe your work on this page  and also fill out the description on the <a href="https://2018.igem.org/Judging/Judging_Form">judging form</a>. Please note you can compete for both the gold medal criterion #3 and the best model prize with this page.
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    background-color: #4CAF50;
<br><br>
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You must also delete the message box on the top of this page to be eligible for the Best Model Prize.
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<h3> Inspiration </h3>
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Here are a few examples from previous teams:
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<li><a href="https://2016.igem.org/Team:Manchester/Model">2016 Manchester</a></li>
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  }
<li><a href="https://2016.igem.org/Team:TU_Delft/Model">2016 TU Delft</li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">2014 ETH Zurich</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">2014 Waterloo</a></li>
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</div>
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<!-- Container (Introduction Section) -->
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<div class="bgimg-1 w3-display-container w3-opacity-min" id="intro">
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  <div class="w3-display-middle" style="white-space:nowrap;">
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    <span class="w3-center w3-padding-large w3-black w3-xlarge w3-wide w3-animate-opacity">INTRODUCTION</span>
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  </div>
 
</div>
 
</div>
  
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<div class="w3-content w3-container w3-padding-64">
 +
  <h5>Our first steps in modelling the subsequent parts of <i>Finding Diphthy</i> iGEM-UI 2018 <i>in silico</i> is by
 +
  constructing all 3D models via <i>I-Tasser</i> server.<sup>1,2,3</sup> The extension of the product file is <i>.pdb</i>, that
 +
  could be read by the server. The chimera molecules which we need to predict their modelling are HBEGF-TAR
 +
  (<i>Heparin Binding Epidermal Growth Factor-</i> TAR chemotaxis), CheA signalling protein, Che-Y signalling protein,
 +
  LuxAB dimerized luciferase subunits, and eYFP (<i>enhanced yellow fluorescent protein</i>), as well as Affitoxin
 +
  (modified diphtheria exotoxin). Since CheA and CheY are required to be linked with LuxB or eYFP,
 +
  we have cited one of the universal linker, that is ‘GGGSGGGGSGGGGSG’ peptides, according to <i>Sun S et al</i>.
 +
 
 +
  <br><br>
 +
 
 +
  Our signalling part of the project is referred these sequences of all chimera combinations.
 +
  <ol type="i">
 +
<li>LuxB-CheY</li>
 +
<li>LuxB-CheA</li>
 +
<li>CheY-eYFP</li>
 +
<li>CheA-eYFP</li>
 +
  </ol>
 +
 
 +
  <br><br>
 +
  In choosing the best combination, we use <i>FoldX</i> option via <i>YASARA molecules viewer</i>
 +
  to calculate the ∆G of each molecule, searching for the smallest free energy
 +
  (regarding its stability in <i>vivo</i>). All those sequences are also submitted to
 +
  <i>I-Tasser</i> server for projecting their 3D models qualitatively. The following
 +
  results would conclude that our <i>cytoplasmic</i> signalling combinations are
 +
  CheY-eYFP and LuxB-CheA.
 +
 
 +
  <br><br>
 +
 
 +
  <div align="center"><!-------TABLE 1-------TABLE 1-------TABLE 1------->
 +
  <h6><b>Table 1.</b> Specific Gibbs Energy within Each Protein Combination.</h6>
 +
  <table >
 +
<tr>
 +
<th width="120px">Combination</th>
 +
<th width="120px"><p align="center">∆G</p></th>
 +
</tr><tr>
 +
<td><b>LuxB-CheY</b></td>
 +
<td><p align="right">58.15 kcal/mol</p></td>
 +
</tr><tr>
 +
<td><b>LuxB-CheA</b></td>
 +
<td><p align="right">1355.46 kcal/mol</p></td>
 +
</tr><tr>
 +
<td><b>CheY-eYFP</b></td>
 +
<td><p align="right">36.48 kcal/mol</p></td>
 +
</tr><tr>
 +
<td><b>CheA-eYFP</b></td>
 +
<td><p align="right">36.48 kcal/mol</p></td>
 +
</tr>
 +
  </table>
 +
  </div>
 +
 
