I am currently working on a Computer Science project where we are trying to build a large set of orthogonal single-stranded DNA sequences. The goal would be to ensure that when put in solution, the ssDNA do not interact with each other to form double-stranded DNA.
I hope that this makes sense, but my knowledge biological understanding is developing because I have a CS background. Please excuse any inadvertent errors.
As one of the first steps, we used NUPACK to predict the percent of the resulting AB complex, given two single-stranded sequences A, B in concentration 1μM each. We would use the concentration of AB to classify if the strands are likely to form double-stranded DNA.
However, we cannot use NUPACK for large sets, as we would need to do the above check against each of the other sequences, which is a quadratic problem. For a set of size 30,000 we would have to do 450 million NUPACK computations which is simply unfeasible.
So I turned to the idea of approximating NUPACK. In this paper, it is claimed that
Ideally, the thermodynamics of hybridization between a candidate probe and potential off-target sites would be modeled in silico and employed as a means of identifying probe oligos likely to only bind their intended targets in a given set of reaction conditions. Although powerful utilities such as NUPACK (52– 54) are capable of performing such simulations, the limited throughput of these programs renders a direct thermodynamic approach impractical for genome-scale probe design. However, we hypothesized that features in rapidly calculated data such as alignment scores may be predictive of thermodynamic behavior and could therefore serve as a proxy for the information that would be produced by thermodynamic simulations.
The alignment scores are then used to predict the interaction. bowtie2 is used in the paper for alignment purposes. However, the context is different as their computation is done on genome information. Very sensitive settings of bowtie2 seem to be slow (hours) on my laptop and result in enormous files (tens of GB). I used less sensitive settings as a compromise but it seems to negatively affect the LDA.
I am looking at alternative applications for alignment, but there are many alternatives (some of the more promising ones so far, in my opinion: SNAP, MMseqs2, Genoogle). Would any of these, or others not mentioned, be better suited for my purpose?
Also any other advice or suggestions are welcome!