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2024 Competition
Tsinghua
Commits
e0fe97da
Commit
e0fe97da
authored
5 months ago
by
Zhefu Li
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e0fe97da
...
...
@@ -88,6 +88,15 @@
overflow-x
:
auto
;
/* 允许水平滚动 */
}
.col-lg-12
a
{
color
:
#fa8072
;
text-decoration
:
none
;
transition
:
color
0.3s
ease
;
}
.col-lg-12
a
:hover
{
color
:
#ff6347
;
text-decoration
:
underline
;
}
</style>
</head>
...
...
@@ -138,7 +147,7 @@
</div>
<div
class=
"image-container"
>
<img
src=
"https://static.igem.wiki/teams/5187/wiki-model-fig/introduction.png"
alt=
"introduction_figure"
class=
"shadowed-image"
>
class=
"shadowed-image"
style=
"width: 80%; max-width: 800px;"
>
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 1 General Description of Model
</p>
</div>
...
...
@@ -148,7 +157,7 @@
<h2
id=
"topic1"
>
<h2>
Compartment Model for Muscone Inhalation
</h2>
<hr>
<h3>
Model Description
</h3>
<h3>
1.
Model Description
</h3>
<p>
The main focus of our project is the use of muscone as a signaling molecule to activate engineered
yeast in the gut for therapeutic purposes. Therefore, it is crucial to provide a quantitative
description and computational support for the diffusion of muscone in the body. This model describes
...
...
@@ -188,7 +197,7 @@
<li><strong>
Compartment 4
</strong>
(Target Intestine, \(I\)): \(Q_I(t)\) represents the amount of
muscone in the intestine(\(\text{mg}\)).
</li>
<p></p>
<h3>
Initial Settings and Assumptions
</h3>
<h3>
2.
Initial Settings and Assumptions
</h3>
<p>
At \(t=0\), the amount of muscone in all compartments is \(0\).
</p>
<p>
Assuming that the total amount of inhaled muscone is \(Q_{\text{inhale}}\) (\(\text{mg}\)), which is
assumed to be \(100\text{mg}\). Only \(0.5\%\) of muscone enters the systemic circulation through
...
...
@@ -196,7 +205,7 @@
synthesize lactate, we only consider the metabolism and excretion of muscone in the systemic
circulation. We only focus on the short-term process of muscone appearing in the intestine from
scratch, and the subsequent process of reaching a certain concentration can be ignored.
</p>
<h3>
Model Equations
</h3>
<h3>
3.
Model Equations
</h3>
<h4>
Inhalation Equation for Muscone
</h4>
...
...
@@ -323,7 +332,7 @@
\text{min}^{-1} \)
</p>
<h3>
System of Equations:
</h3>
<h3>
4.
System of Equations:
</h3>
<p>
In summary, we can write a system of ordinary differential equations and import it into MATLAB for
simulation:
</p>
...
...
@@ -469,7 +478,7 @@ end</div>
prepare the three-dimensional molecular model of the research object. In this study, our goal is
to simulate the interaction between muscone and the olfactory receptor Or5an6 (MOR215-1).
</li>
</ul>
<h4>
1.
Constructing the Three-Dimensional Structures of Muscone and the Receptor:
</h4>
<h4>
Constructing the Three-Dimensional Structures of Muscone and the Receptor:
</h4>
<ul>
<li><strong>
Muscone
</strong>
:
</li>
...
...
@@ -578,7 +587,7 @@ ALQRCKNKCFSQCHC</div>
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 6 Protein structure of MOR215-1
</p>
<h4>
2.
System Preparation:
</h4>
<h4>
System Preparation:
</h4>
<ul>
<li>
To study how muscone binds to the receptor, molecular docking tools such as AutoDock and Vina
are used to determine potential binding conformations and obtain docking data:
...
...
@@ -676,7 +685,7 @@ out=muscure.pdbqt</div>
</li>
</ul>
<h3>
2. Force field parameterization
</h3>
<h4>
1.
