Biomod/2013/NanoUANL/Enzyme: Difference between revisions

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<html>  <script type="text/x-mathjax-config"> MathJax.Hub.Config({tex2jax: {inlineMath: [['$','$'], ['\$','\$']]}}); MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: "AMS" } } }); </script> <script type="text/javascript" src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script> <head> <title></title> </head> <body>    ENZYME   <img alt="" src="http://openwetware.org/images/e/e4/UANLEnzyme1.jpg" style="width: 410px; height: 385px;" /> Enzyme In biological systems, chemical transformations are typically accelerated by enzymes, macromolecules capable of turning one or more compounds into others (substrates and products). The activity is determined greatly by their three-dimensional structure. Most enzymes are proteins, although several catalytic RNA molecules have been identified. They may also need to employ organic and inorganic cofactors for the reaction to occur. The process is based upon the diminishment of the activation energy needed for a reaction, greatly increasing its rate of reaction. The rate enhancement provided by these proteins can be as high as 10^19, while maintaining high substrate specificity. Because of this, reaction rates are millions of times faster than un-catalyzed reactions. Enzymes are not consumed by the reactions that they take part in, and they do not alter the equilibrium. Enzyme activity can be affected by a wide variety of factors. Inhibitors and activators intervene directly in the reaction rate, environmental factors like temperature, pressure, pH and substrate concentration also play a part in these kinetics. For temperature and pH, usually exist a range of values for which the enzyme works better (optimal conditions). The enzyme activity lowers dramatically as you get farther away from this range of values. As for concentration, other kind of relationship is observed. With increasing concentration, enzyme activity increases, until we reach the most optimal performance. Further increase of concentration generally won’t have an impact on the enzyme activity. Being able to determine these conditions allow us to manipulate the enzyme activity, thus achieving greater control over the reaction. Michaelis-Menten kinetics Michaelis-Menten kinetics is one of the oldest models for describing the catalytic activity of enzymes. The reaction cycle is divided into two basic steps: the reversible binding between the enzyme and substrate to form an intermediate complex, and the irreversible catalytic step to generate the product and release the enzyme; in which the first step is affected by the constants k1 and k-1, whereas the irreversible step only takes into account  k2. \begin{equation} E + S \leftrightarrow ES \rightarrow E^0 + P \end{equation} The rate of consumption can be expressed by the formation of the ES complex in the following equation: \begin{equation} \frac{d[ES]}{dt}=k_1[E][S]-k_{-1}[ES]-k_2[ES] \end{equation} Using a steady-approximation and rearranging eq. 2 we obtain: \begin{equation} [ES]= \frac{[E][S]}{K_M+[S]} \end{equation} where ''KM'' is the Michaelis constant defined as \begin{equation} K_M= \frac{k_{-1} + k_2}{k_1} \end{equation} As it was mentioned in the introduction, single-enzyme studies have proven that the "traditional" enzyme kinetics do not apply, and a new approach is needed. Enzyme concentration is meaningless in a single-molecule level, so it is more appropriate to consider the probability ''PE(t)'' for the enzyme to find a catalytically active enzyme in a time ''t'' in the process. This is because the reaction is a stochastic event. Therefore, the rate equations of each species are: \begin{equation} \frac{d[E]}{dt}=-k_1[E][S]+k_{-1}[ES] \end{equation} \begin{equation} \frac{d[ES]}{dt}=k_1[E][S]-(k_{-1}+k_2)[ES] \end{equation} \begin{equation} \frac{d[E^0]}{dt}=\frac{d[P]}{dt}=k_2[ES] \end{equation} </body> where ''t'' is the elapsed time, the initial conditions are [ES]=0 and [E0]=0 at ''t''=0. To derive the rate equations that describe the corresponding single-molecule Michaelis-Menten kinetics, the concentrations in equations 5-7 are replaced by the probabilities P of finding the single enzyme molecule in the states E, ES, and E0 , leading to the equations: \begin{equation} \frac{dP_E(t)}{dt}=-k_1^0P_E(t)+k_{-1}P_{ES}(t) \end{equation} \begin{equation} \frac{dP_{ES}(t)}{dt}=k_1^0P_E(t)-(k_{-1}+k_2)P_{ES}(t) \end{equation} \begin{equation} \frac{dP_E^0(t)}{dt}=k_2P_{ES}(t) \end{equation} These equations must satisfy the conditions ''PE''(0)=1, ''PES''(0)=0 and ''PE0''=0 at ''t''=0 (start of the reaction). Also, ''PE''(t) + ''PES''(t) + ''PE0''(t)=1. The rate constant ''k''10 can be taken as ''k''10=''k''1[S], assuming [S] is time-independent. Given that a single enzyme is unlikely to deplete all the substrate presence, [S] can be considered constant, virtually being unaffected. Equations 8-10 become a system of linear first-order differential equations that can be solved exactly for ''PE''(t), ''PES''(t) and ''PE0''(t). Knowing ''PE0''(t), the probability that a turnover occurs between ''t'' and ''t +'' Δ''t'' is ''f(t)Δt, the same as Δ''PE0''(t). Taking this into account, in the limit of infinitesimal Δ''t'': \begin{equation} f(t)=\frac{dP_E^0(t)}{dt}=k_2P_{ES}(t) \end{equation} Solving equations 8-10, and using equation 11: \begin{equation} f(t)=\frac{k_1k_2[S]}{2A}[exp(A+B)t-exp(B-A)t] \end{equation} in which: \begin{equation} A=\sqrt{(k_1[S]+k_{-1}+k_2)^2/4-k_1k_2[S]} \end{equation} \begin{equation} B=- \frac{k_1[S]+k_{-1}+k_2}{2} \end{equation} when the substrate concentration dependence [S] has been shown throught the relation ''k10 = k1''[S]. With these equations, we have used different values for ''k-1'' and [S], using values found in literature. At the first moment of ''f(t)'', which would be the mean waiting time for the reaction, ''<t>'', and its reciprocal can be taken as the average reaction rate.  Starting eq. 12: \begin{equation} \frac{1}{(t)}=-\frac{(A^2-B^2)^2}{2Bk_1k_2[S]} \end{equation} \begin{equation} \frac{1}{(t)}=\frac{k_2[S]}{[S]+K_M} \end{equation} Randomness parameter The probability density ''f(t)'' completely characterizes single-enzyme kinetics, with the ''n''th moment being given by: \begin{equation} f(t)= \int_0^\infty dt f(t)t^n \end{equation} Although the first moment of ''f(t)'' can be described eq. 11, higher moments of ''f(t)'' are usually calculated along with a "randomness parameter". Implying no dynamic disorder, ''r'' is given by: \begin{equation} r=\frac{(k_1[S]+k_2+k_{-1})^2-2k_1k_2[S]}{(k1[S]+k_2+k_{-1})^2} \end{equation} As substrate concentration increases, ''r'' decreases, indicating the formation of an intermediate enzyme-substrate complex ES. At even higher concentrations, the catalytic step limits the reaction, as is the same when concentration is low and the substrate binding limits the rate. </html>

