Topology independent comparison of RNA 3D structures using the CLICK algorithm

Area of Science:

• Structural biology
• Computational biology
• Biochemistry

Background:

• Non-coding RNA molecules play crucial regulatory roles, making them attractive therapeutic targets.
• Classifying RNA 3D structures provides insights into RNA evolution and function.
• An increasing number of atomic-resolution RNA structures necessitate effective classification and similarity investigation tools.

Purpose of the Study:

• To extend and optimize the CLICK algorithm for superimposing RNA 3D structures and RNA-protein complexes.
• To develop a tool that is independent of the associated topologies of RNA structures.
• To enable the identification of conformational changes and maximize detectable similarity.

Main Methods:

• Extension and optimization of the CLICK algorithm, named Rclick.
• Superimposition of RNA 3D structures and RNA-protein complexes using clique matching and 3D least squares fitting.
• Benchmarking Rclick against other structural alignment methods on diverse datasets.

Main Results:

• Rclick demonstrates comparable or superior performance to existing methods in terms of structural overlap extent.
• The algorithm successfully recognizes conformational changes in RNA structures.
• Rclick accurately aligned RNA binding sites with substrates when applied to Ribonuclease III protein.

Conclusions:

• Rclick is an effective tool for superimposing RNA 3D structures and RNA-protein complexes.
• The algorithm aids in understanding RNA structure, function, and evolution.
• Rclick has potential applications in identifying ligand-binding pockets in RNA and can be accessed via a web server.