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Study Links TNA Backbone Rigidity to Enzyme Evolvability

Researchers at UC Irvine found that threose nucleic acid enzymes face higher catalytic energy barriers than DNA due to their rigid backbone structures.

WHAT YOU NEED TO KNOW
  • DNAzyme catalysis reached optimal activity at 37 °C and weak activity at 50 °C.
  • Threozymes displayed the opposite temperature trend, requiring higher temperatures to overcome a steeper free-energy barrier.
  • Threozymes with more flexible active sites showed reduced temperature dependence during RNA cleavage.
  • The study was authored by Erica M. Lee and John C. Chaput at the University of California, Irvine.

Researchers at the University of California, Irvine, determined that threose nucleic acid enzymes face evolutionary constraints due to their rigid backbone structure, according to a study published in Nature Communications. Authors Erica M. Lee and John C. Chaput investigated how structural flexibility influences catalytic performance and adaptive potential in synthetic genetic polymers compared to natural DNA systems.

The investigation evaluated RNA-cleavage profiles by comparing the established 10-23 DNA enzyme, or DNAzyme, against two in vitro selected threose nucleic acid enzymes, termed threozymes. Testing demonstrated contrasting temperature dependencies between the systems. The DNAzyme achieved optimal reaction rates at 37 °C and showed weak activity at 50 °C.

Threozymes showed the reverse response, demonstrating higher activity at 50 °C than at 37 °C. This performance profile indicates that TNA catalysis must overcome a higher free-energy barrier than DNA catalysis. For threozymes engineered with more flexible active sites, the catalytic reaction exhibited less dependence on temperature changes.

Lee and Chaput reported that the preorganized, conformationally restricted backbone of TNA constrains its dynamism compared to DNA. The researchers identified backbone architecture as a critical parameter controlling evolvability, with direct relevance to RNA world evolutionary models and biomedical applications.

The study, accepted on July 30, 2026, and published on August 14, 2026, was supported by discretionary start-up funds from the University of California, Irvine, to Chaput. The authors acknowledged next-generation sequencing services from UCI's Genomics Research and Technology Hub alongside technical assistance from N. Setterholm and M. Hajjar.

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