Literature DB >> 30372611

A Logic Programming Language for Computational Nucleic Acid Devices.

Carlo Spaccasassi1, Matthew R Lakin2,3, Andrew Phillips1.   

Abstract

Computational nucleic acid devices show great potential for enabling a broad range of biotechnology applications, including smart probes for molecular biology research, in vitro assembly of complex compounds, high-precision in vitro disease diagnosis and, ultimately, computational theranostics inside living cells. This diversity of applications is supported by a range of implementation strategies, including nucleic acid strand displacement, localization to substrates, and the use of enzymes with polymerase, nickase, and exonuclease functionality. However, existing computational design tools are unable to account for these strategies in a unified manner. This paper presents a logic programming language that allows a broad range of computational nucleic acid systems to be designed and analyzed. The language extends standard logic programming with a novel equational theory to express nucleic acid molecular motifs. It automatically identifies matching motifs present in the full system, in order to apply a specified transformation expressed as a logical rule. The language supports the definition of logic predicates, which provide constraints that need to be satisfied in order for a given rule to be applied. The language is sufficiently expressive to encode the semantics of nucleic strand displacement systems with complex topologies, together with computation performed by a broad range of enzymes, and is readily extensible to new implementation strategies. Our approach lays the foundation for a unifying framework for the design of computational nucleic acid devices.

Keywords:  DNA computing; biological computation; logic programming; molecular programming; process calculus; programming language; site graph; strand graph

Mesh:

Substances:

Year:  2018        PMID: 30372611     DOI: 10.1021/acssynbio.8b00229

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  4 in total

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  4 in total

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