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bindcraft-reference

BindCraft protein binder design reference. Use when working with AF2 backpropagation, binder design, interface optimization, PyRosetta metrics, design filtering, or comparing with RFdiffusion approaches.

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安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

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技能说明

BindCraft Reference Skill

Full documentation: docs/plans/2026-01-15-bindcraft-comprehensive-skill.md

Quick Reference

Pipeline Overview

Target PDB → AF2 Hallucination → MPNN Sequences → AF2 Validation → PyRosetta Relax → Filtering

Key Difference from RFdiffusion

BindCraft: AF2 backpropagation (sequence+structure simultaneously)
RFdiffusion: Diffusion model (backbone first, then MPNN)

Design Algorithms

Algorithm	Method	Speed
4stage	Logits→Softmax→One-hot→PSSM (default)	Medium
3stage	Logits→Softmax→One-hot	Faster
2stage	Logits→PSSM semi-greedy	Fastest
greedy	Random loss-reducing mutations	Slowest

Target Settings (JSON)

{
    "design_path": "/path/to/output/",
    "binder_name": "MyBinder",
    "starting_pdb": "/path/to/target.pdb",
    "chains": "A",
    "target_hotspot_residues": "56,58,62",
    "lengths": [65, 150],
    "number_of_final_designs": 100
}

Key Loss Weights

Weight	Effect
`weights_con_inter`	Interface contacts (higher = more)
`weights_plddt`	Confidence optimization
`weights_helicity`	Negative = favor β-sheets
`weights_rg`	Compactness (radius of gyration)
`weights_iptm`	Interface pTM

Key Filters

Filter	Good Value	Meaning
`pLDDT`	≥0.8	Confidence
`i_pTM`	≥0.5	Interface confidence
`dG`	≤0	Binding energy (negative = good)
`ShapeComplementarity`	≥0.6	Surface fit
`n_InterfaceHbonds`	≥3	Hydrogen bonds

PyRosetta Interface Metrics

dG: Binding free energy
dSASA: Buried surface area
ShapeComplementarity: Geometric fit
PackStat: Packing quality
InterfaceHbonds: H-bond count
InterfaceUnsatHbonds: Buried polar without H-bonds

Presets

Preset	Use Case
`default_4stage_multimer`	Standard binders
`betasheet_4stage_multimer`	β-sheet rich
`peptide_3stage_multimer`	Short peptides
`*_hardtarget`	Difficult targets
`*_flexible`	Flexible interfaces

Concepts for Banta Lab

Multi-stage optimization: Soft → temp → hard → greedy
Combined loss functions: Multiple objectives
Integrated AF2 validation: After MPNN design
PyRosetta interface scoring: Add to validation pipeline
Filter-based selection: Multi-metric thresholds
Acceptance rate monitoring: Auto-terminate poor campaigns

When to Use BindCraft vs RFdiffusion

Use BindCraft	Use RFdiffusion
Need high AF2 confidence	Need structural diversity
Integrated validation	Large-scale screening
Well-defined binding site	Novel fold exploration
Quality over quantity	Memory constrained

使用示例

查看来源仓库中的使用示例与配置说明。

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来源历史

收录时间: 2026-01-20
索引更新时间: 2026-01-26
Branch: main

收录与同步日期属于本站记录。源码修改历史请查看来源仓库。

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