What is the difference between RFdiffusion and ProteinMPNN?

RFdiffusion designs the 3D coordinates of the protein backbone (the global fold), while ProteinMPNN is used afterward to determine the specific amino acid sequence that will fold into that shape.

Does this skill support symmetric proteins?

Yes, it supports multiple symmetry types including cyclic (C2-C6), dihedral (D2-D4), and higher-order symmetries like tetrahedral and octahedral.

Do I need a GPU to run this skill?

Yes, RFdiffusion requires a CUDA-enabled GPU with at least 16GB of VRAM (24GB recommended) to perform the diffusion simulations efficiently.

What is RFdiffusion used for?

RFdiffusion is used to generate the 3D backbone structures (the 'shape') of proteins, which is the first step in designing new binders, novel monomers, or symmetric complexes.

Can I design binders for a specific target with this skill?

Yes, you can provide a target PDB file and specify 'hotspot' residues to guide the model to generate binders that interact with specific regions of your target protein.

RFdiffusion Protein Design

Name: RFdiffusion Protein Design
Author: adaptyvbio

byadaptyvbio

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데이터 과학 및 ML

Generates novel protein backbones and binder scaffolds using diffusion-based generative modeling for de novo protein structure design.

RFdiffusion is a specialized skill for Claude Code that enables researchers and bio-engineers to design protein structures from scratch or around specific target motifs. It leverages a powerful diffusion model to create high-quality protein backbones, supporting the creation of binders, symmetric oligomers, and scaffolded functional motifs. This skill automates the configuration of complex parameters like contig maps and hotspot residues, facilitating a streamlined workflow from initial target identification to validated backbone generation within a computational biology pipeline.

주요 기능

01Support for symmetric oligomer assembly (C, D, and polyhedral symmetries)

02De novo protein backbone generation from scratch

03Binder scaffold generation for specific protein targets

04Partial diffusion for structural refinement and existing backbone modification

0575 GitHub stars

06Functional motif scaffolding with coordinate preservation

사용 사례

01Creating novel enzyme scaffolds by grafting active sites onto new backbones

02Generating symmetric protein assemblies for nanotechnology or vaccine design

03Designing high-affinity protein binders for therapeutic targets

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add adaptyvbio/protein-design-skills rfdiffusion

For use in Claude.ai and ChatGPT

Download Skill