ProCaliper: functional and structural analysis, visualization, and annotation of proteins

Fuente: arXiv
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Main Authors: Rozum, Jordan C., Ufford, Hunter, Im, Alexandria K., Zhang, Tong, Pollock, David D., Kim, Doo Nam, Feng, Song
Format: Preprint
Published: 2025
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author Rozum, Jordan C.
Ufford, Hunter
Im, Alexandria K.
Zhang, Tong
Pollock, David D.
Kim, Doo Nam
Feng, Song
author_facet Rozum, Jordan C.
Ufford, Hunter
Im, Alexandria K.
Zhang, Tong
Pollock, David D.
Kim, Doo Nam
Feng, Song
contents Understanding protein function at the molecular level requires connecting residue-level annotations with physical and structural properties. This can be cumbersome and error-prone when functional annotation, computation of physico-chemical properties, and structure visualization are separated. To address this, we introduce ProCaliper, an open-source Python library for computing and visualizing physico-chemical properties of proteins. It can retrieve annotation and structure data from UniProt and AlphaFold databases, compute residue-level properties such as charge, solvent accessibility, and protonation state, and interactively visualize the results of these computations along with user-supplied residue-level data. Additionally, ProCaliper incorporates functional and structural information to construct and optionally sparsify networks that encode the distance between residues and/or annotated functional sites or regions. The package ProCaliper and its source code, along with the code used to generate the figures in this manuscript, are freely available at https://github.com/PNNL-Predictive-Phenomics/ProCaliper.
format Preprint
id arxiv_https___arxiv_org_abs_2506_19961
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle ProCaliper: functional and structural analysis, visualization, and annotation of proteins
Rozum, Jordan C.
Ufford, Hunter
Im, Alexandria K.
Zhang, Tong
Pollock, David D.
Kim, Doo Nam
Feng, Song
Biomolecules
Molecular Networks
Understanding protein function at the molecular level requires connecting residue-level annotations with physical and structural properties. This can be cumbersome and error-prone when functional annotation, computation of physico-chemical properties, and structure visualization are separated. To address this, we introduce ProCaliper, an open-source Python library for computing and visualizing physico-chemical properties of proteins. It can retrieve annotation and structure data from UniProt and AlphaFold databases, compute residue-level properties such as charge, solvent accessibility, and protonation state, and interactively visualize the results of these computations along with user-supplied residue-level data. Additionally, ProCaliper incorporates functional and structural information to construct and optionally sparsify networks that encode the distance between residues and/or annotated functional sites or regions. The package ProCaliper and its source code, along with the code used to generate the figures in this manuscript, are freely available at https://github.com/PNNL-Predictive-Phenomics/ProCaliper.
title ProCaliper: functional and structural analysis, visualization, and annotation of proteins
topic Biomolecules
Molecular Networks
url https://arxiv.org/abs/2506.19961