 +
  <!-------PAGE 2----------PAGE 2----------PAGE 2----------PAGE 2------->
 +
 
 +
  <br><br>
 +
 
 +
  Characterisation or purification of those proteins would promote the usage
 +
  of <i>His-tag</i>; therefore, insertion of His-tag inside the sequence is essential.
 +
  To ensure the slightest change of tertiary structures of each protein,
 +
  we would need to find out the secondary structure and surface accesibility
 +
  via <i>NetSurfP ver. 1.1</i> analyser (http://www.cbs.dtu.dk/services/NetSurfP/).
 +
  We would insert <i>His-tag</i> sequence in either no available specific protein
 +
  domain or the coiled secondary structure of protein to minimize any
 +
  interruptions. Here is our affitoxin data from <i>NetSurfP</i> server.
 +
 
 +
  <br><br>
 +
 
 +
  <div align="center"><!-------TABLE 2-------TABLE 2-------TABLE 2------->
 +
  <h6><b>Table 2.</b> Coiling probability of Affitoxin’s specific domain.</h6>
 +
  <table >
 +
<tr>
 +
<th>Class assignment</th>
 +
<th>Amino acid</th>
 +
<th><p align="right">Amino acid<br>number</p></th>
 +
<th><p align="right">Probability<br>for Coil</p></th>
 +
</tr><tr>
 +
<td><b>B</b></td>
 +
<td>I</td>
 +
<td><p align="right">54</p></td>
 +
<td><p align="right">0.223</p></td>
 +
</tr><tr>
 +
<td><b>E</b></td>
 +
<td>K</td>
 +
<td><p align="right">55</p></td>
 +
<td><p align="right">0.669</p></td>
 +
</tr><tr>
 +
<td><b>E</b></td>
 +
<td>S</td>
 +
<td><p align="right">56</p></td>
 +
<td><p align="right">0.994</p></td>
 +
</tr>
 +
</table>
 +
  </div>
 +
 
 +
  <br><br>
 +
 
 +
Result from the <i>NetSurf server</i>, we choose C-terminus side,
 +
because it most likely turns/coils around (indicated by
 +
has high number on the most right column is closest to 1),
 +
and it is freely exposed (indicated by most left column has E alphabet)
 +
  <br><br>
 +
Performing structural similarity between original molecule and
 +
the one inserted with <i>His-tag</i> sequence have been done by <i>MUSTANG</i>
 +
server that built in via <i>YASARA molecule viewer.<sup>5<sup></i> The output would be
 +
distance calculation between interacting atoms called RMSD
 +
(Root-mean-square deviation). Following tables are summaries of the
 +
molecular similarity analysis
 +
 
 +
  <br><br>
 +
 
 +
  <div align="center">
 +
  <h6><b>Table 1.</b> RMSD Calculation within Several Protein Linked with His-tag.</h6>
 +
  <table ><!-------TABLE 3-------TABLE 3-------TABLE 3------->
 +
<tr>
 +
<th width="300px"><p align="center">Similarities between</th>
 +
<th width="120px"><p align="center">RMSD</p></th>
 +
</tr><tr>
 +
<td><b>LuxA with LuxA + His</b></td>
 +
<td>2.203 Å</td>
 +
</tr><tr>
 +
<td><b>LuxC with LuxC + His</b></td>
 +
<td>0.985 Å</td>
 +
</tr><tr>
 +
<td><b>LuxD with LuxD + His</b></td>
 +
<td>0.1777 Å</td>
 +
</tr><tr>
 +
<td><b>LuxE with LuxE + His</b></td>
 +
<td>0.800 </td>
 +
</tr><tr>
 +
<td><b>CheY-eYFP with CheY-eYFP+his</b></td>
 +
<td>0.108 Å</td>
 +
</tr><tr>
 +
<td><b>eYFP with eYFP + His</b></td>
 +
<td>0.315 Å</td>
 +
</tr><tr>
 +
<td><b>CheA with CheA + His</b></td>
 +
<td>0.134 Å</td>
 +
</tr>
 +
  </table>
 +
  </div>
 +
 
