  An RNA sequence is a word over an alphabet on four elements $\{A,C,G,U\}$
called bases. RNA sequences fold into secondary structures where some bases
match one another while others remain unpaired. Pseudoknot-free secondary
structures can be represented as well-parenthesized expressions with additional
dots, where pairs of matching parentheses symbolize paired bases and dots,
unpaired bases. The two fundamental problems in RNA algorithmic are to predict
how sequences fold within some model of energy and to design sequences of bases
which will fold into targeted secondary structures. Predicting how a given RNA
sequence folds into a pseudoknot-free secondary structure is known to be
solvable in cubic time since the eighties and in truly subcubic time by a
recent result of Bringmann et al. (FOCS 2016). As a stark contrast, it is
unknown whether or not designing a given RNA secondary structure is a tractable
task; this has been raised as a challenging open question by Anne Condon (ICALP
2003). Because of its crucial importance in a number of fields such as
pharmaceutical research and biochemistry, there are dozens of heuristics and
software libraries dedicated to RNA secondary structure design. It is therefore
rather surprising that the computational complexity of this central problem in
bioinformatics has been unsettled for decades.
  In this paper we show that, in the simplest model of energy which is the
Watson-Crick model the design of secondary structures is NP-complete if one
adds natural constraints of the form: index $i$ of the sequence has to be
labeled by base $b$. This negative result suggests that the same lower bound
holds for more realistic models of energy. It is noteworthy that the additional
constraints are by no means artificial: they are provided by all the RNA design
pieces of software and they do correspond to the actual practice.
