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Mn_riboswitch.md

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De novo modeling of a Manganese riboswitch with Rosetta

Installation

Before starting make sure you have the following packages installed:

Preparation

The riboswitch that we are modeling here is derived from the yybP-ykoY aptamer of Xanthomoinas oryzae (Suddala, Nat. Commun., 2019).

The RNA sequence and secondary structure annotation are provided as inputs for de novo modeling:

mn_riboswitch.fasta

>mn_riboswitch A:1-57 B:1-48
auccuuggggaguagccugcuuucuucggaaagcgccuguaucaacauacucggcua,uagccguggugcaggcaacggcgaaagccgucuggcgagaccagggau

mn_riboswitch_secstruct.txt

((((((((......(((.((((((....))))))((((((((((.......((((((,)))))))))))))))).(((((....)))))..)))....))))))))

FARFAR Rosetta modeling

The FARAFAR2 protocol of Rosetta includes improved base-pair sampling, and an updated fragment library and socring function (Watkins et al., Structure 2020). Models are calculated with rna_denovo. To run rna_denovo on multiple cores in parallel rosettascripts provides a utility script submitJobs to kickstart the simulations. First write the call to rna_denovo into a file.

FARFAR2.txt

rna_denovo.linuxgccrelease 
    -nstruct 1000 
    -fasta mn_riboswitch.fasta
    -secstruct_file mn_riboswitch_secstruct.txt
    -silent mn_riboswitch.out 
    -minimize_rna true 
    -cycles 20000

The flags used here are:

  • -nstruct number of models to compute on each core
  • -fasta path to fasta sequence file
  • -secstruct_file path to secondary structure in dot-bracket notation
  • -silent output silentfile where models are stored
  • -minimize_rna whether to refinement in the output structures with the high-resolution Rosetta potential
  • -cycles number of Monte Carlo cycles)

Then, start the simulations on as many cores as you like (here: 12) and write the models to a silentfile in the specified output directory (here: "denovo")

submitJobs -i FARFAR2.txt -d denovo -p 12

Postprocessing

At any time during the modeling you can check the number of generated models by running extract_pdb in dry mode (-e false prevents extraction of any PDB file):

extract_pdb -d denovo -e false

You can extract the top scoring PDB models (here: n=10) from the Rosetta generated silentfiles (set the -m flag to true if you want to merge them into a single PDB file)

extract_pdb -d denovo -n 10 -m true