 +
  <br><br>
 +
 
 +
From the data that described above, all the combinations are acceptable,
 +
except LuxA, since its possible combination has high RMSD. The threshold
 +
is relative, but several literatures define the RMSD value of 2 as
 +
threshold for structure similarity.<sup>5,6,7</sup>
 +
  <br><br>
 +
To ensure that the chimeric protein functions as both diphtheria’s
 +
toxin receptor and Tar-mediated intracellular signaller, we chose
 +
specific site of HB-EGF and Tar protein selectively for functional
 +
combination. The chimera was designed by replacing parts of extracellular
 +
domain of Tar receptor with binding domain of HB-EGF.
 +
  <br><br>
 +
In HB-EGF, the part that serves as binding domain for diphtheria exotoxin
 +
predominantly located in the extracellular environment. Therefore,
 +
the domain, expands between 20<sup>th</sup> – 160<sup>th</sup> amino acid, was selected from
 +
natural HB-EGF protein. On the other hand, the Tar domain that are
 +
functions to establish intracellular chemotactic signalling includes
 +
NdeI cutting-site (around 257<sup>th</sup> amino acid) until the utmost C-terminal
 +
of the protein (the 553<sup>rd</sup> amino acid).8-11 By those factors, our team also
 +
selected Tar domains involving the 1st – 33<sup>rd</sup> and 191<sup>st</sup> –
 +
553<sup>rd</sup> amino acid as part of chimeric protein.
 +
 
 +
  <br><br>
 +
 
 +
  <img></img><!----Figure 1 Image----->
 +
 
 +
  <br><br>
 +
 
 +
<h6><b>Figure 1.</b> The selected segment of Tar protein. The functional
 +
intracellular domain of Tar is shown as yellow box, blue box is
 +
transmembrane domain and orange box is periplasmic domain. Selected Tar
 +
domain expands from 1st -33<sup>rd</sup> amino acids and 191<sup>st</sup> -553<sup>rd</sup> amino acids.
 +
Modification of binding domain is located between 33<sup>rd</sup> – 191<sup>st</sup> amino acids</h6>
 +
 
 +
  <br><br>
 +
 
 +
<h5>Our team have predicted the HB-EGF/Tar protein orientation in the
 +
<i>Escherichia coli</i> membrane. For this purpose, server <i>TMHMM</i> and <i>OPM Membrane</i>,
 +
are utilized to predict protein orientation.<sup>12,13</sup> Conceptual hypothesis
 +
about the chimera protein is that it should begin its orientation of
 +
C-terminus in cytoplasm, then continued to fold into transmembrane and
 +
extracellular sites, as well as re-folding towards cytoplasm.
 +
 
 +
  <!-------PAGE 3----------PAGE 3----------PAGE 3----------PAGE 3------->
 +
 
 +
  <br><br>
 +
 
 +
<h6><b>Figure 2.</b> The graph above explains the result of HB-EGF/Tar
 +
orientation, which began from C-terminus (left) to N-terminus (right).<sup>12</sup>
 +
Y-axis pictured the possibility of n<sup>th</sup> amino acid on protein located somewhere
 +
between transmembrane (red part), intracellular (blue line), and
 +
extracellular (pink line). There is also a diagram located above the graph
 +
that represent the most possible location of each domain (with elongated box).</h6>
 +
 
 +
  <br>
 +
 
 +
<h5>From the results, it could be concluded that the protein was oriented
 +
as expected in the hypothesis. Therefore, the usage of chimera protein is
 +
predicted to be functional anatomically.
 +
 
 +
  <br>
 +
 
 +
  <img></img><!----Figure 2 Image----->
 +
 
 +
  <br>
 +
 
 +
  <img></img><!----Figure 3 Image----->
 +
 
 +
  <br>
 +
 
 +
<h6><b>Figure 3.</b>Molecular comparation of HB-EGF native protein (left)
 +
with the HB-EGF/Tar fusion (right).<sup>13,14</sup> The pink-coloured
 +
domain is intracellularly located as the N-terminus, yellow-coloured
 +
domain for the transmembrane one. Then, purple-coloured could be a sign
 +
as the extracellular domain, finally folding into transmembrane and back
 +
to cytoplasm with orange-coloured and cyan-coloured domain respectively.</h6>
 +
 
 +
  <!-------PAGE 4----------PAGE 4----------PAGE 4----------PAGE 4------->
 +
 
 +
  <br>
 +
 
 +
After deciding sequence combination of amino acids in modelled chimera
 +
HB-EGF/Tar protein, analyzing the interaction of both fusion protein and
 +
diphtheria exotoxin is extremely important to ensure functional
 +
ligand-receptor system. The basic concept of interaction modelling is
 +
that the protein will be bound to each other well if it causes the
 +
‘environment’ energy (termed by E parameter; calculated by formula below)
 +
being lowered down. In this part, our team sent the respective sequence to
 +
ClusPro website for further analyzing.15
 +
 
