Direct RNA sequence design under codon constraints using expressive tensor-based secondary structure models

Fuente: arXiv
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Autori principali: Fornace, Mark, Wang, Christina Wuyan, Lindsey, Michael
Natura: Preprint
Pubblicazione: 2026
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author Fornace, Mark
Wang, Christina Wuyan
Lindsey, Michael
author_facet Fornace, Mark
Wang, Christina Wuyan
Lindsey, Michael
contents Nucleic acid sequence design via codon optimization is a fundamental task with applications across synthetic biology, mRNA therapeutics, and vaccine design. Given a target protein, it is a major open challenge to navigate the combinatorially large design space of codon sequences mapping to its amino acid sequence. Computational approaches generally seek to optimize simple objectives based on the codon sequence, possibly together with more complicated contributions based on secondary structure analysis. In this work, we demonstrate a direct and efficient algorithm to sample sequences from a suitable Boltzmann distribution defined in terms of the codon sequence and a fully detailed secondary structure free energy model, as well as related algorithms for exact computation of statistical quantities such as free energies, base pairing probabilities, and base and codon marginals. These algorithms draw upon a recently developed tensor-based formulation of secondary structure thermodynamics and demonstrate, for the first time, that global sequence design can be accomplished with respect to a highly accurate free energy model. Moreover, the algorithms can leverage any available CPU and GPU resources in parallel for massive computational speedups.
format Preprint
id arxiv_https___arxiv_org_abs_2604_19718
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Direct RNA sequence design under codon constraints using expressive tensor-based secondary structure models
Fornace, Mark
Wang, Christina Wuyan
Lindsey, Michael
Quantitative Methods
Nucleic acid sequence design via codon optimization is a fundamental task with applications across synthetic biology, mRNA therapeutics, and vaccine design. Given a target protein, it is a major open challenge to navigate the combinatorially large design space of codon sequences mapping to its amino acid sequence. Computational approaches generally seek to optimize simple objectives based on the codon sequence, possibly together with more complicated contributions based on secondary structure analysis. In this work, we demonstrate a direct and efficient algorithm to sample sequences from a suitable Boltzmann distribution defined in terms of the codon sequence and a fully detailed secondary structure free energy model, as well as related algorithms for exact computation of statistical quantities such as free energies, base pairing probabilities, and base and codon marginals. These algorithms draw upon a recently developed tensor-based formulation of secondary structure thermodynamics and demonstrate, for the first time, that global sequence design can be accomplished with respect to a highly accurate free energy model. Moreover, the algorithms can leverage any available CPU and GPU resources in parallel for massive computational speedups.
title Direct RNA sequence design under codon constraints using expressive tensor-based secondary structure models
topic Quantitative Methods
url https://arxiv.org/abs/2604.19718