Breakthrough in Nucleic Acid Analysis: New Algorithms Expand Capabilities of NUPACK Software Suite

Strategic Insights -

Researchers have developed new dynamic programming algorithms within the NUPACK software suite, enabling the analysis of equilibrium base-pairing properties for complex systems containing mixed-material nucleic acid strands. Currently, calculations are limited to single-material systems, but the new algorithms can analyze mixed-material systems, which are critical for modern applications in vitro, in situ, and in vivo. The mixed-material dynamic programming algorithms maintain the O(N^3) time complexity of the single-material algorithms, allowing for efficient calculation of diverse physical quantities over complex and test tube ensembles.

Key Takeaways:

  • The new algorithms enable analysis of equilibrium base-pairing properties for complex systems containing mixed-material nucleic acid strands, such as RNA/DNA and RNA/2'OMe-RNA.
  • The mixed-material dynamic programming algorithms maintain the O(N^3) time complexity of the single-material algorithms, enabling efficient calculation of diverse physical quantities.
  • The new algorithms account for the material of each nucleotide throughout the recursive process, allowing for the treatment of full complex and test tube ensembles.
  • The mixed-material models and algorithms are shown to predict RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures from the experimental literature as well as RNA/DNA melt profiles from new experiments.
  • The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems.
  • The NUPACK web app (www.nupack.org) and the NUPACK Python module can be used to perform mixed-material analyses online or locally.

Statistics:

  • The new algorithms result in a cost increase of roughly 2.0-3.5x compared to the single-material algorithms.
  • The mixed-material dynamic programming algorithms are able to calculate diverse physical quantities such as complex partition function, equilibrium complex concentrations, equilibrium base-pairing probabilities, minimum free energy secondary structure(s), and Boltzmann-sampled secondary structures.
  • The new algorithms are shown to improve accuracy in predicting RNA/DNA and RNA/2'OMe-RNA duplex melting temperatures and melt profiles.
  • The results of existing single-material algorithms are exactly reproduced when applying the new mixed-material algorithms to single-material systems.

Sources:

  • biorxiv.org/content/10.1101/2025.06.30.662484v1