 +
  <br>
 +
 
 +
  <div><h4 align="center">
 +
E = 0.4E<sub>rep</sub> + -0.40E<sub>att</sub> + 600E<sub>elec</sub> + 1.00E<sub>DARS</sub>
 +
  </h4></div>
 +
 
 +
<h6>Note: E<sub>rep</sub> and E<sub>attr</sub> denote as repulsive and attractive contributions
 +
to the <i>van der Waals</i> interaction energy. Additionally, E<sub>elec</sub> means an
 +
electrostatic energy that occur during both protein interaction. E<sub>DARS</sub>
 +
is a pairwise structure-based potential constructed by the Decoys of
 +
the Reference State (DARS) approach, and it primarily represents
 +
desolvation contributions, i.e., the free energy change due to the
 +
removal of the water molecules from the interface.<sup>15</sup><h6>
 +
 
 +
  <br>
 +
 
 +
  <div align="center">
 +
  <h6><b>Table 4.</b> Comparation of E parameter of native and chimera protein of HB-EGF interacted with affitoxin.</h6>
 +
  <table ><!-------TABLE 4-------TABLE 4-------TABLE 4------->
 +
<tr>
 +
<th><p align="center">HB-EGF<br>Protein</th>
 +
<th><p align="center">Median Energy (kcal/mol)</p></th>
 +
<th><p align="center">Lowest Energy (kcal/mol)</p></th>
 +
</tr><tr>
 +
<td><b>Native</b></td>
 +
<td><p align="center">-944.3</p></td>
 +
<td><p align="center">-994.3</p></td>
 +
</tr><tr>
 +
<td><b>Chimera</b></td>
 +
<td><p align="center">858.2</p></td>
 +
<td><p align="center">934.4</p></td>
 +
</tr>
 +
  </table>
 +
  </div>
 +
 
 +
  <br>
 +
 
 +
  <img></img><!----Figure 4 Image----->
 +
 
 +
<h6><b>Figure 5.</b>HB-EGF natural receptor and Affitoxin 3D interaction modelling result.</h6>
 +
 
 +
  <br>
 +
 
 +
The result of interaction modelling is quantified as energy score based on
 +
the formula above. Referring to figure 4 and 5, we might expect that the
 +
affitoxin (cyan) would bind to both native and chimeric HB-EGF receptor that
 +
are both located in the extracellular (green). It is indicated by higher
 +
energy score of interaction between chimeric HB-EGF/Tar receptor-Affitoxin
 +
than that of to HB-EGF natural receptor-Affitoxin (Table 4). This means
 +
that the chimeric receptor could bind towards affitoxin as good
 +
(or even better) than the original one.
 +
 
 +
  <br><br>
 +
 
 +
Beside the cell’s ability to detect toxin, our team also need to ensure
 +
the signaling machine works well. Our team also modelled the interaction
 +
between LuxA dan LuxB (that we fused with CheA). From figure 6 and 7,
 +
we might expect that both proteins are still able to interact normally
 +
after combining them with FRET unit (CheA or CheY protein).
 +
 
 +
  <!-------PAGE 5----------PAGE 5----------PAGE 5----------PAGE 5------->
 +
 
 +
  <br>
 +
 
 +
  <div align="center">
 +
  <h6><b>Table 5.</b> Comparation of E parameter of native and His-tagged protein of LuxB-CheA.</h6>
 +
  <table ><!-------TABLE 5-------TABLE 5-------TABLE 5------->
 +
<tr>
 +
<th><p align="center">LuxAB</th>
 +
<th><p align="center">Median Energy (kcal/mol)</p></th>
 +
<th><p align="center">Lowest Energy (kcal/mol)</p></th>
 +
</tr><tr>
 +
<td><b>Native</b></td>
 +
<td><p align="center">-1515.4.3</p></td>
 +
<td><p align="center">-1553.2</p></td>
 +
</tr><tr>
 +
<td><b>Chimera</b></td>
 +
<td><p align="center">-1220.9</p></td>
 +
<td><p align="center">-1290.7</p></td>
 +
</tr>
 +
  </table>
 +
  </div>
 +
 
 +
  <br>
 +
 
 +
  <img></img><!----Figure 6 Image----->
 +
 
 +
<h6><b>Figure 6.</b>LuxA and LuxB-CheA (LuxAB-CheA) 3D interaction modelling result.</h6>
 +
 
