(Created page with "<!DOCTYPE html> <html> <head><meta charset="utf-8" /> <title>.ipynb</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> <scr...") |
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<html> | <html> | ||
<head><meta charset="utf-8" /> | <head><meta charset="utf-8" /> | ||
| − | <title> | + | <title>KinProj_Final</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script> |
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script> | <script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script> | ||
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<div class="cell border-box-sizing code_cell rendered"> | <div class="cell border-box-sizing code_cell rendered"> | ||
<div class="input"> | <div class="input"> | ||
| − | <div class="prompt input_prompt">In [ | + | <div class="prompt input_prompt">In [3]:</div> |
<div class="inner_cell"> | <div class="inner_cell"> | ||
<div class="input_area"> | <div class="input_area"> | ||
| − | <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">bokeh.plotting</span> <span class="k">import</span> <span class="n">Figure</span><span class="p">,</span> <span class="n">output_notebook</span><span class="p">,</span> <span class="n">show</span> | + | <div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">bokeh</span> |
| + | <span class="kn">from</span> <span class="nn">bokeh.plotting</span> <span class="k">import</span> <span class="n">Figure</span><span class="p">,</span> <span class="n">output_notebook</span><span class="p">,</span> <span class="n">show</span> | ||
<span class="kn">import</span> <span class="nn">math</span> | <span class="kn">import</span> <span class="nn">math</span> | ||
<span class="kn">import</span> <span class="nn">scipy</span> | <span class="kn">import</span> <span class="nn">scipy</span> | ||
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<div class="bk-root"> | <div class="bk-root"> | ||
<a href="https://bokeh.pydata.org" target="_blank" class="bk-logo bk-logo-small bk-logo-notebook"></a> | <a href="https://bokeh.pydata.org" target="_blank" class="bk-logo bk-logo-small bk-logo-notebook"></a> | ||
| − | <span id=" | + | <span id="1055">Loading BokehJS ...</span> |
</div> | </div> | ||
</div> | </div> | ||
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| − | <div id=" | + | <div id="81a33e18-2e22-4db6-8eb3-ba89537a39b0"></div> |
<div class="output_subarea output_javascript "> | <div class="output_subarea output_javascript "> | ||
<script type="text/javascript"> | <script type="text/javascript"> | ||
| − | var element = $('# | + | var element = $('#81a33e18-2e22-4db6-8eb3-ba89537a39b0'); |
(function(root) { | (function(root) { | ||
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function display_loaded() { | function display_loaded() { | ||
| − | var el = document.getElementById(" | + | var el = document.getElementById("1055"); |
if (el != null) { | if (el != null) { | ||
el.textContent = "BokehJS is loading..."; | el.textContent = "BokehJS is loading..."; | ||
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document.getElementsByTagName("head")[0].appendChild(s); | document.getElementsByTagName("head")[0].appendChild(s); | ||
