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Models and Algorithms for Equilibrium Analysis of Mixed-Material Nucleic Acid Systems.

Avinash Nanjundiah1, Mark E Fornace1,2, Samuel J Schulte1

  • 1Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, California 91125, United States.

ACS Synthetic Biology
|January 7, 2026
PubMed
Summary
This summary is machine-generated.

New NUPACK algorithms enable analysis of mixed-material nucleic acid systems, crucial for in vitro and in vivo applications. These models efficiently calculate equilibrium properties for RNA/DNA and RNA/2'OMe-RNA complexes.

Keywords:
2′OMe-RNABoltzmann-sampled secondary structuresDNANUPACKRNAchimeric casecomplex ensemblecomplex partition functiondynamic programming algorithmequilibrium base-pairing probabilitiesequilibrium complex concentrationshybrid caseminimum free energy secondary structuremixed materialssalt correctionsodiumtest tube ensemble

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Area of Science:

  • Computational Biology
  • Biophysics
  • Molecular Biology

Background:

  • NUPACK software currently analyzes single-material nucleic acid systems (all-RNA or all-DNA).
  • Mixed-material nucleic acid systems are vital for advanced in vitro, in situ, and in vivo applications.
  • Existing models lack the capability to analyze systems with both RNA and DNA components.

Purpose of the Study:

  • To develop physical models and dynamic programming algorithms for analyzing mixed-material nucleic acid systems.
  • To enable nucleotide-resolution specification of material composition in complex and test tube ensembles.
  • To extend NUPACK's capabilities to RNA/DNA and RNA/2'OMe-RNA systems.

Main Methods:

  • Developed new physical models and dynamic programming algorithms for mixed-material systems.
  • Constructed free energy parameter sets for RNA/DNA and RNA/2'OMe-RNA by combining existing parameters.
  • Implemented new dynamic programming recursions that account for nucleotide-specific material composition.

Main Results:

  • Mixed-material algorithms maintain O(N^3) time complexity, similar to single-material algorithms.
  • Calculations for complex partition function, equilibrium concentrations, and base-pairing probabilities are now possible for mixed systems.
  • Significantly enhanced accuracy in predicting duplex melting temperatures and melt profiles for RNA/DNA and RNA/2'OMe-RNA systems.

Conclusions:

  • The new algorithms enable efficient and accurate analysis of mixed-material nucleic acid ensembles.
  • These advancements are critical for designing and understanding complex nucleic acid-based applications.
  • Mixed-material analyses are accessible via the NUPACK web app and Python module.