 +
  <img></img><!----Figure 7 Image----->
 +
 
 +
<h6><b>Figure 7.</b>.LuxA and LuxB 3D interaction modelling result.</h6>
 +
 
 +
  <!-------PAGE 6----------PAGE 6----------PAGE 6----------PAGE 6------->
 +
 
 +
  <br>
 +
 +
  <div>
 +
Reference :
 +
<ol align="justify">
 +
<li>J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015)</li>
 +
<li>A Roy, A Kucukural, Y Zhang. I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols, 5: 725-738 (2010)</li>
 +
<li>Y Zhang. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, vol 9, 40 (2008)</li>
 +
<li>Sun, S., Yang, X., Wang, Y., Shen, X., 2016. In Vivo Analysis of Protein–Protein Interactions with Bioluminescence Resonance Energy Transfer (BRET): Progress and Prospects. International Journal of Molecular Sciences 17, 1704. https://doi.org/10.3390/ijms17101704</li>
 +
<li>MUSTANG: A multiple structural alignment algorithm Konagurthu AS, Whisstock JC, Stuckey PJ, Lesk AM (2006) Proteins 64,559-574</li>
 +
<li>Bordogna, A., Pandini, A., Bonati, L., 2010. Predicting the accuracy of protein-ligand docking on homology models. Journal of Computational Chemistry 32, 81–98. https://doi.org/10.1002/jcc.21601</li>
 +
<li>Carugo, O., 2003. How root-mean-square distance (r.m.s.d.) values depend on the resolution of protein structures that are compared. Journal of Applied Crystallography 36, 125–128. https://doi.org/10.1107/s0021889802020502</li>
 +
<li>Kanchan, K., Linder, J., Winkler, K., Hantke, K., Schultz, A. and Schultz, J. (2009). Transmembrane Signaling in Chimeras of the Escherichia coli Aspartate and Serine Chemotaxis Receptors and Bacterial Class III Adenylyl Cyclases. <i>Journal of Biological Chemistry</i>, 285(3), pp.2090-2099.</li>
 +
<li>Ward, S., Delgado, A., Gunsalus, R. and Manson, M. (2002). A NarX-Tar chimera mediates repellent chemotaxis to nitrate and nitrite. <i>Molecular Microbiology</i>, 44(3), pp.709-719.</li>
 +
<li><b>Melchers, L. S., Regensburg-Tuïnk, T. J., Bourret, R. B., Sedee, N. J., Schilperoort, R. A. and Hooykaas, P. J. (1989). Membrane topology and functional analysis of the sensory protein VirA of Agrobacterium tumefaciens. The <i>EMBO Journal</i>, 8(7), pp.1919-1925.</li></b>
 +
<li><b>Weerasuriya, S., Schneider, B. M. and Manson, M. D. (1998). Chimeric Chemoreceptors in <i>Escherichia coli</i>: Signaling Properties of Tar-Tap and Tap-Tar Hybrids. <i>Journal of Bacteriology</i>, 180(4), pp.914-920.</li></b>
 +
<li>Cbs.dtu.dk. (2018). <i>TMHMM Server</i>, v. 2.0. [online] Available at: http://www.cbs.dtu.dk/services/TMHMM/ [Accessed 22 Jul. 2018].</li>
 +
<li>Lomize M.A., Pogozheva I,D, Joo H., Mosberg H.I., Lomize A.L. OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res., 2012, 40(Database issue):D370-6</li>
 +
<li>Kelley LA et al. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. <i>Nature Protocols</i> 10, pp.845-858 </li>
 +
<li>Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, Beglov D, Vajda S. The ClusPro web server for protein-protein docking. <i>Nature Protocols</i>.2017 Feb;12(2):255-278 ; pdf </li>
 +
<li>Kozakov D, Beglov D, Bohnuud T, Mottarella S, Xia B, Hall DR, Vajda, S. How good is automated protein docking? <i>Proteins: Structure, Function, and Bioinformatics</i>, 2013 Aug ;  pdf </li>
 +
<li>Kozakov D, Brenke R, Comeau SR, Vajda S. PIPER: An FFT-based protein docking program with pairwise potentials. <i>Proteins</i>. 2006 Aug 24;  pdf </li>
 +
<li>Comeau SR, Gatchell DW, Vajda S, Camacho CJ. ClusPro: an automated docking and discrimination method for the prediction of protein complexes.<i>Bioinformatics</i>. 2004 Jan 1;  pdf </li>
 +
<li>Comeau SR, Gatchell DW, Vajda S, Camacho CJ. ClusPro: a fully automated algorithm for protein-protein docking <i>Nucleic Acids Research</i>. 2004 Jul 1;  pdf </li>
 +
<li>Högbom, M., Eklund, M., Nygren, P. Å., & Nordlund, P. (2003). Structural basis for recognition by an in vitro evolved affibody. Proceedings of the National Academy of Sciences, 100(6), 3191-3196.</li>
 +
<li>2015.igem.org. (2018). <i>Team:Stockholm/Description - 2015.igem.org</i>. [online] Available at: https://2015.igem.org/Team:Stockholm/Description [Accessed 22 Jul. 2018].</li>
 +
</ol></div>
 +
 
