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Journal Article

PepFun: Open Source Protocols for Peptide-Related Computational Analysis

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Cossio,  Pilar
Biophysics of Tropical Diseases, Max Planck Tandem Group, University of Antioquia, Medellin, Colombia;
Department of Theoretical Biophysics, Max Planck Institute of Biophysics, Max Planck Society;

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Citation

Ochoa, R., & Cossio, P. (2021). PepFun: Open Source Protocols for Peptide-Related Computational Analysis. Molecules, 26(6): 1664. doi:10.3390/molecules26061664.


Cite as: http://hdl.handle.net/21.11116/0000-0008-4C5A-F
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.