Research Resource: EPSLiM: Ensemble Predictor for Short Linear Motifs in Nuclear Hormone Receptors

Abstract

Nuclear receptors (NRs) are a superfamily of transcription factors central to regulating many biological processes, including cell growth, death, metabolism, and immune responses. NR-mediated gene expression can be modulated by coactivators and corepressors through direct physical interaction or protein complexes with functional domains in NRs. One class of these domains includes short linear motifs (SLiMs), which facilitate protein-protein interactions, phosphorylation, and ligand binding primarily in the intrinsically disordered regions (IDRs) of proteins. Across all proteins, the number of known SLiMs is limited due to the difficulty in studying IDRs experimentally. Computational tools provide a systematic and data-driven approach for predicting functional motifs that can be used to prioritize experimental efforts. Accordingly, several tools have been developed based on sequence conservation or biophysical features; however, discrepancies in predictions make it difficult to determine the true candidate SLiMs. In this work, we present the ensemble predictor for short linear motifs (EPSLiM), a novel strategy to prioritize the residues that are most likely to be SLiMs in IDRs. EPSLiM applies a generalized linear model to integrate predictions from individual methodologies. We show that EPSLiM outperforms individual predictors, and we apply our method to NRs. The androgen receptor is an example with an N-terminal domain of 559 disordered amino acids that contains several validated SLiMs important for transcriptional activation. We use the androgen receptor to illustrate the predictive performance of EPSLiM and make the results of all human and mouse NRs publically available through the web service http://epslim.bwh.harvard.edu.

Investigating the disordered regions (MoRFs, SLiMs and LCRs) and functions of mimicry proteins/peptides in silico

“…To assess the extent of structural disorderliness, the mimicry proteins were divided in three different categories based on the PDR, as was also done in earlier studies [ 26 , 27 , 41 ]. Our results revealed that 107 of the 147 bacterial (73%) and 16 of the 34 (47%) viral mimicry proteins were ordered (PDR <10%).…”

Control of Steroid Receptor Dynamics and Function by Genomic Actions of the Cochaperones p23 and Bag-1L

“…It is likely that the ability to be involved in such protein-protein interactions allows the BAG domain of Bag-1L to exert a great impact on AR function. Since several steroid receptors have SLiMs-containing regions at their intrinsically disordered N-termini [97], it seems plausible that they could also be targeted by the BAG domain of Bag-1L. It is likely that they already account for the reported effects of Bag-1L on steroid receptor action [81–83].…”

Quarterly intrinsic disorder digest (April–May–June, 2014)

“…They find that a slowly exchanging Kapb1 phase forms a key constituent with the FG Nups that exists simultaneously in a fast phase, and that this suggests a Kapcentric barrier mechanism. 52 53 A rapid lysine ubiquitination predictor called Rapid UBIquitination (RUBI) was released by Walsh et al 54 In training RUBI, they found that intrinsic disorder was weakly anti-correlated with ubiquitination. The online protein characterization tool cleverSuite was introduced by Klus et al CleverSuite reports statistics on protein sequences based on their physico-chemical properties.…”