An implementation of ESM2 in Equinox+JAX
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Updated
Apr 20, 2026 - Python
An implementation of ESM2 in Equinox+JAX
End-to-end protein function prediction from structure alone: active sites, binding pockets, GO terms, PPI partners, and drug candidates.
Repository of the paper "Exploring sequence landscape of biosynthetic gene clusters with protein language models" published at ICML2024 workshop Machine Learning for Life and Material Science: From Theory to Industry applications
A reproducible in silico pipeline to rationally design and prioritize anti-Listeria antimicrobial peptides. This workflow integrates sequence generation, physicochemical filtering, ESM-2 embedding and multi-criteria scoring to narrow candidates and reduce experimental burden. Open for community evaluation, modification and further development.
Prediction of anti-fungal proteins using protein language models
AI-powered protein mutation analysis platform. Enter any UniProt ID, mutate a residue, and SERAPH, an original ESM2+CNN+BiLSTM model, predicts exactly which secondary structures change and why.
Next-generation protein-protein interaction site (PPIS) prediction integrating ESM-2 protein language model representations with structural & evolutionary features via biophysics-supervised gated fusion and equivariant graph networks.
Similarity search for protein sequences using ESM-2 embeddings and Approximate Nearest Neighbor (ANN) methods.
Antimicrobial peptide discovery via ESM-2 fine-tuning. LoRA training on ESCAPE/GenPept-Curated-2025/PepBenchmark with multilabel evaluation.
Do protein foundation models help predict peptide-HLA class I complex stability on unseen binding grooves? No: a conventional supervised net beats all eleven PLM configurations tested. London AI x Science Hackathon 2026, Serova track.
Experimental-design methods for budgeted protein-epistasis mapping with zero-shot ESM-2 signals; evaluated on GB1.
Residue-residue contact prediction using ESM2 enhanced with template-based structural priors from homologous sequences.
Zero-shot variant pathogenicity prediction via spectral covariance analysis of ESM2 hidden states | Claw4S 2026
Transformer fusion pipeline for protein binding-site prediction using ESM2 protein embeddings, physicochemical surface descriptors, and neighbourhood-aware attention.
Functional prediction and evidence-grounded interpretation of KCNH2 missense variants using MaveDB, ESM-2, XGBoost, ClinVar, AlphaMissense and RAG.
Unified Python library and CLI for protein structure prediction and inverse folding.
RCSF-AMP: residue-confidence-guided sequence-structure fusion for antimicrobial peptide prediction
Dual-scale peptide property prediction with atom/residue encoders and cross-attention fusion.
Fine-tuning ESM-2 with LoRA for enzyme family classification. Homology-aware splitting, calibrated uncertainty, integrated gradients interpretability, and FastAPI inference. Built for production.
Real-time, zero-shot Variant Effect Prediction (VEP) and in-silico mutagenesis engine powered by Meta's ESM-2. Achieves sub-second inference on edge and consumer hardware.
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