A Nextflow pipeline for protein binder design
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Updated
Apr 17, 2026 - Python
A Nextflow pipeline for protein binder design
A modular, extensible peptide design pipeline with target preparation, backbone generation, sequence design, scoring, and ranking. Full local CPU pipeline, and backend hooks for RFpeptides, ProteinMPNN/LigandMPNN, and ColabFold.
Open hotspot-guided de novo protein binder design pipeline integrating OpenMM, BindCraft, ProteinMPNN, and AlphaFold2.
Optimized ProteinMPNN for Apple Silicon: 15× speedup with 0% accuracy loss through architecture pruning, batching, and ANE acceleration. Comprehensive benchmarking study of speed-accuracy trade-offs.
Molecular dynamic simulation of RFdiffusion/ProteinMPNN designed HMERF mutated titin Ig152/Fn3-119 domain protein binder
Retraining of ProteinMPNN model specifically with acid-stable structures and sequences
Computational pipeline for measuring protein interior reprogrammability. Identifies chassis candidates where exterior fold is preserved while interior chemistry varies.
🧬 Lectures for course ML-protein-design
Protein binder design GUI
LigandMPNN but with dynamic constraints. This allows the biases applied during inference to adjust to a desired goal during the generation process. Current implementations are for pI targeting and surface patch generation
Manage protein design processes
🧬 Experiments and setup of RFdiffusion/ProteinMPNN running on macOS Apple Silicon (CPU).
Protein binder mutagenesis GUI
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