} | } | ||
| − | };var element = document.getElementById(" | + | };var element = document.getElementById("1055"); |
if (element == null) { | if (element == null) { | ||
| − | console.log("Bokeh: ERROR: autoload.js configured with elementid ' | + | console.log("Bokeh: ERROR: autoload.js configured with elementid '1055' but no matching script tag was found. ") |
return false; | return false; | ||
} | } | ||
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root._bokeh_failed_load = true; | root._bokeh_failed_load = true; | ||
} else if (force !== true) { | } else if (force !== true) { | ||
| − | var cell = $(document.getElementById(" | + | var cell = $(document.getElementById("1055")).parents('.cell').data().cell; |
cell.output_area.append_execute_result(NB_LOAD_WARNING) | cell.output_area.append_execute_result(NB_LOAD_WARNING) | ||
} | } | ||
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| − | <div class="bk-root" id=" | + | <div class="bk-root" id="aa1a842c-a760-4d97-b7c8-4124f3e1f35a" data-root-id="1059"></div> |
</div> | </div> | ||
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| − | <div id=" | + | <div id="37d359ff-c239-4abd-a0ab-e18e8ba99d7a"></div> |
<div class="output_subarea output_javascript "> | <div class="output_subarea output_javascript "> | ||
<script type="text/javascript"> | <script type="text/javascript"> | ||
| − | var element = $('# | + | var element = $('#37d359ff-c239-4abd-a0ab-e18e8ba99d7a'); |
(function(root) { | (function(root) { | ||
function embed_document(root) { | function embed_document(root) { | ||
| − | + | var docs_json = 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DNA = parseFloat(DNA.value)\n Cas1 = parseFloat(Cas1.value)\n Cas2 = parseFloat(Cas2.value)\n SO = parseInt(SO.value)\n CpO = 0\n CEBL = 0\n if(DNA < Cas1 && DNA < Cas2){CEBL = DNA}else{if(Cas1>Cas2){CEBL = Cas2}else{CEBL = Cas1}}\n Km = parseFloat(Km.value)\n data = source.data\n kcat = 2.22\n dt1=data['x1']\n C=data['y1']\n b = 0\n\n for (var i = 0; i < 3600; i++)\n {\n if (i == 0)\n {\n Cp = CpO\n }\n else\n {\n Cp = Cp + ((CEBL*kcat*(SO - Cp))*(dt1[i] - dt1[i-1])/(Km + (SO - Cp)))\n if (Cp > SO)\n {\n b = i-1\n break;\n }\n }\n C[i] = Cp\n }\n b.value = b\n source.change.emit();\n"},"id":"1039","type":"CustomJS"},{"attributes":{"callback":{"id":"1040","type":"CustomJS"},"icon":null,"label":"Reset"},"id":"1049","type":"Button"},{"attributes":{"callback":{"id":"1039","type":"CustomJS"},"value":"3599"},"id":"1047","type":"TextInput"},{"attributes":{"callback":{"id":"1039","type":"CustomJS"},"end":10,"start":0,"step":0.5,"title":"[sgRNA-dCas9_1], nM","value":5},"id":"1042","type":"Slider"},{"attributes":{"callback":{"id":"1039","type":"CustomJS"},"end":5.0,"start":0,"step":0.5,"title":"[DNA], nM","value":2.5},"id":"1041","type":"Slider"},{"attributes":{"text":"time, needed to detect signal"},"id":"1048","type":"PreText"},{"attributes":{"args":{"Cas1":{"id":"1042","type":"Slider"},"Cas2":{"id":"1043","type":"Slider"},"DNA":{"id":"1041","type":"Slider"},"SO":{"id":"1044","type":"Slider"},"source":{"id":"1038","type":"ColumnDataSource"}},"code":"\n A = 