A Nextflow pipeline for protein binder design
-
Updated
May 19, 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.
Unified Python library and CLI for protein structure prediction and inverse folding.
Retraining of ProteinMPNN model specifically with acid-stable structures and sequences
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
Protein binder mutagenesis GUI
RNA-seq counts to ranked de novo protein binder candidates, with full provenance back to the patient cohort.
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.
Computational pipeline for measuring protein interior reprogrammability. Identifies chassis candidates where exterior fold is preserved while interior chemistry varies.
Manage protein design processes
🧬 Lectures for course ML-protein-design
Personalized lymphoma therapy design with Gemma 4, AlphaFold, RFdiffusion. Kaggle Gemma 4 Good Hackathon submission.
De novo protein binder design pipeline: motif-scaffolded RFdiffusion + ProteinMPNN + AlphaFold2 self-consistency validation. PD-L1 reference example.
Molecular dynamic simulation of RFdiffusion/ProteinMPNN designed HMERF mutated titin Ig152/Fn3-119 domain protein binder
Iterative AlphaFold-Guided Nanobody Design for Lateral Flow Immunoassays
Empirical dual-use risk assessment of protein language models (ESM-2) and structure-based design tools (ProteinMPNN)
🧬 Experiments and setup of RFdiffusion/ProteinMPNN running on macOS Apple Silicon (CPU).
Universal Peptide Drug Discovery — AI-driven cyclic peptide design pipeline with ncAA integration
Add a description, image, and links to the proteinmpnn topic page so that developers can more easily learn about it.
To associate your repository with the proteinmpnn topic, visit your repo's landing page and select "manage topics."