K2N

K2N converts knotted RNA structures into nested, pseudoknot-free structures to enable computational analyses that require pseudoknot-free input.

Key Features:

• Diverse algorithms: Provides multiple pseudoknot-removal algorithms to address different characteristics of RNA pseudoknots.
• Base-pair removal: Produces nested structures by disregarding selected base pairs from the original knotted configuration.
• Sequence and alignment integration: Some algorithms incorporate sequence or alignment data into the pseudoknot-removal process.
• Reference implementations in PyCogent: Offers reference implementations implemented in the PyCogent project for reproducibility of the methods.
• Impact awareness: Acknowledges that different pseudoknot-removal methods can produce varying nested structures that affect downstream structure-based analyses.

Scientific Applications:

• Structural biology: Enables analyses that require pseudoknot-free secondary structures for comparative or predictive structural studies.
• Genomics: Facilitates genome-scale RNA structure analyses by providing nested structures compatible with large-scale pipelines.
• Molecular evolution: Supports evolutionary studies that compare RNA secondary structures after standardized pseudoknot removal.
• Structure-based computational analyses: Serves as input preparation for algorithms and tools that require pseudoknot-free RNA structures.

Methodology:

Conversion of knotted to nested RNA structures by removing pseudoknots via algorithms that disregard selected base pairs; multiple pseudoknot-removal algorithms are implemented, with some integrating sequence or alignment data; reference implementations are provided in PyCogent.