ArticleJournal of peptide science : an official publication of the European Peptide Society2025
PepFuNN: Novo Nordisk Open-Source Toolkit to Enable Peptide in Silico Analysis.
Article in Journal of peptide science : an official publication of the European Peptide Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- PepFoundry: A Pipeline for Building Machine-Learning Ready Representations of Nonstandard Peptides Containing Cycles, Non-natural Residues, Polymer Units, and More.Journal of chemical information and modeling · 2026Article
- Beyond natural amino acids: extending immunogenicity risk assessment to modified peptides through chemical feature encoding. A case study on citrullination.Frontiers in immunology · 2026Article
- How to build machine learning models able to extrapolate from standard to modified peptides.Journal of cheminformatics · 2025Article
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2 authors.
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Abstract
We present PepFuNN, a new open-source version of the PepFun package with functions to study the chemical space of peptide libraries and perform structure-activity relationship analyses. PepFuNN is a Python package comprising five modules to study peptides with natural amino acids and, in some cases, sequences with non-natural amino acids based on the availability of a public monomer dictionary. The modules allow calculating physicochemical properties, performing similarity analysis using different peptide representations, clustering peptides using molecular fingerprints or calculated descriptors, designing peptide libraries based on specific requirements, and a module dedicated to extracting matched pairs from experimental campaigns to guide the selection of the most relevant mutations in design new rounds. The code and tutorials are available at https://github.com/novonordisk-research/pepfunn.
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