@InProceedings{Backofen:IDA2001, author = {Rolf Backofen}, title = {RNA-Sequence-Structure Properties and Selenocysteine Insertion}, booktitle = {Proc. of the Fourth International Symposium on Intelligent Data Analysis}, year = 2001, pages = {187--197}, editor= {Frank Hoffmann and David J. Hand and Niall Adams and Douglas Fisher and Gabriela Guimaraes}, series = {Lecture Notes in Computer Science}, volume = 2189, publisher = {Springer Verlag}, abstract = {Selenocysteine (Sec) is a recently discovered 21st amino acid. Selenocysteine is encoded by the nucleotide triplet UGA, which is usually interpreted as a STOP signal. The insertion of selenocysteine requires an additional signal in form of a SECIS-element (\textbf{Se}leno\textbf{c}ysteine \textbf{I}nsertion \textbf{S}equence). This is an mRNA-motif, which is defined by both sequence-related and structure-related properties. The bioinformatics problem of interest is to design new selenoproteins (i.e., proteins containing selenocysteine), since seleno variants of proteins are very useful in structure analysis. When designing new bacterial selenoproteins, one encounters the problem that the SECIS-element itself is translated (and therefore encodes a subsequence of the complete protein). Hence, changes on the level of mRNA made in order to generate a SECIS-element will also modify the amino acid sequence. Thus, one searches for an mRNA that is maximally similar to a SECIS-element, and for which the encoded amino acid sequence is maximally similar to the original amino acid sequence. In addition, it must satisfy the constraints imposed by the structure. Though the problem is NP-complete if arbitrary structural constraints are allowed, it can be solved efficiently when we consider the structures as used in SECIS-elements. The remaining problem is to generate a description of the SECIS-element (and its diversity) based on the available data.} }