BoltzGen: Toward Universal Binder Design

Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)

Codes for our paper "UniMoMo: Unified Generative Modeling of 3D Molecules for De Novo Binder Design" (ICML 2025)

Codes for our paper "Programming Biomolecular Interactions with All-Atom Generative Model"

Automated generation of immunogenic peptides from protein structures and molecular docking analysis using AlphaFold2 and AutodockVina.

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.

Source code for Targeting SARS-CoV-2 Receptor Binding Domain and Main Protease with D-peptides

Evaluation other methods for macrocyclic design

A Claude Code Skill for de novo D-peptide inhibitor design using the Boltz2 IC₅₀ prediction pipeline

AI-Driven De Novo Peptide Generator. Designing novel, highly diverse amino acid sequences for targeted biomedical applications.

Multi-phase peptide ML pipeline for hemolysis prediction, generative design, and closed-loop optimization, built on transformers and modern PyTorch tooling.

AMP Forge is an antimicrobial peptide generation project based on PLM embeddings, VAE, and latent diffusion.

A design framework for programmable genome engineering. Useful for designing peptide linkers that connect Transcription Activator-Like Effector (TALE) DNA-binding arrays to catalytic effector domains.

Universal Peptide Drug Discovery — AI-driven cyclic peptide design pipeline with ncAA integration