RosettaCommons / RosettaCommons/RFdiffusion

Looking for methods on to create n-terminals that package more kb in a viral capsid using RFDiffusion.

Open
#195 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
3.1k
Forks
644
PR merge metrics
No merged PRs in 30d

Description

Thank you for this software. I have been using motif scaffolding and binder design. However, my main focus is to create n-terminals that would potentially package more kb preferably >5kb, to a viral protein that normally would only package 4.7. Is there a way?, and I want to disclose that I am not an avid coder, but I am learning. I want to use RFDiffusion to create n-terminals that package more kb in a viral capsid. How would I go about creating something like this using RFDiffusion? Do I have to re-create and train model myself? Or is there an option for this specific direction with this code? Please let me know your thoughts and advice, I appreciate it.

Heather

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

The issue names RFdiffusion's motif-scaffolding and binder-design workflows but no file, test, or entry point. Start by reviewing those existing workflows and the project's documentation to determine whether designing N-terminal capsid proteins is supported; done would be a clear feasibility answer and, if applicable, a defined implementation or training plan.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
bioinformatics, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
15/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.