Prediction of protein interactions with function in protein (de-)phosphorylation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F25%3A00143909" target="_blank" >RIV/00216224:14740/25:00143909 - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0319084" target="_blank" >https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0319084</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1371/journal.pone.0319084" target="_blank" >10.1371/journal.pone.0319084</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Prediction of protein interactions with function in protein (de-)phosphorylation

Popis výsledku v původním jazyce

Protein-protein interactions (PPIs) form a complex network called "interactome" that regulates many functions in the cell. In recent years, there is an increasing accumulation of evidence supporting the existence of a hyperbolic geometry underlying the network representation of complex systems such as the interactome. In particular, it has been shown that the embedding of the human Protein-Interaction Network (hPIN) in hyperbolic space (H2) captures biologically relevant information. Here we explore whether this mapping contains information that would allow us to predict the function of PPIs, more specifically interactions related to post-translational modification (PTM). We used a random forest algorithm to predict PTM-related directed PPIs, concretely, protein phosphorylation and dephosphorylation, based on hyperbolic properties and centrality measures of the hPIN mapped in H2. To evaluate the efficacy of our algorithm, we predicted PTM-related PPIs of ataxin-1, a protein which is responsible for Spinocerebellar Ataxia type 1 (SCA1). Proteomics analysis in a cellular model revealed that several of the predicted PTM-PPIs were indeed dysregulated in a SCA1-related disease network. A compact cluster composed of ataxin-1, its dysregulated PTM-PPIs and their common upstream regulators may represent critical interactions for disease pathology. Thus, our algorithm may infer phosphorylation activity on proteins through directed PPIs.

Název v anglickém jazyce

Prediction of protein interactions with function in protein (de-)phosphorylation

Popis výsledku anglicky

Protein-protein interactions (PPIs) form a complex network called "interactome" that regulates many functions in the cell. In recent years, there is an increasing accumulation of evidence supporting the existence of a hyperbolic geometry underlying the network representation of complex systems such as the interactome. In particular, it has been shown that the embedding of the human Protein-Interaction Network (hPIN) in hyperbolic space (H2) captures biologically relevant information. Here we explore whether this mapping contains information that would allow us to predict the function of PPIs, more specifically interactions related to post-translational modification (PTM). We used a random forest algorithm to predict PTM-related directed PPIs, concretely, protein phosphorylation and dephosphorylation, based on hyperbolic properties and centrality measures of the hPIN mapped in H2. To evaluate the efficacy of our algorithm, we predicted PTM-related PPIs of ataxin-1, a protein which is responsible for Spinocerebellar Ataxia type 1 (SCA1). Proteomics analysis in a cellular model revealed that several of the predicted PTM-PPIs were indeed dysregulated in a SCA1-related disease network. A compact cluster composed of ataxin-1, its dysregulated PTM-PPIs and their common upstream regulators may represent critical interactions for disease pathology. Thus, our algorithm may infer phosphorylation activity on proteins through directed PPIs.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10600 - Biological sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PLoS Biology

ISSN

1932-6203

e-ISSN

1932-6203

Svazek periodika

20

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

1-21

Kód UT WoS článku

001437514700024

EID výsledku v databázi Scopus

2-s2.0-86000330544