Abstract
We present forgi, a Python library to analyze the tertiary structure of RNA secondary structure elements. Our representation of an RNA molecule is centered on secondary structure elements (stems, bulges and loops). By fitting a cylinder to the helix axis, these elements are carried over into a coarse-grained 3D structure representation. Integration with Biopython allows for handling of all-atom 3D information. forgi can deal with a variety of file formats including dotbracket strings, PDB and MMCIF files. We can handle modified residues, missing residues, cofold and multifold structures as well as nucleotide numbers starting at arbitrary positions. We apply this library to the study of stacking helices in junctions and pseudoknots and investigate how far stacking helices in solved experimental structures can divert from coaxial geometries.
Highlights
In RNA 3D structure prediction, knowledge-based potentials are commonly used, especially for coarse-grained approaches that are suitable for larger RNA molecules[1]
For knowledge extraction from RNA-containing Protein Data Bank (PDB) files, it is highly desirable to have a software library at hand, which understands the semantics of RNA secondary structures and makes tasks like iterating over loops of a certain type straightforward
We present the forgi library[17], which is centered on RNA secondary structure elements and makes them usable for 3D structure analysis. forgi aims at providing a high level API for many common operations, but can be extended with new functionality
Summary
In RNA 3D structure prediction, knowledge-based potentials are commonly used, especially for coarse-grained approaches that are suitable for larger RNA molecules[1]. For knowledge extraction from RNA-containing PDB files, it is highly desirable to have a software library at hand, which understands the semantics of RNA secondary structures and makes tasks like iterating over loops of a certain type straightforward. Such a library should be written in an accessible scripting language, be well documented and tested and should be available under an open-source license
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