 +
  <br>

Revision as of 12:07, 8 October 2018

INTRODUCTION
Our first steps in modelling the subsequent parts of Finding Diphthy iGEM-UI 2018 in silico is by constructing all 3D models via I-Tasser server.1,2,3 The extension of the product file is .pdb, that could be read by the server. The chimera molecules which we need to predict their modelling are HBEGF-TAR (Heparin Binding Epidermal Growth Factor- TAR chemotaxis), CheA signalling protein, Che-Y signalling protein, LuxAB dimerized luciferase subunits, and eYFP (enhanced yellow fluorescent protein), as well as Affitoxin (modified diphtheria exotoxin). Since CheA and CheY are required to be linked with LuxB or eYFP, we have cited one of the universal linker, that is ‘GGGSGGGGSGGGGSG’ peptides, according to Sun S et al.

Our signalling part of the project is referred these sequences of all chimera combinations.
  1. LuxB-CheY
  2. LuxB-CheA
  3. CheY-eYFP
  4. CheA-eYFP


In choosing the best combination, we use FoldX option via YASARA molecules viewer to calculate the ∆G of each molecule, searching for the smallest free energy (regarding its stability in vivo). All those sequences are also submitted to I-Tasser server for projecting their 3D models qualitatively. The following results would conclude that our cytoplasmic signalling combinations are CheY-eYFP and LuxB-CheA.

Table 1. Specific Gibbs Energy within Each Protein Combination.
Combination

∆G

LuxB-CheY

58.15 kcal/mol

LuxB-CheA

1355.46 kcal/mol

CheY-eYFP

36.48 kcal/mol

CheA-eYFP

36.48 kcal/mol



Characterisation or purification of those proteins would promote the usage of His-tag; therefore, insertion of His-tag inside the sequence is essential. To ensure the slightest change of tertiary structures of each protein, we would need to find out the secondary structure and surface accesibility via NetSurfP ver. 1.1 analyser (http://www.cbs.dtu.dk/services/NetSurfP/). We would insert His-tag sequence in either no available specific protein domain or the coiled secondary structure of protein to minimize any interruptions. Here is our affitoxin data from NetSurfP server.

Table 2. Coiling probability of Affitoxin’s specific domain.
Class assignment Amino acid

Amino acid
number

Probability
for Coil

B I

54

0.223

E K

55

0.669

E S

56

0.994



Result from the NetSurf server, we choose C-terminus side, because it most likely turns/coils around (indicated by has high number on the most right column is closest to 1), and it is freely exposed (indicated by most left column has E alphabet)

Performing structural similarity between original molecule and the one inserted with His-tag sequence have been done by MUSTANG server that built in via YASARA molecule viewer.5 The output would be distance calculation between interacting atoms called RMSD (Root-mean-square deviation). Following tables are summaries of the molecular similarity analysis

Table 1. RMSD Calculation within Several Protein Linked with His-tag.

Similarities between

RMSD

LuxA with LuxA + His 2.203 Å
LuxC with LuxC + His 0.985 Å
LuxD with LuxD + His 0.1777 Å
LuxE with LuxE + His 0.800
CheY-eYFP with CheY-eYFP+his 0.108 Å
eYFP with eYFP + His 0.315 Å
CheA with CheA + His 0.134 Å


From the data that described above, all the combinations are acceptable, except LuxA, since its possible combination has high RMSD. The threshold is relative, but several literatures define the RMSD value of 2 as threshold for structure similarity.5,6,7

To ensure that the chimeric protein functions as both diphtheria’s toxin receptor and Tar-mediated intracellular signaller, we chose specific site of HB-EGF and Tar protein selectively for functional combination. The chimera was designed by replacing parts of extracellular domain of Tar receptor with binding domain of HB-EGF.

