TY  - JOUR
AU  - Perović, Vladimir R.
AU  - Šumonja, Neven
AU  - Marsh, Lindsey A.
AU  - Radovanović, Sandro
AU  - Vukićević, Milan
AU  - Roberts, Stefan G. E.
AU  - Veljković, Nevena V.
PY  - 2018
UR  - http://www.nature.com/articles/s41598-018-28815-x
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/7811
AB  - Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).
T2  - Scientific Reports
T1  - IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins
VL  - 8
IS  - 1
SP  - 10563
DO  - 10.1038/s41598-018-28815-x
ER  - 

@article{
author = "Perović, Vladimir R. and Šumonja, Neven and Marsh, Lindsey A. and Radovanović, Sandro and Vukićević, Milan and Roberts, Stefan G. E. and Veljković, Nevena V.",
year = "2018",
abstract = "Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s).",
journal = "Scientific Reports",
title = "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins",
volume = "8",
number = "1",
pages = "10563",
doi = "10.1038/s41598-018-28815-x"
}

Perović, V. R., Šumonja, N., Marsh, L. A., Radovanović, S., Vukićević, M., Roberts, S. G. E.,& Veljković, N. V.. (2018). IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports, 8(1), 10563.
https://doi.org/10.1038/s41598-018-28815-x

Perović VR, Šumonja N, Marsh LA, Radovanović S, Vukićević M, Roberts SGE, Veljković NV. IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins. in Scientific Reports. 2018;8(1):10563.
doi:10.1038/s41598-018-28815-x .

Perović, Vladimir R., Šumonja, Neven, Marsh, Lindsey A., Radovanović, Sandro, Vukićević, Milan, Roberts, Stefan G. E., Veljković, Nevena V., "IDPpi: Protein-Protein Interaction Analyses of Human Intrinsically Disordered Proteins" in Scientific Reports, 8, no. 1 (2018):10563,
https://doi.org/10.1038/s41598-018-28815-x . .