RNAiFold

RNAiFold designs RNA sequences that fold into specified secondary structures to enable sequence-level engineering for synthetic biology and nanotechnology applications.


Key Features:

  • Input Flexibility: Accepts a target RNA secondary structure and optional constraints including GC-content ranges and counts of strong (GC), weak (AU), and wobble (GU) base pairs.
  • Algorithmic Approaches: Provides RNA-CPdesign, which uses constraint programming suitable for smaller structures requiring precise constraint control, and RNA-LNSdesign, which uses a large neighborhood search heuristic suited for larger structures.
  • Inverse Hybridization Problem Solving: Generates two sequences whose minimum free-energy hybridization aligns with a provided hybridization target structure.

Scientific Applications:

  • Synthetic Biology: Enables design of RNA sequences that fold into specified secondary structures for synthetic biology applications.
  • Nanotechnology: Supports construction of RNA-based nanostructures with prescribed secondary-structure constraints.
  • Molecular Engineering: Assists sequence-level engineering of RNA molecules with defined structural properties.
  • Therapeutic RNA Design: Facilitates design of RNA sequences with target folding characteristics for therapeutic applications.
  • Biomolecular Device Design: Enables creation of novel RNA-based biomolecular devices by specifying desired secondary structures.

Methodology:

Implements constraint programming (RNA-CPdesign) and a large neighborhood search heuristic (RNA-LNSdesign); addresses the inverse hybridization problem by producing two sequences whose minimum free-energy hybridization matches the input target; implementations are in COMET and supported on Linux.

Topics

Details

Tool Type:
web application
Operating Systems:
Linux
Programming Languages:
Python
Added:
3/25/2017
Last Updated:
11/25/2024

Operations

Publications

Garcia-Martin JA, Clote P, Dotu I. RNAiFold: a web server for RNA inverse folding and molecular design. Nucleic Acids Research. 2013;41(W1):W465-W470. doi:10.1093/nar/gkt280. PMID:23700314. PMCID:PMC3692061.

Documentation