alphafold
Validate protein designs using AlphaFold2 structure prediction. Use this skill when: (1) Validating designed sequences fold correctly, (2) P…
Maintainer FreedomIntelligence · Last updated April 1, 2026
Predict peptide-MHC class I and II binding affinity using MHCflurry and NetMHCpan neural network models. Identify potential T-cell epitopes from protein sequences. Use when predicting MHC binding for vaccine design or neoantigen identification.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-immunoinformatics-mhc-binding-prediction
Skill Snapshot
Source Doc
Goal: Install MHCflurry and download pre-trained prediction models.
Approach: Install via pip and fetch model weights for class I pan-allele or specific allele predictions.
## Download models for specific alleles
mhcflurry-downloads fetch models_class1_pan
Goal: Predict peptide-MHC binding affinity and presentation scores for a set of peptides.
Approach: Load the Class1PresentationPredictor and call predict() with peptide-allele pairs to obtain IC50, percentile rank, and presentation scores.
from mhcflurry import Class1PresentationPredictor
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