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Related Articles from SNS
ECHO-PPI: Trustworthy AI for Evidence-Bundled Detection of Overlapping Protein Modules in Protein-Protein Interaction Networks
arXiv:2605.21216v2 Announce Type: replace Abstract: Protein-protein interaction networks provide a graph-level view of cellular organization, yet their functional modules are overlapping, noisy, and difficult to interpret from cluster assignments alone. Existing community-detection methods can recover candidate protein complexes, but they rarely explain why an individual protein is assigned to a specific module or whether that assignment should be treated as core, peripheral, or uncertain....
Enhancing Protein-Protein Interaction Prediction with Hierarchical Motif-based Multimodal Protein Embedding
Announce Type: cross Abstract: Protein-protein interactions (PPIs) are essential for many biological processes. However, existing PPI prediction approaches suffer from two major limitations: they overlook the hierarchical organization of proteins, particularly meso-scale motifs that critically regulate PPIs, and fail to effectively integrate sequence, structure, and function modalities. To address these limitations, we propose MMM-PPI, a Hierarchical Motif-based Multi-Modal protein Encoder...
Improving viral protein clustering using both diversified protein profiles and structural information
Viruses are abundant, ancestral and potentially fast-evolving biological entities. As a result, their encoded proteins are diverse and identifying homologous relationships between sequences is as important for phylogeny and functional annotation as it is challenging. Traditional methods group viral proteins by sequence similarity, build HMM profiles for each protein family, and cluster further via profile comparisons.
Structure-Guided Adaptive Propagation for Protein-Protein Interaction Site Prediction
arXiv:2606.01781v1 Announce Type: new Abstract: Accurate prediction of protein-protein interaction sites (PPIS) is essential for understanding cellular processes, disease mechanisms, and therapeutic target discovery. Graph-based deep learning has advanced PPIS prediction by incorporating residue-level structural context. However, most graph-based models still rely on fixed propagation schemes that treat all residues similarly, despite the structural and functional heterogeneity of protein...
Retrieval and competition: how a protein foundation model starts a protein
Announce Type: replace-cross Abstract: Protein language models are increasingly used to guide experimental and clinical decisions, yet it is often unclear whether a confident prediction reflects recognition of biological evidence or retrieval of a statistical default. We examine this distinction for a near-universal biological rule, that proteins begin with methionine, by tracing the computational pathway through which ESM2-8M produces this prediction. The model does not detect methionine at...
AgentPLM: Agentic Protein Language Models with Reasoning-Augmented Decoding for Protein Sequence Design
arXiv:2606.02386v1 Announce Type: new Abstract: Protein language models (PLMs) are passive oracles: they generate sequences in a single forward pass with no mechanism to consult external biophysical feedback or redirect generation when a candidate violates thermodynamic or structural constraints. We introduce AgentPLM, which addresses this by equipping a pre-trained PLM with i) Reasoning-Augmented Decoding (RAD), which interleaves autoregressive generation with tool calls (ESMFold, FoldX,...
AMix-2: Establishing Protein as a Native Modality in Large Language Models
arXiv:2605.30963v1 Announce Type: cross Abstract: We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein understanding and sequence design within a single foundation model. AMix-2 is built upon two key ideas: (1) a unified protein-text formulation that embeds natural language and protein sequence in a shared token space, enabling one model to perform biological reasoning and conditional design instead...
Laser beam builds cell-like protein networks without chemical modification
Laser beam builds cell-like protein networks without chemical modification Lisa Lock Scientific Editor Robert Egan Associate Editor Networks of protein fibers play important roles in living cells. To understand the dynamical behavior of these networks, model networks are needed to perform in vitro studies. However, fabrication of protein networks similar to those in cells has proved difficult, as current methods could affect the biological function of these proteins—ultimately impacting our...
Synthesized peptides can slip into cells to block hard-to-target protein interactions
Synthesized peptides can slip into cells to block hard-to-target protein interactions Sadie Harley Scientific Editor Robert Egan Associate Editor Many diseases are driven by proteins interacting with each other inside cells. But blocking these interactions with drugs is difficult because typical "small-molecule" drugs often prove to be too small to grip the broad, flat surfaces involved in protein-protein interactions. On the other hand, peptides—short chains of amino acids—can cover larger...
Ribosome tunnel interactions reveal how bacteria can pause protein production
Ribosome tunnel interactions reveal how bacteria can pause protein production Lisa Lock Scientific Editor Robert Egan Associate Editor How do bacteria regulate the production of their proteins? Researchers at the University of Hamburg, in collaboration with international partners, have now demonstrated how small protein building blocks, known as peptides, specifically influence bacterial protein production. The findings have been published in two articles in the journal Nature Communications.