Stability
Stability is one of the most vital factors in DNA origami. Only when the structure is stable enough are we allowed to assemble different components, to initiate conformational changes, and to observe our results. The importance of stability cannot be stressed enough.
Being stable means that first, our monomers are strong enough by themselves, and second, the protruding single strands DNA can pair in the desired way. Therefore, we developed two methods to make sure that our products meet the standards.
CanDo
To begin with, in order to prove that our monomers can withstand room temperature, we went to the website "CanDo" to do the testings. CanDo offers rapid computational feedback on the 3D structure of programmed DNA assemblies according to our designs in caDNAno, enabling us to assess our products' shape and flexibility.
Below are the testing results. The 3D CanDo predicted shapes with flexibility indicated as heat-maps, where red and blue respectively indicates high and low flexibility.
Figure 1: Left lid as generated by CanDo (side view)
Figure 2: Right lid as generated by CanDo (side view)
Figure 3: The base as generated by CanDo (top view & side view)
ssDNA Alignment with Python
Since our device depends heavily on the binding between single stranded DNA that form preferable pairs, it is important that we make sure the ssDNA we designed will not only pair with each other as expected, but also avoid wrong pairings. However, with over 35 ssDNA it is extremely difficult to prove the correctness of our sequence design. Therefore, we decided to let computer to do the task.
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We developed an algorithm, one that would take two ssDNA sequence as input, and output their most probable alignment and the number of paired bases between them.
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The algorithm would try every possible alignment by shifting one of the sequence one nucleotide at a time, as shown below.
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In the end, the one alignment that is most probable will be output. We then check our design correctness and altered the sequence accordingly. After that, we will test out the free energy of these paring to make sure they're bonds are strong enough.
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With this algorithm, we can easily detect wrong pairings when designing sequences and change them right away. We no longer have to worry that incorrect pairings will affect our results.
Here is the link to our program and the outcome.