OVO, an open-source ecosystem for de novo protein design
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Updated
Jul 13, 2026 - Python
OVO, an open-source ecosystem for de novo protein design
Official repository for the ProteinDJ protein design pipeline
A Nextflow pipeline for protein binder design
De novo therapeutic peptide design pipeline using RFdiffusion and ESMFold to hallucinate NaV1.7 pain-channel blockers locally on CPU
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.
De novo design of a miniprotein binder targeting the SARS-CoV-2 spike RBD using RFdiffusion, ProteinMPNN, and Rosetta. A step-by-step project integrating generative AI and structural bioinformatics.
In-silico protein design bench: takes a target + epitope to designed, structurally validated, developable binders and multivalent scaffolds. Composes the binder-design, developability-hardening, and multivalent-display skills with the structure-model
Protein binder design GUI
Auditable SciForge × BioGym de novo protein-design run: RFdiffusion → ProteinMPNN → Boltz-2
RNA-seq counts to ranked de novo protein binder candidates, with full provenance back to the patient cohort.
Molecular dynamic simulation of RFdiffusion/ProteinMPNN designed HMERF mutated titin Ig152/Fn3-119 domain protein binder
🧬 Lectures for course ML-protein-design
구조 기반 de novo 항체 설계
Manage protein design processes
Design proteins in your terminal. A TUI agent for de novo protein design — free by default.
Open-source production control plane for protein-design pipelines (RFdiffusion → ProteinMPNN → Boltz/AlphaFold2). Start here: architecture, docs, dev tooling.
Cross-Model CKA: EVO2/FAESM–RFdiffusion3 alignment reflects low-frequency smoothing bias, not structural convergence. Paper + full analysis pipeline.
Auditable Codex skill for protein design, molecular docking, batch screening, provenance, and evidence-aware result review.
UC Berkeley MSSE Capstone Project: Evaluating & refining filtering strategies for de novo protein binders
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