  DNA is not only the genetic material of life, but also a favorable material
for a new computing model. Various research works based on DNA computing have
been carried out in recent years. DNA sequence design is the foundation of such
research. The sequence quality directly affects the universality, robustness,
and stability of DNA computing. How to design DNA sequences depends on the
biological properties and target requirements, which is a typical combinatorial
optimization problem. In this paper, in order to design DNA sequences with
high-quality, we propose a novel meta-heuristic evolutionary algorithm, termed
the static virus spread algorithm (SVS). Through this algorithm, we focus on
the constraints of universal DNA sequence design and produce a large number of
DNA sequences with non-complementarity and small difference in melting
temperature as the objectives, and fully considering the balanced proportion of
the four bases. The computer simulation and polyacrylamide gel electrophoresis
experiments show that the high-quality DNA sequences designed by this algorithm
are effective, which is expected to provide a convenient tool for sequence
preparation before DNA biochemical operations.