Select Force Field:
</h4>
<h4>
Select Force Field:
</h4>
<ul>
<li>
To perform molecular dynamics simulations, it is necessary to choose an appropriate molecular
force field to describe the interactions between molecules within the system. CHARMM36 was
...
...
@@ -684,7 +693,7 @@ out=muscure.pdbqt</div>
due to the absence of direct parameters for musk ketone in existing force fields, custom
parameters need to be generated to supplement it.
</li>
</ul>
<h4>
2.
Generate Force Field Parameters:
</h4>
<h4>
Generate Force Field Parameters:
</h4>
<ul>
<li>
Use Avogadro to convert to
<code>
.mol2
</code>
format, adjust file information, and then use the
software
<a
href=
"https://cgenff.com/"
>
CGenFF
</a>
to generate its CHARMM36 force field parameter
...
...
@@ -694,7 +703,7 @@ out=muscure.pdbqt</div>
</ul>
<pre><code>
perl sort_mol2_bonds.pl MUS.mol2 MUS_fix.mol2
</code></pre>
<h3>
3. Preprocessing
</h3>
<h4>
1.
Build the system:
</h4>
<h4>
Build the system:
</h4>
<ul>
<li>
Generate the topology file
<code>
MOR_processed.gro
</code>
for the receptor using GROMACS's
<code>
pdb2gmx
</code>
command.
...
...
@@ -706,7 +715,7 @@ out=muscure.pdbqt</div>
<pre><code>
python cgenff_charmm2gmx_py3_nx2.py MUS MUS_fix.mol2 MUS.str charmm36-jul2022.ff
</code></pre>
</ul>
<h4>
2.
Merge the system:
</h4>
<h4>
Merge the system:
</h4>
<ul>
<li>
Prepare the complete solvent system required for simulations using the
<code>
editconf
</code>
and
<code>
solvate
</code>
commands, merging the topology files of muscone
<code>
mus.gro
</code>
and
...
...
@@ -729,7 +738,7 @@ SOL 31227
CL 9
</code></pre>
</ul>
<h4>
3.
Energy minimization:
</h4>
<h4>
Energy minimization:
</h4>
<ul>
<li>
Perform energy minimization on the overall system to eliminate unreasonable conflicts in the
initial geometry. Achieve rapid convergence of energy through the gradient descent algorithm and
...
...
@@ -756,7 +765,7 @@ dit xvg_show -f potential.xvg</code></pre>
Minimization
</p>
</ul>
<h3>
4. Molecular Dynamics Simulation
</h3>
<h4>
1.
System Equilibration:
</h4>
<h4>
System Equilibration:
</h4>
<ul>
<li>
To achieve thermal and mechanical equilibrium of the system, simulations are conducted in two
stages: NVT (constant temperature) and NPT (constant pressure) equilibration. The system
...
...
@@ -793,7 +802,7 @@ dit xvg_show -f temperature.xvg</code></pre>
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 11 Curve of the density over time
</p>
<h4>
2.
Production Simulation:
</h4>
<h4>
Production Simulation:
</h4>
<ul>
<li>
Under the conditions of equilibrium, a long-term production simulation is conducted. This
simulation observes the time evolution characteristics of the dynamic interactions between
...
...
@@ -828,7 +837,7 @@ gmx mdrun -deffnm md_0_10</code></pre>
PyMOL.
</li>
</ul>
<h4>
1.
Trajectory Analysis:
</h4>
<h4>
Trajectory Analysis:
</h4>
<p>
To gain deeper insights into the interactions between muscone and the receptor, visualization tools
are used to make the simulation process intuitive, identifying key interaction sites and structural
...
...
@@ -882,7 +891,7 @@ gmx trjconv -s md_0_10.tpr -f md_0_10_fit.xtc -o traj.pdb -dt 10
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 15 Trajectory Analysis
</p>
<h4>
2.