In HB-EGF, the part that serves as binding domain for diphtheria exotoxin predominantly located in the extracellular environment. Therefore, the domain, expands between 20th – 160th amino acid, was selected from natural HB-EGF protein. On the other hand, the Tar domain that are functions to establish intracellular chemotactic signalling includes NdeI cutting-site (around 257th amino acid) until the utmost C-terminal of the protein (the 553rd amino acid).8-11 By those factors, our team also selected Tar domains involving the 1st – 33rd and 191st – 553rd amino acid as part of chimeric protein.



Figure 1. The selected segment of Tar protein. The functional intracellular domain of Tar is shown as yellow box, blue box is transmembrane domain and orange box is periplasmic domain. Selected Tar domain expands from 1st -33rd amino acids and 191st -553rd amino acids. Modification of binding domain is located between 33rd – 191st amino acids


Our team have predicted the HB-EGF/Tar protein orientation in the Escherichia coli membrane. For this purpose, server TMHMM and OPM Membrane, are utilized to predict protein orientation.12,13 Conceptual hypothesis about the chimera protein is that it should begin its orientation of C-terminus in cytoplasm, then continued to fold into transmembrane and extracellular sites, as well as re-folding towards cytoplasm.

Figure 2. The graph above explains the result of HB-EGF/Tar orientation, which began from C-terminus (left) to N-terminus (right).12 Y-axis pictured the possibility of nth amino acid on protein located somewhere between transmembrane (red part), intracellular (blue line), and extracellular (pink line). There is also a diagram located above the graph that represent the most possible location of each domain (with elongated box).

From the results, it could be concluded that the protein was oriented as expected in the hypothesis. Therefore, the usage of chimera protein is predicted to be functional anatomically.


Figure 3.Molecular comparation of HB-EGF native protein (left) with the HB-EGF/Tar fusion (right).13,14 The pink-coloured domain is intracellularly located as the N-terminus, yellow-coloured domain for the transmembrane one. Then, purple-coloured could be a sign as the extracellular domain, finally folding into transmembrane and back to cytoplasm with orange-coloured and cyan-coloured domain respectively.

After deciding sequence combination of amino acids in modelled chimera HB-EGF/Tar protein, analyzing the interaction of both fusion protein and diphtheria exotoxin is extremely important to ensure functional ligand-receptor system. The basic concept of interaction modelling is that the protein will be bound to each other well if it causes the ‘environment’ energy (termed by E parameter; calculated by formula below) being lowered down. In this part, our team sent the respective sequence to ClusPro website for further analyzing.15

E = 0.4Erep + -0.40Eatt + 600Eelec + 1.00EDARS

Note: Erep and Eattr denote as repulsive and attractive contributions to the van der Waals interaction energy. Additionally, Eelec means an electrostatic energy that occur during both protein interaction. EDARS is a pairwise structure-based potential constructed by the Decoys of the Reference State (DARS) approach, and it primarily represents desolvation contributions, i.e., the free energy change due to the removal of the water molecules from the interface.15

Table 4. Comparation of E parameter of native and chimera protein of HB-EGF interacted with affitoxin.

HB-EGF
Protein

Median Energy (kcal/mol)

Lowest Energy (kcal/mol)

Native

-944.3

-994.3

Chimera

858.2

934.4


Figure 5.HB-EGF natural receptor and Affitoxin 3D interaction modelling result.

The result of interaction modelling is quantified as energy score based on the formula above. Referring to figure 4 and 5, we might expect that the affitoxin (cyan) would bind to both native and chimeric HB-EGF receptor that are both located in the extracellular (green). It is indicated by higher energy score of interaction between chimeric HB-EGF/Tar receptor-Affitoxin than that of to HB-EGF natural receptor-Affitoxin (Table 4). This means that the chimeric receptor could bind towards affitoxin as good (or even better) than the original one.

Beside the cell’s ability to detect toxin, our team also need to ensure the signaling machine works well. Our team also modelled the interaction between LuxA dan LuxB (that we fused with CheA). From figure 6 and 7, we might expect that both proteins are still able to interact normally after combining them with FRET unit (CheA or CheY protein).
Table 5. Comparation of E parameter of native and His-tagged protein of LuxB-CheA.

LuxAB

Median Energy (kcal/mol)

Lowest Energy (kcal/mol)

Native

-1515.4.3

-1553.2

Chimera

-1220.9

-1290.7


Figure 6.LuxA and LuxB-CheA (LuxAB-CheA) 3D interaction modelling result.
Figure 7..LuxA and LuxB 3D interaction modelling result.

