{"title":"PepFuNN: Novo Nordisk Open-Source Toolkit to Enable Peptide in Silico Analysis","authors":"Rodrigo Ochoa, Kristine Deibler","doi":"10.1002/psc.3666","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":16946,"journal":{"name":"Journal of Peptide Science","volume":"31 2","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11706630/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Peptide Science","FirstCategoryId":"99","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/psc.3666","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The official Journal of the European Peptide Society EPS
The Journal of Peptide Science is a cooperative venture of John Wiley & Sons, Ltd and the European Peptide Society, undertaken for the advancement of international peptide science by the publication of original research results and reviews. The Journal of Peptide Science publishes three types of articles: Research Articles, Rapid Communications and Reviews.
The scope of the Journal embraces the whole range of peptide chemistry and biology: the isolation, characterisation, synthesis properties (chemical, physical, conformational, pharmacological, endocrine and immunological) and applications of natural peptides; studies of their analogues, including peptidomimetics; peptide antibiotics and other peptide-derived complex natural products; peptide and peptide-related drug design and development; peptide materials and nanomaterials science; combinatorial peptide research; the chemical synthesis of proteins; and methodological advances in all these areas. The spectrum of interests is well illustrated by the published proceedings of the regular international Symposia of the European, American, Japanese, Australian, Chinese and Indian Peptide Societies.