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Introduction

AlignIF is a tool for 3D RNA inverse folding, leveraging multiple structure alignment (MStA) to design nucleotide sequences from RNA structures. It is designed for researchers and professionals in biomolecule design and synthetic biology, providing a user-friendly interface to input RNA structures and generate sequences.

Features

  • Supports PDB and mmCIF format for RNA structure input.
  • Optional multiple structure alignment (MStA) for enhanced sequence design.
  • Customizable parameters including random seed, temperature, and number of sequences.
  • Optional known sub-sequence input for constrained design.
  • Generates downloadable FASTA files and visual sequence logos.

How to Use

  1. Input RNA Structure: Paste a PDB/mmCIF structure into the textarea or upload a file.
  2. Select Parameters: Adjust settings like MStA toggle, random seed, temperature, and number of sequences (1-100).
  3. Optional Sub-sequence: Provide a known sub-sequence in the format --AGCU-- (where A, G, C, U are known residues, and '-' indicates unknown).
  4. Submit: Click the "Design" button to process the input and generate sequences.
  5. View Results: Download the generated sequences in FASTA format or view the sequence logo.

Example

Try loading the example PDB file provided on the home page to see AlignIF in action. The example demonstrates how to input a structure and generate sequences with default parameters.

Notes

* Ensure that the input structure is valid and in PDB or mmCIF format. For best results, use the MStA option when designing sequences for complex RNA structures. The tool is optimized for modern browsers and supports both light and dark modes for accessibility.
* The software is free to academic users ONLY; For commercial usage, please contact with us (Xiaoyong Pan, 2008xypan@sjtu.edu.cn).
* Please do not use any crawler tools or submit frequently in a very short time.

Contact

For support or inquiries, please reach out via the Contact section on the home page.

Reference

Shengfan Wang, et al. structure alignment-driven cross-graph modeling for funcitonal RNA design. In submisson