Cargando…

Design of nucleic acid sequences for DNA computing based on a thermodynamic approach

We have developed an algorithm for designing multiple sequences of nucleic acids that have a uniform melting temperature between the sequence and its complement and that do not hybridize non-specifically with each other based on the minimum free energy (ΔG(min)). Sequences that satisfy these constra...

Descripción completa

Detalles Bibliográficos
Autores principales: Tanaka, Fumiaki, Kameda, Atsushi, Yamamoto, Masahito, Ohuchi, Azuma
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC549402/
https://www.ncbi.nlm.nih.gov/pubmed/15701762
http://dx.doi.org/10.1093/nar/gki235
Descripción
Sumario:We have developed an algorithm for designing multiple sequences of nucleic acids that have a uniform melting temperature between the sequence and its complement and that do not hybridize non-specifically with each other based on the minimum free energy (ΔG(min)). Sequences that satisfy these constraints can be utilized in computations, various engineering applications such as microarrays, and nano-fabrications. Our algorithm is a random generate-and-test algorithm: it generates a candidate sequence randomly and tests whether the sequence satisfies the constraints. The novelty of our algorithm is that the filtering method uses a greedy search to calculate ΔG(min). This effectively excludes inappropriate sequences before ΔG(min) is calculated, thereby reducing computation time drastically when compared with an algorithm without the filtering. Experimental results in silico showed the superiority of the greedy search over the traditional approach based on the hamming distance. In addition, experimental results in vitro demonstrated that the experimental free energy (ΔG(exp)) of 126 sequences correlated well with ΔG(min) (|R| = 0.90) than with the hamming distance (|R| = 0.80). These results validate the rationality of a thermodynamic approach. We implemented our algorithm in a graphic user interface-based program written in Java.