一键在 Manus 中运行任何 Skill

setup

星标147

分支20

更新时间2026年6月11日 13:32

First-time setup for protein design tools. Use this skill when: (1) User is new and hasn't run any tools yet, (2) Commands fail with "file not found" or "modal: command not found", (3) Modal authentication errors occur, (4) User asks how to get started or set up the environment, (5) biomodals directory is missing or tools aren't working.

安装

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

在 Manus 中运行

来源

adaptyvbio

adaptyvbio/protein-design-skills

打开 GitHub 仓库查看创作者相关仓库

下载

在 Manus 中运行

相关职业SOC

基于 SOC 职业分类

网络与计算机系统管理员计算机与数学类职业·SOC 15-1244

SKILL.md

readonly

同仓库更多 Skills

同仓库

bindcraft

adaptyvbio/protein-design-skills

End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.

2026-06-11147

binder-design

adaptyvbio/protein-design-skills

Guidance for choosing the right protein binder design tool. Use this skill when: (1) Deciding between BoltzGen, BindCraft, or RFdiffusion, (2) Planning a binder design campaign, (3) Understanding trade-offs between different approaches, (4) Selecting tools for specific target types. For specific tool parameters, use the individual tool skills (boltzgen, bindcraft, rfdiffusion, etc.).

2026-06-11147

boltzgen

adaptyvbio/protein-design-skills

All-atom protein design using BoltzGen diffusion model. Use this skill when: (1) Need side-chain aware design from the start, (2) Designing around small molecules or ligands, (3) Want all-atom diffusion (not just backbone), (4) Require precise binding geometries, (5) Using YAML-based configuration. For backbone-only generation, use rfdiffusion. For sequence-only design, use proteinmpnn. For structure validation, use boltz.

2026-06-11147

esm

adaptyvbio/protein-design-skills

ESM protein language models for embeddings, sequence scoring, structure prediction, and binder design. Use this skill when: (1) Computing pseudo-log-likelihood (PLL) or mutation-effect scores, (2) Getting protein embeddings for clustering or filtering, (3) Predicting complex structures with ESMFold2, (4) Designing binders by inverting ESMFold2, (5) Filtering designs by sequence plausibility. For diffusion-based structure prediction, use boltz or chai. For QC thresholds, use protein-qc. For gradient-based multi-objective design, use mosaic.

2026-06-11147

germinal

adaptyvbio/protein-design-skills

De novo antibody and nanobody (VHH) design with Germinal. Use this skill when: (1) Designing epitope-targeted nanobodies or scFvs, (2) Needing CDR design on a fixed framework, (3) Working on antibody-format binders rather than miniproteins. For miniprotein binders, use binder-design (BoltzGen, BindCraft, RFdiffusion, Mosaic). For structure validation, use boltz or chai.

2026-06-11147

mosaic

adaptyvbio/protein-design-skills

Multi-objective, gradient-based protein binder design with Mosaic. Use this skill when: (1) Composing several structure or sequence models into one design objective, (2) Optimizing binders against a custom loss rather than a fixed pipeline, (3) Wanting gradient descent over sequence space in the style of ColabDesign, RSO, or BindCraft but with interchangeable predictors, (4) Letting the optimizer choose the epitope instead of fixing hotspots. For an end-to-end binder pipeline with default filters, use bindcraft. For all-atom diffusion design, use boltzgen. For backbone-only generation, use rfdiffusion.

2026-06-11147

name	setup
description	First-time setup for protein design tools. Use this skill when: (1) User is new and hasn't run any tools yet, (2) Commands fail with "file not found" or "modal: command not found", (3) Modal authentication errors occur, (4) User asks how to get started or set up the environment, (5) biomodals directory is missing or tools aren't working.
license	MIT
category	utilities
tags	["setup","onboarding","installation"]

Setup Guide

Help users get their environment ready to run protein design tools.

Quick checklist

Run through this checklist when a user encounters setup issues:

Step	Check	Fix
1. Modal CLI	`modal --version`	`pip install modal`
2. Modal auth	`modal token show`	`modal setup`
3. biomodals	`ls biomodals/modal_*.py`	`git clone https://github.com/hgbrian/biomodals`
4. Test	`cd biomodals && modal run modal_boltzgen.py --help`	See troubleshooting

Diagnosing issues

Error: "modal: command not found"

Cause: Modal CLI not installed.

Fix:

pip install modal

Then restart the terminal or run hash -r.

Error: "Permission denied" or "Unauthorized"

Cause: Modal not authenticated.

Fix:

modal setup

This opens a browser. Click "Authorize" to complete authentication.

Error: "No such file or directory: modal_boltzgen.py"

Cause: biomodals repository not cloned or not in correct directory.

Fix:

git clone https://github.com/hgbrian/biomodals
cd biomodals

Error: "uvx: command not found"

Cause: uvx is an optional wrapper from the uv package. It's not required.

Fix: Run modal directly (recommended):

modal run modal_boltzgen.py --help

Or install uv if you prefer using uvx:

pip install uv

Full setup steps

Step 1: Install Modal CLI

pip install modal

Verify: modal --version

Step 2: Authenticate Modal

modal setup

This opens a browser. Click "Authorize".

Verify: modal token show

Step 3: Clone biomodals

git clone https://github.com/hgbrian/biomodals
cd biomodals

Verify: ls modal_*.py should show files like modal_boltzgen.py

Step 4: Test the Setup

cd biomodals
modal run modal_boltzgen.py --help

Expected: Usage instructions appear showing --input-yaml, --protocol, --num-designs options.

Common workflows after setup

Once setup is complete, users can:

cd biomodals

# Design binders with BoltzGen (requires YAML config)
modal run modal_boltzgen.py --input-yaml binder.yaml --protocol protein-anything --num-designs 50

# Generate backbones with RFdiffusion (official repo, not biomodals)
python run_inference.py inference.input_pdb=target.pdb contigmap.contigs=[A1-150/0 70-100] inference.num_designs=100

# Validate with Chai
modal run modal_chai1.py --input-faa designs.fasta

GPU selection

Set GPU with environment variable:

GPU=L40S modal run modal_boltzgen.py --input-yaml config.yaml --num-designs 50
GPU=A100 modal run modal_chai1.py --input-faa complex.fasta

GPU	VRAM	Best For
T4	16GB	ProteinMPNN, ESM
A10G	24GB	RFdiffusion, Chai
L40S	48GB	BoltzGen, BindCraft
A100	40-80GB	Large complexes

Modal free tier

Modal offers $30/month in free credits - enough for:

~500 BoltzGen designs
~2000 RFdiffusion backbones
~1000 Chai predictions

Full documentation: See Getting started