We introduce here a heuristic approach to kinetic RNA folding that constructs secondary structures by stepwise combination of building blocks. These blocks correspond to sub-sequences and their thermodynamically optimal structures. These are determined by the standard dynamic programming approach to RNA folding. Folding trajectories are modeled at base pair resolution using the Morgan-Higgs heuristic and a barrier tree based heuristic to connect combinations of the local building blocks. Implemented in the program Kinwalker, the algorithm allows cotranscriptional folding and can be used to fold sequences of up to about 1500 nucleotides in length. A detailed comparison with several well-studied examples from the literature, including the delayed folding of bacteriophage cloverleaf structures, the ASR riboswitch, and the Hok RNA, shows an excellent agreement of predicted trajectories and experimental evidence. The software is available as part of the Vienna RNA Package.

Summary. The increasing complexity of models for prediction of the native spatial structure of RNA molecules requires visualization methods that help to analyze and understand the models and their predictions. This paper improves the visualization method for sequences of barrier trees previously published by the authors. The barrier trees of these sequences are rough topological simplifications of changing folding landscapes – energy landscapes in which kinetic folding takes place. The folding landscapes themselves are generated for RNA molecules where the number of nucleotides increases. Successive landscapes are thus correlated and so are the corresponding barrier trees. The landscape sequence is visualized by an animation of a barrier tree that changes with time. The animation is created by an adaption of the foresight layout with tolerance algorithm for dynamic graph layout problems. Since it is very general, the main ideas for the adaption are presented: construction and layout of a supergraph, and how to build the final animation from its layout. Our previous suggestions for heuristics lead to visually unpleasing results for some datasets and, generally, suffered from a poor usage of available screen space. We will present some new heuristics that improve the readability of the final animation.

Summary. Local minima and the saddle points separating them in the energy landscape are known to dominate the dynamics of biopolymer folding. Here we introduce a notion of a “folding funnel ” that is concisely defined in terms of energy minima and saddle points, while at the same time conforming to a notion of a “folding funnel ” as it is discussed in the protein folding literature. 1