0.2\n Em = 20000*Math.pow(10,-6)\n L = 1\n DNA = 2.5\n Cas1 = 5 \n Cas2 = 5 \n SO = (A/(Em*L))*1000 \n CpO = 0\n CEBL = 0\n if(DNA < Cas1 && DNA < Cas2){CEBL = DNA}else{if(Cas1>Cas2){CEBL = Cas2}else{CEBL = Cas1}}\n Km = 10*1000\n kcat = 2.22\n data = source.data\n dt1=data['x1']\n C=data['y1']\n b = 0\n\n for (var i = 0; i < 3600; i++)\n {\n if (i == 0)\n {\n Cp = CpO\n }\n else\n {\n Cp = Cp + ((CEBL*kcat*(SO - Cp))*(dt1[i] - dt1[i-1])/(Km + (SO - Cp)))\n if (Cp > SO)\n {\n b = i-1\n break\n }\n }\n C[i] = Cp\n }\n SO.value = A/(Em*L)\n DNA.value = 2\n Cas1.value = 3\n Cas2.value = 3\n Km.value = (10).toString()\n source.change.emit();\n"},"id":"1040","type":"CustomJS"},{"attributes":{"children":[{"id":"1041","type":"Slider"},{"id":"1042","type":"Slider"},{"id":"1043","type":"Slider"},{"id":"1044","type":"Slider"},{"id":"1049","type":"Button"}]},"id":"1058","type":"WidgetBox"},{"attributes":{},"id":"1023","type":"PanTool"},{"attributes":{"plot":null,"text":"\u0417\u0430\u0432\u0438\u0441\u0438\u043c\u043e\u0441\u0442\u044c \u043a\u043e\u043d\u0446\u0435\u043d\u0442\u0440\u0430\u0446\u0438\u0438 \u043f\u0440\u043e\u0434\u0443\u043a\u0442\u0430 \u0440\u0430\u0441\u0449\u0435\u043f\u043b\u0435\u043d\u0438\u044f \u043d\u0438\u0442\u0440\u043e\u0446\u0435\u0444\u0438\u043d\u0430 \u0431\u0435\u0442\u0430-\u043b\u0430\u043a\u0442\u0430\u043c\u0430\u0437\u043e\u0439 \u043e\u0442 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| − | var render_items = [{"docid":" | + | var render_items = [{"docid":"585cb8b3-b190-4b37-aa68-9e83ebbda4c3","roots":{"1059":"aa1a842c-a760-4d97-b7c8-4124f3e1f35a"}}]; |
root.Bokeh.embed.embed_items_notebook(docs_json, render_items); | root.Bokeh.embed.embed_items_notebook(docs_json, render_items); | ||
Latest revision as of 20:16, 16 October 2019
import bokeh
from bokeh.plotting import Figure, output_notebook, show
import math
import scipy
import numpy as np
from bokeh.layouts import widgetbox, row, column
from bokeh.models import CustomJS, ColumnDataSource, Slider, Button, PreText, TextInput
A = 0.35
Em = 20000*math.pow(10,-6)
L = 1
DNA = 2.5 #(наномоль/л) - концентрация ДНК
Cas1 = 5 #(наномоль/л) - концентрация dCas9_1
Cas2 = 5 #(наномоль/л) - концентрация dCas9_2
print((A/(Em*L))*1000)
SO = ((A/(Em*L))*1000)*4 + 10000 #(наномоль/л) - концентрация субстрата
CpO = 0
if (DNA < Cas1 and DNA < Cas2):
CEBL = DNA
else:
if(Cas1>Cas2):
CEBL = Cas2
else:
CEBL = Cas1
Km = 10*1000 #(наномоль/л)
kcat = 2.22
dt1=[dt for dt in range(0, 3600)] #Изменение времени в секундах
C = [0]*3600
b = 0
#Построение графика
y1 = list(C)
x1 = list(dt1)
source = ColumnDataSource(data=dict(x1=x1, y1=y1))
fig = Figure(plot_width=700, plot_height=500, title="Зависимость концентрации продукта расщепления нитроцефина бета-лактамазой от времени",x_axis_label='Время, с', y_axis_label='Концентрация продукта, нМ')
for i in range(0,3600):
if (i == 0):
Cp = CpO
else:
Cp = Cp + ((kcat*CEBL*(SO - Cp))*(dt1[i] - dt1[i-1])/(Km + (SO - Cp)))
if (Cp >= (A/(Em*L))*1000):
b = i
y1[i] = Cp
print(Cp)
dt1 = [dt for dt in range(0,b)]
x1 = list(dt1)
source = ColumnDataSource(data=dict(x1=x1, y1=y1))
#Перестройка графика при изменении параметров
