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Graph deep learning guides the design of chemically modified ultrashort antimicrobial peptides

Researchers at Zhejiang University of Technology in Hangzhou, China, reported in the Journal of Medicinal Chemistry, published online on 7 October, a deep learning framework called SMAMP that represents antimicrobial peptides as molecular graphs built from their full chemical structure rather than as strings of standard amino acids.

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A peptide hidden inside a fungal protein tells a plant pathogen it has entered its host

Researchers at Heinrich Heine University Düsseldorf in Germany, working with colleagues at the University of Groningen, the University of Göttingen, NC State University and Imperial College London, reported in Nature Communications, published online on 9 October, a receptor system that lets the corn smut fungus Ustilago maydis detect that it has entered plant tissue.

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Three orthogonal chromatography methods map impurities and newly reported oligomers in a 20-amino-acid peptide

A new study pairs SEC, reversed-phase and HILIC with high-resolution MS to map 10 impurities and newly reported oligomers in a synthetic peptide.

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Study shows an oxime resin can be reused across many solid-phase peptide synthesis cycles to cut waste

Researchers at Université Laval in Canada reported in ACS Omega, published online on 17 October, a systematic study of reusing the Kaiser-DeGrado oxime resin as a greener approach to solid-phase peptide synthesis (SPPS).

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Deep-learning 'chain-as-prompt' framework designs antimicrobial lipopeptides from bacterial genome mining

Researchers at Shanghai Jiao Tong University in China reported in Nature Communications, published online on 17 October, a deep-learning framework for the de novo design of antimicrobial lipopeptides, short peptides carrying an N-terminal fatty-acid chain.

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MassNet releases a billion-scale, AI-ready mass spectrometry corpus for deep-learning proteomics

A team led by Westlake University in China, with collaborators at Zhejiang University, Fudan University, Soochow University, the University of British Columbia and several Shanghai research institutes, reported in Nature Methods, published online on 14 October, MassNet, an open artificial-intelligence-ready data corpus for mass-spectrometry-based proteomics.

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University of Toronto's OpenPep will build an open peptide–protein binding database and AI models with Google.org funding

A University of Toronto team has launched OpenPep, a project to build an open-access database of peptide–protein binding measurements and AI models trained on that data.

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Review maps how peptaibol length and lipid environment set membrane orientation and oligomer size in solid-state NMR studies

Researchers at the University of Strasbourg and CNRS in France reported in the Journal of Peptide Science, first published on 16 October, an open-access review of solid-state NMR studies of peptaibols, fungal peptides rich in the non-coded residue alpha-aminoisobutyric acid (Aib) that serve as models for pore-forming proteins.

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NuXLApp brings protein-nucleic acid crosslinking mass spectrometry analysis into one open-source web app

Researchers at the University of Tübingen, the Max Planck Institute for Multidisciplinary Sciences and University Medical Center Göttingen in Germany reported in Protein Science, first published on 15 October, NuXLApp, an interactive web application for crosslinking mass spectrometry (XL-MS) studies of protein-nucleic acid interactions.

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Benchmark of 10 public tools finds antimicrobial peptide MIC predictors more useful for ranking than for exact values

Researchers at Hunan Normal University in China reported in Small Methods, published online on 15 October, a retrospective benchmark of 10 publicly released tools that predict the minimum inhibitory concentration (MIC) of antimicrobial peptides (AMPs) directly from sequence.