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Paper#LLM🔬 ResearchAnalyzed: Jan 3, 2026 16:12

HELM-BERT: Peptide Property Prediction with HELM Notation

Published:Dec 29, 2025 03:29
1 min read
ArXiv

Analysis

This paper introduces HELM-BERT, a novel language model for predicting the properties of therapeutic peptides. It addresses the limitations of existing models that struggle with the complexity of peptide structures by utilizing HELM notation, which explicitly represents monomer composition and connectivity. The model demonstrates superior performance compared to SMILES-based models in downstream tasks, highlighting the advantages of HELM's representation for peptide modeling and bridging the gap between small-molecule and protein language models.
Reference

“HELM-BERT significantly outperforms state-of-the-art SMILES-based language models in downstream tasks, including cyclic peptide membrane permeability prediction and peptide-protein interaction prediction.”

PermalinkArXiv
Research#Drug Discovery🔬 ResearchAnalyzed: Jan 10, 2026 07:24

AVP-Fusion: Novel AI Approach for Antiviral Peptide Identification

Published:Dec 25, 2025 07:29
1 min read
ArXiv

Analysis

The study, published on ArXiv, introduces AVP-Fusion, an adaptive multi-modal fusion model for identifying antiviral peptides. This research contributes to the field of AI-driven drug discovery, potentially accelerating the development of new antiviral therapies.
Reference

“AVP-Fusion utilizes adaptive multi-modal fusion and contrastive learning.”

PermalinkArXiv