#Общий callback
callback = CustomJS(args=dict(source=source), code="""
DNA = parseFloat(DNA.value)
Cas1 = parseFloat(Cas1.value)
Cas2 = parseFloat(Cas2.value)
SO = parseInt(SO.value)
CpO = 0
CEBL = 0
if(DNA < Cas1 && DNA < Cas2){CEBL = DNA}else{if(Cas1>Cas2){CEBL = Cas2}else{CEBL = Cas1}}
Km = parseFloat(Km.value)
data = source.data
kcat = 2.22
dt1=data['x1']
C=data['y1']
b = 0
for (var i = 0; i < 3600; i++)
{
if (i == 0)
{
Cp = CpO
}
else
{
Cp = Cp + ((CEBL*kcat*(SO - Cp))*(dt1[i] - dt1[i-1])/(Km + (SO - Cp)))
if (Cp > SO)
{
b = i-1
break;
}
}
C[i] = Cp
}
b.value = b
source.change.emit();
""")
reset = CustomJS(args=dict(source=source), code="""
A = 0.2
Em = 20000*Math.pow(10,-6)
L = 1
DNA = 2.5
Cas1 = 5
Cas2 = 5
SO = (A/(Em*L))*1000
CpO = 0
CEBL = 0
if(DNA < Cas1 && DNA < Cas2){CEBL = DNA}else{if(Cas1>Cas2){CEBL = Cas2}else{CEBL = Cas1}}
Km = 10*1000
kcat = 2.22
data = source.data
dt1=data['x1']
C=data['y1']
b = 0
for (var i = 0; i < 3600; i++)
{
if (i == 0)
{
Cp = CpO
}
else
{
Cp = Cp + ((CEBL*kcat*(SO - Cp))*(dt1[i] - dt1[i-1])/(Km + (SO - Cp)))
if (Cp > SO)
{
b = i-1
break
}
}
C[i] = Cp
}
SO.value = A/(Em*L)
DNA.value = 2
Cas1.value = 3
Cas2.value = 3
Km.value = (10).toString()
source.change.emit();
""")
#Слайдеры
DNAsl = Slider(title = '[DNA], nM', start=0, end=DNA*2, value=DNA, step=0.5, callback=callback)
callback.args["DNA"] = DNAsl
reset.args["DNA"] = DNAsl
Casasl = Slider(title = '[sgRNA-dCas9_1], nM', start=0, end=Cas1*2, value=Cas1, step=0.5, callback=callback)
callback.args["Cas1"] = Casasl
reset.args["Cas1"] = Casasl
Casbsl = Slider(title = '[sgRNA-dCas9_2], nM', start=0, end=Cas2*2, value=Cas2, step=0.5, callback=callback)
callback.args["Cas2"] = Casbsl
reset.args["Cas2"] = Casbsl
SOsl = Slider(title = '[Nitrocefin], nM', start=SO/2, end=SO*2, value=SO, step=5, callback=callback)
callback.args["SO"] = SOsl
reset.args["SO"] = SOsl
#Textbox'ы
IKm = TextInput(callback=callback, value=str(Km))
callback.args["Km"] = IKm
TKm = PreText(text = "Km")
ITime = TextInput(callback=callback, value=str(b))
callback.args["b"] = ITime
Ttime = PreText(text = "time, needed to detect signal")
#Кнопка Reset
resetbt = Button(callback=reset,label="Reset")
fig.circle('x1','y1', source=source, size = 1.5, color = 'red')
output_notebook()
show(column(row(fig,widgetbox(IKm,TKm,ITime,Ttime)),widgetbox(DNAsl,Casasl,Casbsl,SOsl,resetbt)))
Для описания кинетики реакций, используемых в нашем проекте, мы разделили их на три части: • Взаимодействие dCas9 с ДНК (связывание) • Взаимодействие разъединенных доменов бета-лактамазы с образованием молекулы фермента • Фермент-субстратное взаимодействие
Исходя из источников литературы, константы связывания dCas9 с ДНК велики, поэтому ими можно пренебречь, следовательно, в рамках модели считается, что связывание dCas9 c ДНК происходит мгновенно.
Фермент-субстратное взаимодействие описывается уравнением Михаэлиса-Ментен:
$$\frac{d[P]}{dt} = \frac{kcat[E0][S]}{Km + [S]}$$
Модель представляет собой интерактивный график зависимости концентрации продукта гидролиза нитроцефина бета-лактамазой от времени. Уравнение имеет следующий вид:
$$[P] = [P] + \frac{kcat[E][S]dt}{Km + [S]}$$