Can rosetta generate a centroid model based on the rna sequence?

[Anonymous]

For RNA, what kind of model can be defined as a centroid model?

Does rosetta have a function to generate a centroid model for RNA? For proteins, pose_from_sequence(sequence, ‘centroid’ ) can be used to generate a centroid model from the sequence. Is there a similar function for RNA?

[Anonymous]

In brief, not really. The centroid model is unique to proteins, where a full-atom backbone but a centroided-out sidechain makes sense. RNA has a “coarse” model (a three- or four-bead system) — use ‘coarse_rna’ instead of ‘centroid’ above — but really, it would help to know what your goal is.

[Anonymous]

assembler = core.import_pose.RNA_HelixAssembler()

pose= assembler.build_init_pose(seq,”) 

Coarse_rna=pyrosetta.rosetta.protocols.rna.denovo.coarse.CoarseRNA_LoopCloser()

Coarse_rna.apply(pose,pose.total_residue())

I first generate a helix full-atom pose，Using CoarseRNA_LoopCloser() on the pose is no different from the previous pose, it seems that CoarseRNA_LoopCloser() does not work.

pose=pyrosetta.rosetta.core.import_pose.make_extended_coarse_pose(pose,pose.sequence())

ERROR: Warning: residue RAD is RNA but is not specified as L_RNA or D_RNA in its params file!

Then I used make_extended_coarse_pose to try to generate a coarse structure, but the error was reported as above.

pyrosetta.rosetta.core.import_pose.make_coarse_pose(pose: pyrosetta.rosetta.core.pose.Pose, coarse_pose: pyrosetta.rosetta.core.pose.Pose) → None

pyrosetta.rosetta.core.import_pose.make_extended_coarse_pose(coarse_pose: pyrosetta.rosetta.core.pose.Pose, full_sequence: str) → None

I don’t know what the coarse_rna marked with the red color in rosetta’s documentation refers to. Hope you can help me generate a coarse rna structure and look forward to your reply! Thanks a lot…

[Anonymous]

Sorry, I stared at the rosetta documention for a long time, but I found that I didn’t understand him at all. Can you tell me how to use Coarse_rna to generate Coarse  RNA from sequence or structure, and save it in pdb format, so that I can observe this coarse  structure。

[Anonymous]

The coarse_rna code is old and not actively maintained, so I’m not too surprised that it’s not working when you combine components in pyrosetta like this. Generally speaking, I would expect those movers to only really work in the context of the CoarseRNA_DeNovoProtocol — but no clue if that code itself still works.

Anyway, as far as I know, what currently works is: a pair of movers in very recent versions of rosetta in protocols.rna.movers called RNA_Coarsify and RNA_Decoarsify that transform PDBs between fullatom and coarse_rna representations. 

Again, I think the central question is: why do you want a coarse RNA pose? What scientific question are you trying to answer, and how would this help? Understanding this will let me figure out what you need.

[Anonymous]

As far as I know, the establishment of the centroid model is very helpful in the de novo protein modeling, because the representation of the all-atom model is very expensive. Similarly, I want to generate the reduced representation in the building of the RNA model  for further optimization.

[Anonymous]

That’s true, but it’s not at all necessary for RNA. We have a low-resolution scoring function that we apply during RNA fragment assembly that’s quite cheap but it doesn’t rely on a centroid RNA model. You can just use FARFAR2 for your modeling needs.

[Anonymous]

So can I understand it this way? The centroid model is important for protein de novo modeling but not so important for RNA. The key factor is that low-resolution scoring function depends on the centroid model for proteins and not for RNA.

But this link(https://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/14.00-RNA-Basics.ipynb) tells me: Analogous to the protein low-resolution potential, an RNA low-resolution potential has been developed to more quickly score RNA structures represented in centroid mode. 

I am very confused, can you help me solve this confusion? Thank you！

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