Difference between revisions of "Team:Heidelberg/Modeling"

 
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<h3 class="basicheader"> Modeling </h3>
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<h3 class="basicheader"> Overview Modeling</h3>
 
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Nowadays detection of new aptamers is dependent on systematic evolution of ligands by exponential enrichment (SELEX)<x-ref>ellington1990</x-ref><x-ref>tuerk1990</x-ref><x-ref>bartel1993</x-ref>. This process involves numerous cycles to select potential candidates from a random pool. These selected sequences have to be further mutated over and over again in order to generate an aptamer with a high affinity.
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In our subprojects on the development of switchable aptamer sensors and on aptamer-based small-molecule sensing, we wanted to determine affinities and kinetic parameters of enzymes. For this purpose, we constructed mathematical models of coupled ordinary differential equations (ODEs) and used experimental data for parameter estimations.
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To substitute this very time consuming and expensive SELEX we developed a new software with different featuressoftware <b>M</b>aking <b>A</b>patmers <b>W</b>ithout <b>S</b>ELEX (MAWS), which enables us to efficiently generate new aptamers within less than a day compared. Thus we were able to predict many aptamers by MAWS and validated them in different assay during the summer. If we had been restricted to use the existing methods this would not have been possible.
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Thereby, we could successfully characterize affinities of switchable aptamer sensors to their targets and the switching behavior of software-designed stems. With regard to our in-vitro transcription subproject, we could test different hypotheses on the function of a polymerase based on model selection. We learned that the binding kinetics of the polymerase to its target is an important determinant for the transcription kinetics. The surprising result that increasing the concentration of the polymerase results in a hyper-linear gain of products could be mechanistically verified by a decrease of polymerase accuracy at higher ATP to polymerase ratios. In the following sections the two models shall be described. <br/> <br/>
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Every aptamer bears the potential to be used as module in order to generate switchable aptazymes.<x-ref>Soukup</x-ref> In order to obtain the best possible fusion of an aptamer with a ribozyme or DNAzyme another SELEX with several cycles would have been needed. In order to bypass this second time-cosuming SELEX we developed <b>J</b>oining <b>A</b>patmers <b>W</b>ithout <b>S</b>ELEX (JAWS). We are able to optimize the transition element to create a bistable system where either one conformation is favored in presence of the ligand while the other one is in absence of the ligand.
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MAWS enables the scientific community the possibility to generate aptamers for any ligand <i>in silico</i>. The JAWS generated modules can be fused to a ribozyme or DNAzyme to create ligand-dependent tools. JAWS thus bypasses the requirement for SELEX and, in conjunction with MAWS, enables rapid design-prototype-test cycles, drastically improving the stardardization and modularization of nucleic acid-based devices.
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Get further information about <a href="software/maws">MAWS</a>
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Assisting the optimization of switchable <a href="https://2015.igem.org/Team:Heidelberg/Modeling/aptakinetics">aptamer sensors</a> by mathematical modeling <br/> <br/>
  
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or about <a href="software/jaws">JAWS</a>
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Studying <a href="https://2015.igem.org/Team:Heidelberg/Modeling/rtsms">determinants of polymerase efficiency</a> based on an aptamer sensor
  
 
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Latest revision as of 05:13, 2 October 2015

Overview Modeling

In our subprojects on the development of switchable aptamer sensors and on aptamer-based small-molecule sensing, we wanted to determine affinities and kinetic parameters of enzymes. For this purpose, we constructed mathematical models of coupled ordinary differential equations (ODEs) and used experimental data for parameter estimations. Thereby, we could successfully characterize affinities of switchable aptamer sensors to their targets and the switching behavior of software-designed stems. With regard to our in-vitro transcription subproject, we could test different hypotheses on the function of a polymerase based on model selection. We learned that the binding kinetics of the polymerase to its target is an important determinant for the transcription kinetics. The surprising result that increasing the concentration of the polymerase results in a hyper-linear gain of products could be mechanistically verified by a decrease of polymerase accuracy at higher ATP to polymerase ratios. In the following sections the two models shall be described.

Assisting the optimization of switchable aptamer sensors by mathematical modeling

Studying determinants of polymerase efficiency based on an aptamer sensor