An Agent-Oriented Simulation of RNA Folding and its Application to the Analysis of RNA Conformational Spaces

摘要

We present a stochastic agent-oriented simulation of ribonucleic acid (RNA) folding that enables the analysis of RNA conformational spaces. The simulation implements a heuristic algorithm that models the folding of RNA as the sequential selection of helices for incorporation into a nascent RNA conformation. The algorithm introduces a number of modifications to similar heuristic algorithms, including an "opportunity cost" function that takes into account the ensemble of helices that become incompatible with the nascent conformation due to the selection of a given helix, and a "direction" constraint that drastically reduces the number of selection steps involved in the assembly of new RNA conformations. Each new conformation is assembled in fewer than n selection steps, where n is the length of the folded sequence. This represents a significant improvement over a similar algorithm that performs an average of 5N selection steps, where N, the number of helices, is known to increase quadratically with the length of the folded sequence. Another important feature of the simulation that is implicit in its agent-oriented implementation is its ability to concurrently generate large numbers of probable or suboptimal conformations of a given RNA sequence.