Length-Based Substructure Mutation Policies for Improved RNA Design in Simulated Annealing

RNA Design is a crucial bioinformatics problem to tailor specific RNA sequences into structures that guide our biology and medicine. Because these computer generated sequences are often statistically different from observed RNA sequence and do not fold as intended in real lab conditions, methods are developed to ensure more biological consistency. One approach is substructure restriction where any solutions are composed of observed RNA substructures recorded in a database. However, studies on this restricted problem are limited: while our Applied Research Lab's Simulated Annealing solution (SIMARD) uses substructures it only considers a single mutation policy and single method of generating substructure consistent sequences. We therefore propose two new policies of mutation: uniform, randomly modifying any structure, and length proportional, substructures are swapped randomly in proportion to their RNA length to target substructures that cover the most bases of a problem. In experiments on roughly fifty RNA Design problems, we conclude the potential value of these substructure based mutation methods resulting in solutions potentially hundreds of bases closer to the target folded structure than previous Simulated Annealing solutions.