In wmm27/idpr: Profiling and Analyzing Intrinsically Disordered Proteins in R

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "75%"
)

idpr

Overall, ‘idpr’ aims to integrate tools for the computational analysis of intrinsically disordered proteins within R. This package is used to identify known characteristics of IDPs within a sequence of interest with easily reported and dynamic results. Additionally, this package also includes tools for IDP-based sequence analysis to be used in conjunction with other R packages. See our recently published peer-reviewed publication in PLOS ONE (https://doi.org/10.1371/journal.pone.0266929)

Please Refer to idpr-vignette.Rmd file for a detailed introduction to the idpr package.

Links to the vignettes found at the Bioconductor landing page (here) or

Installation

You can install the stable release version version from Bioconductor with:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("idpr")

Additionally, you can install the development version from Bioconductor with:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

Or you can install the most recent development version from GitHub with:

# install.packages("devtools") #if not already installed
devtools::install_github("wmm27/idpr")

Example

This is a basic example to quickly profile your protein of interest:

library(idpr)

P53_HUMAN <- TP53Sequences[2] #Getting a pre-loaded sequence from idpr
print(P53_HUMAN)

P53_ID <- "P04637" #Human TP53 UniProt ID

#Generates the IDP Profile:
idprofile(sequence = P53_HUMAN, 
          uniprotAccession = P53_ID, 
          proteinName = "TP53 Human", #Optional Argument
          window = 11, #Optional Argument
          pKaSet = "Lehninger", #Optional Argument
          iupredType = "redox" #Optional Argument
)

Please Refer to idpr-vignette.Rmd file for a detailed introduction to the idpr package. Link to the Vignette (here)

Appendix

For use and details on 'idpr', see our peer-reviewed article published in PLOS ONE (https://doi.org/10.1371/journal.pone.0266929)

Package citation

citation("idpr")

Function citations

Bálint Mészáros, Gábor Erdős, Zsuzsanna Dosztányi, IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding, Nucleic Acids Research, Volume 46, Issue W1, 2 July 2018, Pages W329–W337, https://doi.org/10.1093/nar/gky384
Erdős, G., & Dosztányi, Z. (2020). Analyzing protein disorder with IUPred2A. Current Protocols in Bioinformatics, 70, e99. https://doi.org/10.1002/cpbi.99
Kozlowski, L. P. (2016). IPC – Isoelectric Point Calculator. Biology Direct, 11(1), 55. https://doi.org/10.1186/s13062-016-0159-9
Kyte, J., & Doolittle, R. F. (1982). A simple method for displaying the hydropathic character of a protein. Journal of molecular biology, 157(1), 105-132.
Nelson, D. L., & Cox, M. M. (2017). Lehninger Principles of Biochemistry (Seventh ed.). New York, NY: W. H. Freeman and Company.
Prilusky, J., Felder, C. E., et al. (2005). FoldIndex: a simple tool to predict whether a given protein sequence is intrinsically unfolded. Bioinformatics, 21(16), 3435-3438.
Uversky, V. N. (2016). Paradoxes and wonders of intrinsic disorder: Complexity of simplicity. Intrinsically Disordered Proteins, 4(1), e1135015. https://doi.org/10.1080/21690707.2015.1135015
Uversky, V. N. (2013). A decade and a half of protein intrinsic disorder: Biology still waits for physics. Protein Science, 22(6), 693-724. doi:10.1002/pro.2261
Uversky, V. N., Gillespie, J. R., & Fink, A. L. (2000). Why are “natively unfolded” proteins unstructured under physiologic conditions?. Proteins: structure, function, and bioinformatics, 41(3), 415-427. https://doi.org/10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7