@@ Line 133: / Line 133: @@
 <p>
 			<p>
-			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><span style="font-size: 12px;">At the first moment of &#39;&#39;f(t)&#39;&#39;, </span></span></p>
+			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><span style="font-size: 12px;">At the first moment of &#39;&#39;f(t)&#39;&#39;, which would be the mean waiting time for the reaction, &#39;&#39;&lt;t&gt;&#39;&#39;, and its reciprocal can be taken as the average reaction rate.&nbsp; Starting eq. 12:</span></span></p>
-\<t> = \int_0^\infty dt tf(t)
+\begin{equation}
+\frac{1}{(t)}=-\frac{(A^2-B^2)^2}{2Bk_1k_2[S]}
+\end{equation}
+\begin{equation}
+\frac{1}{(t)}=\frac{k_2[S]}{[S]+K_M}
+\end{equation}
 <p>
-			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><span style="font-size: 12px;">&nbsp;which would be the mean waiting time for the reaction, &#39;&#39;&lt;t&gt;&#39;&#39;, and its reciprocal can be taken as the average reaction rate.&nbsp; Starting eqtn 12:</span></span></p>
+			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><strong><span style="font-size: 14px;">Randomness parameter</span></strong><br />
+			<span style="font-size: 12px;">The probability density &#39;&#39;f(t)&#39;&#39; completely characterizes single-enzyme kinetics, with the &#39;&#39;n&#39;&#39;&lt;sup&gt;th&lt;/sup&gt; moment being given by:</span></span></p>
 \begin{equation}
-\frac{1}{<t>}=-\frac{(A^2-B^2)^2}{2Bk_1k_2[S]}
+f(t)= \int_0^\infty dt f(t)t^n
 \end{equation}
+<p>
+			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><span style="font-size: 12px;">Although the first moment of &#39;&#39;f(t)&#39;&#39; can be described eq. 11, higher moments of &#39;&#39;f(t)&#39;&#39; are usually calculated along with a &quot;randomness parameter&quot;. Implying no dynamic disorder, &#39;&#39;r&#39;&#39; is given by: </span></span></p>
 \begin{equation}
-\frac{1}{<t>}=\frac{k_2[S]}{[S]+K_M}
+r=\frac{(k_1[S]+k_2+k_{-1})^2-2k_1k_2[S]}{(k1[S]+k_2+k_{-1})^2}
 \end{equation}
 <p>
-			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><strong><span style="font-size: 14px;">Randomness parameter</span></strong><br />
+			<span style="font-family:trebuchet ms,helvetica,sans-serif;"><span style="font-size: 12px;">As substrate concentration increases, ''r'' decreases, indicating the formation of an intermediate enzyme-substrate complex ES. At even higher concentrations, the catalytic step limits the reaction, as is the same when concentration is low and the substrate binding limits the rate.
-			<span style="font-size: 12px;">The probability density &#39;&#39;f(t)&#39;&#39; completely characterizes single-enzyme kinetics, with the &#39;&#39;n&#39;&#39;&lt;sup&gt;th&lt;/sup&gt; moment being given by:</span></span></p>
+</span></span></p>

Biomod/2013/NanoUANL/Enzyme: Difference between revisions

Revision as of 16:05, 26 October 2013

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