GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability.

Journal: Mathematical biosciences
Published Date: Jun 27, 2025

Abstract

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Authors

  • Paolo Climaco
    Institut für Numerische Simulation, University of Bonn, Bonn, 53115, NRW, Germany. Electronic address: climacopaolo@gmail.com.
  • Noelle M Mitchell
    Department of Chemistry and Biochemistry, Los Angeles, 90095, CA, USA. Electronic address: noellemariemitchell@gmail.com.
  • Matthew J Tyler
    Department of Mathematics, University of California, Los Angeles, 90095, CA, USA. Electronic address: mtyler1059@gmail.com.
  • Kyungae Yang
    Department of Medicine, Columbia University Irving Medical Center, New York, NY, 10032, USA. Electronic address: ky2231@cumc.columbia.edu.
  • Anne M Andrews
    Department of Chemistry and Biochemistry, Los Angeles, 90095, CA, USA; California NanoSystems Institute, University of California, Los Angeles, 90095, CA, USA; Departments of Psychiatry & Biobehavioral Sciences and Bioengineering, Semel Institute for Neuroscience & Human Behavior, and Hatos Center for Neuropharmacology, University of California, Los Angeles, 90095, CA, USA. Electronic address: aandrews@mednet.ucla.edu.
  • Andrea L Bertozzi
    Department of Mathematics, University of California, Los Angeles, Los Angeles, California 90095, United States.

Keywords

External Resources

Popular Topics
Recent Journals