RMSD (Root Mean Square Deviation) Analysis
</h4>
<h4>
RMSD (Root Mean Square Deviation) Analysis
</h4>
<ul>
<li>
RMSD provides a fundamental metric for measuring structural deviation during the simulation
...
...
@@ -921,7 +930,7 @@ xmgrace rmsd_mus.xvg</code></pre>
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 16 RMSD Analysis
</p>
<h4>
3.
Radius of Gyration (Rg) Calculation
</h4>
<h4>
Radius of Gyration (Rg) Calculation
</h4>
<ul>
<li>
The radius of gyration (Rg) is used to assess the compactness of a protein and is an important
...
...
@@ -946,7 +955,7 @@ xmgrace gyrate.xvg</code></pre>
</div>
<p
style=
"text-align: center; font-size: 0.9em; margin-top: 10px;"
>
fig 17 Radius of Gyration Calculation
</p>
<h4>
4.
Protein-Ligand Interaction Energy
</h4>
<h4>
Protein-Ligand Interaction Energy
</h4>
<ul>
<li>
By calculating the Coulomb and Lennard-Jones interaction energies within the system, the binding
...
...
@@ -989,7 +998,7 @@ dit xvg_show -f interaction_energy.xvg</code></pre>
<h2
id=
"topic3"
>
<h2>
Ordinary Differential Equation of the signal transduction of the yeast MAPK pathway
</h2>
<hr>
<h3>
Model Description
</h3>
<h3>
1.
Model Description
</h3>
<p>
In our project, we express the muscone receptor (GPCR) on the yeast cell membrane. After a
certain concentration of muscone diffuses into the intestine and binds to the receptor, it
activates the receptor, which in turn activates the G protein. The G protein dissociates into α and
...
...
@@ -1025,7 +1034,7 @@ dit xvg_show -f interaction_energy.xvg</code></pre>
<img
src=
"https://static.igem.wiki/teams/5187/wiki-model-fig/mapk.png"
alt=
"MAPK Pathway"
class=
"shadowed-image"
style=
"width: 50%; max-width: 500px;"
>
</div>
<h3>
Basic Assumptions
</h3>
<h3>
2.
Basic Assumptions
</h3>
<ol>
<li>
Since the model only simulates the signal transduction shortly after muscone activation, it
does not consider protein synthesis and degradation, assuming that the concentrations of each
...
...
@@ -1036,7 +1045,7 @@ dit xvg_show -f interaction_energy.xvg</code></pre>
factors.
</li>
</ol>
<h3>
Model Equations
</h3>
<h3>
3.
Model Equations
</h3>
<h4>
Activation of muscone Receptor
</h4>
<strong>
Reactions
</strong>
:
<div>
...
...
@@ -1848,9 +1857,9 @@ hold off;</div>
<div
class=
"row mt-4"
>
<div
class=
"col-lg-12"
>
<h2
id=
"topic4"
>
<h2>
l
actate Absorption Model
</h2>
<h2>
L
actate Absorption Model
</h2>
<hr>
<h3>
Model Description
</h3>
<h3>
1.
Model Description
</h3>
<p>
Our project alleviates IBD symptoms by secreting lactate in the intestine to weaken
autoimmunity, but it may face two aspects of doubt: first, why can't lactate or lactate
...
...
@@ -1862,7 +1871,7 @@ hold off;</div>
regulate treatment time and prevent acidosis.
</p>
<h3>
Basic Assumptions
</h3>
<h3>
2.
Basic Assumptions
</h3>
<ol>
<li>
Only the absorption process of lactate is described, without considering other effects of
lactate on the human body.
</li>
...
...
@@ -1872,7 +1881,7 @@ hold off;</div>
secrete a total amount of lactate \(a\) within time \(t_0\), secreting \(\frac{a}{n}\) of
lactate in the time interval \(\frac{t_0}{n}\).
</li>
</ol>
<h3>
Model Equation
</h3>
<h3>
3.
Model Equation
</h3>
<p>
According to Fick's law :
</p>
...
...
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