RNAmutants is software and a web server to compute the following:

  1. the Boltzmann partition function and average energy of all secondary structures of all k-point mutants, 0 ≤ k ≤ K, where K ≤ n is a user-specified upper bound.
  2. the k-superoptimal secondary structures, for 0 ≤ k ≤ 10. Here, the k-superoptimal secondary structure is that structure, whose energy is the minimum over all secondary structures of all i-point mutants, for i ≤ k.
In (a), the current version of RNAmutants uses (a variant of) the simple Nussinov-Jacobson energy model [2], where GC, AU, GU base pairs are assigned an energy of -3,-2,-1 respectively. The partition function for all secondary structures of (exactly) k-point mutants of a given RNA sequence is then computed by a dynamic programming method in time O(n3K) for all 0 ≤ k ≤ K, simultaneously. In (b), the energy model is essentially the Turner nearest neighbor model [1], without dangles and with a slight restriction explained in the paper cited below. The algorithm used in (b) is AMSAG [3], which uses multi-tape S-attribute grammars to describe all possible secondary structures of k-point mutants, and dynamic programming. Further details can be found in:

If you use RNAmutants, please cite the paper above.

There is an additional Web Supplement for this paper, which includes the output of RNAmutants on a number of RNA sequences.

Bibliography

  1. Mathews DH, Sabina J, Zuker M, Turner DH.
    Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.
    J Mol Biol. May 21;288(5):911-40 (1999).
  2. Nussinov R, Jacobson AB.
    Free in PMC Fast algorithm for predicting the secondary structure of single-stranded RNA.
    Proc Natl Acad Sci U S A. Nov;77(11):6309-13 (1980).
  3. Waldispühl J, Behzadi B, Steyaert JM.
    Free Full Text An approximate matching algorithm for finding (sub-)optimal sequences in S-attributed grammars.
    Bioinformatics 18 Suppl 2:S250-9 (2002).