ArticleMolecules (Basel, Switzerland)2021
PepFun: Open Source Protocols for Peptide-Related Computational Analysis.
Article in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 25 citations in OpenAlex.
- PepFuNN: Novo Nordisk Open-Source Toolkit to Enable Peptide in Silico Analysis.Journal of peptide science : an official publication of the European Peptide Society · 2025Article
- Bioactive milk peptides: an updated comprehensive overview and database.Critical reviews in food science and nutrition · 2024Review
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- Article
- pyPept: a python library to generate atomistic 2D and 3D representations of peptides.Journal of cheminformatics · 2023Article
- Computational exploration of the global microbiome for antibiotic discovery.bioRxiv : the preprint server for biology · 2023Article
- Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening.Pharmaceuticals (Basel, Switzerland) · 2023Article
- PDAUG: a Galaxy based toolset for peptide library analysis, visualization, and machine learning modeling.BMC bioinformatics · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 2 countries.
Funding
Abstract
Peptide research has increased during the last years due to their applications as biomarkers, therapeutic alternatives or as antigenic sub-units in vaccines. The implementation of computational resources have facilitated the identification of novel sequences, the prediction of properties, and the modelling of structures. However, there is still a lack of open source protocols that enable their straightforward analysis. Here, we present PepFun, a compilation of bioinformatics and cheminformatics functionalities that are easy to implement and customize for studying peptides at different levels: sequence, structure and their interactions with proteins. PepFun enables calculating multiple characteristics for massive sets of peptide sequences, and obtaining different structural observables derived from protein-peptide complexes. In addition, random or guided library design of peptide sequences can be customized for screening campaigns. The package has been created under the python language based on built-in functions and methods available in the open source projects BioPython and RDKit. We present two tutorials where we tested peptide binders of the MHC class II and the Granzyme B protease.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.