RNA Structure Prediction and Folding Algorithms

RNA molecules play essential roles in fundamental biological mechanisms, including the regulation of gene expression and the catalysis of enzymatic reactions. Deciphering RNA structure is critical to understanding its diverse functions, defining its roles within cellular contexts, and enabling the design of RNA-targeted therapeutic strategies. This chapter offers a comprehensive overview of computational techniques developed for predicting RNA secondary and tertiary structures. We begin by introducing the core principles that govern RNA folding, such as base pairing rules, common secondary structure motifs, and tertiary interactions. The discussion then progresses to computational frameworks and comparative sequence analysis methods used to infer RNA secondary structures. The chapter also explores various approaches for modeling RNA three-dimensional architecture, including molecular modeling, coarse-grained simulations, and integrative methodologies that may incorporate experimental data and artificial intelligence-based predictions. Throughout the chapter, we evaluate the advantages, limitations, and practical applications of these tools, with an emphasis on how they contribute to elucidating RNA structure–function relationships.