Reference :
  1. J Yang, R Yan, A Roy, D Xu, J Poisson, Y Zhang. The I-TASSER Suite: Protein structure and function prediction. Nature Methods, 12: 7-8 (2015)
  2. A Roy, A Kucukural, Y Zhang. I-TASSER: a unified platform for automated protein structure and function prediction. Nature Protocols, 5: 725-738 (2010)
  3. Y Zhang. I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, vol 9, 40 (2008)
  4. Sun, S., Yang, X., Wang, Y., Shen, X., 2016. In Vivo Analysis of Protein–Protein Interactions with Bioluminescence Resonance Energy Transfer (BRET): Progress and Prospects. International Journal of Molecular Sciences 17, 1704. https://doi.org/10.3390/ijms17101704
  5. MUSTANG: A multiple structural alignment algorithm Konagurthu AS, Whisstock JC, Stuckey PJ, Lesk AM (2006) Proteins 64,559-574
  6. Bordogna, A., Pandini, A., Bonati, L., 2010. Predicting the accuracy of protein-ligand docking on homology models. Journal of Computational Chemistry 32, 81–98. https://doi.org/10.1002/jcc.21601
  7. Carugo, O., 2003. How root-mean-square distance (r.m.s.d.) values depend on the resolution of protein structures that are compared. Journal of Applied Crystallography 36, 125–128. https://doi.org/10.1107/s0021889802020502
  8. Kanchan, K., Linder, J., Winkler, K., Hantke, K., Schultz, A. and Schultz, J. (2009). Transmembrane Signaling in Chimeras of the Escherichia coli Aspartate and Serine Chemotaxis Receptors and Bacterial Class III Adenylyl Cyclases. Journal of Biological Chemistry, 285(3), pp.2090-2099.
  9. Ward, S., Delgado, A., Gunsalus, R. and Manson, M. (2002). A NarX-Tar chimera mediates repellent chemotaxis to nitrate and nitrite. Molecular Microbiology, 44(3), pp.709-719.
  10. Melchers, L. S., Regensburg-Tuïnk, T. J., Bourret, R. B., Sedee, N. J., Schilperoort, R. A. and Hooykaas, P. J. (1989). Membrane topology and functional analysis of the sensory protein VirA of Agrobacterium tumefaciens. The EMBO Journal, 8(7), pp.1919-1925.
  11. Weerasuriya, S., Schneider, B. M. and Manson, M. D. (1998). Chimeric Chemoreceptors in Escherichia coli: Signaling Properties of Tar-Tap and Tap-Tar Hybrids. Journal of Bacteriology, 180(4), pp.914-920.
  12. Cbs.dtu.dk. (2018). TMHMM Server, v. 2.0. [online] Available at: http://www.cbs.dtu.dk/services/TMHMM/ [Accessed 22 Jul. 2018].
  13. Lomize M.A., Pogozheva I,D, Joo H., Mosberg H.I., Lomize A.L. OPM database and PPM web server: resources for positioning of proteins in membranes. Nucleic Acids Res., 2012, 40(Database issue):D370-6
  14. Kelley LA et al. (2015). The Phyre2 web portal for protein modeling, prediction and analysis. Nature Protocols 10, pp.845-858
  15. Kozakov D, Hall DR, Xia B, Porter KA, Padhorny D, Yueh C, Beglov D, Vajda S. The ClusPro web server for protein-protein docking. Nature Protocols.2017 Feb;12(2):255-278 ; pdf
  16. Kozakov D, Beglov D, Bohnuud T, Mottarella S, Xia B, Hall DR, Vajda, S. How good is automated protein docking? Proteins: Structure, Function, and Bioinformatics, 2013 Aug ; pdf
  17. Kozakov D, Brenke R, Comeau SR, Vajda S. PIPER: An FFT-based protein docking program with pairwise potentials. Proteins. 2006 Aug 24; pdf
  18. Comeau SR, Gatchell DW, Vajda S, Camacho CJ. ClusPro: an automated docking and discrimination method for the prediction of protein complexes.Bioinformatics. 2004 Jan 1; pdf
  19. Comeau SR, Gatchell DW, Vajda S, Camacho CJ. ClusPro: a fully automated algorithm for protein-protein docking Nucleic Acids Research. 2004 Jul 1; pdf
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