scholarly journals Glutamate promotes SSB protein–protein Interactions via intrinsically disordered regions

2017 ◽  
Vol 429 (18) ◽  
pp. 2790-2801 ◽  
Author(s):  
Alexander G. Kozlov ◽  
Min Kyung Shinn ◽  
Elizabeth A. Weiland ◽  
Timothy M. Lohman
Author(s):  
Stefano Gianni ◽  
Per Jemth

Abstract Intrinsically disordered protein regions may fold upon binding to an interaction partner. It is often argued that such coupled binding and folding enables the combination of high specificity with low affinity. The basic tenet is that an unfavorable folding equilibrium will make the overall binding weaker while maintaining the interaction interface. While theoretically solid, we argue that this concept may be misleading for intrinsically disordered proteins. In fact, experimental evidence suggests that interactions of disordered regions usually involve extended conformations. In such cases, the disordered region is exceptionally unlikely to fold into a bound conformation in the absence of its binding partner. Instead, these disordered regions can bind to their partners in multiple different conformations and then fold into the native bound complex, thus, if anything, increasing the affinity through folding. We concede that (de)stabilization of native structural elements such as helices will modulate affinity, but this could work both ways, decreasing or increasing the stability of the complex. Moreover, experimental data show that intrinsically disordered binding regions display a range of affinities and specificities dictated by the particular side chains and length of the disordered region and not necessarily by the fact that they are disordered. We find it more likely that intrinsically disordered regions are common in protein–protein interactions because they increase the repertoire of binding partners, providing an accessible route to evolve interactions rather than providing a stability–affinity trade-off.


2021 ◽  
Author(s):  
Caroline Benz ◽  
Muhammad Ali ◽  
Izabella Krystkowiak ◽  
Leandro Simonetti ◽  
Ahmed Sayadi ◽  
...  

Specific protein-protein interactions are central to all processes that underlie cell physiology. Numerous studies using a wide range of experimental approaches have identified tens of thousands of human protein-protein interactions. However, many interactions remain to be discovered, and low affinity, conditional and cell type-specific interactions are likely to be disproportionately under-represented. Moreover, for most known protein-protein interactions the binding regions remain uncharacterized. We previously developed proteomic peptide phage display (ProP-PD), a method for simultaneous proteome-scale identification of short linear motif (SLiM)-mediated interactions and footprinting of the binding region with amino acid resolution. Here, we describe the second-generation human disorderome (HD2), an optimized ProP-PD library that tiles all disordered regions of the human proteome and allows the screening of ~1,000,000 overlapping peptides in a single binding assay. We define guidelines for how to process, filter and rank the results and provide PepTools, a toolkit for annotation and analysis of identified hits. We uncovered 2,161 interaction pairs for 35 known SLiM-binding domains and confirmed a subset of 38 interactions by biophysical or cell-based assays. Finally, we show how the amino acid resolution binding site information can be used to pinpoint functionally important disease mutations and phosphorylation events in intrinsically disordered regions of the human proteome. The HD2 ProP-PD library paired with PepTools represents a powerful pipeline for unbiased proteome-wide discovery of SLiM-based interactions.


2014 ◽  
Vol 50 (40) ◽  
pp. 5245-5247 ◽  
Author(s):  
Hadar Amartely ◽  
Ahuvit David ◽  
Mario Lebendiker ◽  
Hadar Benyamini ◽  
Shai Izraeli ◽  
...  

2020 ◽  
Vol 19 (7) ◽  
pp. 1070-1075 ◽  
Author(s):  
Katrina Meyer ◽  
Matthias Selbach

Protein-protein interactions are often mediated by short linear motifs (SLiMs) that are located in intrinsically disordered regions (IDRs) of proteins. Interactions mediated by SLiMs are notoriously difficult to study, and many functionally relevant interactions likely remain to be uncovered. Recently, pull-downs with synthetic peptides in combination with quantitative mass spectrometry emerged as a powerful screening approach to study protein-protein interactions mediated by SLiMs. Specifically, arrays of synthetic peptides immobilized on cellulose membranes provide a scalable means to identify the interaction partners of many peptides in parallel. In this minireview we briefly highlight the relevance of SLiMs for protein-protein interactions, outline existing screening technologies, discuss unique advantages of peptide-based interaction screens and provide practical suggestions for setting up such peptide-based screens.


2020 ◽  
Vol 36 (8) ◽  
pp. 2458-2465 ◽  
Author(s):  
Isak Johansson-Åkhe ◽  
Claudio Mirabello ◽  
Björn Wallner

Abstract Motivation Interactions between proteins and peptides or peptide-like intrinsically disordered regions are involved in many important biological processes, such as gene expression and cell life-cycle regulation. Experimentally determining the structure of such interactions is time-consuming and difficult because of the inherent flexibility of the peptide ligand. Although several prediction-methods exist, most are limited in performance or availability. Results InterPep2 is a freely available method for predicting the structure of peptide–protein interactions. Improved performance is obtained by using templates from both peptide–protein and regular protein–protein interactions, and by a random forest trained to predict the DockQ-score for a given template using sequence and structural features. When tested on 252 bound peptide–protein complexes from structures deposited after the complexes used in the construction of the training and templates sets of InterPep2, InterPep2-Refined correctly positioned 67 peptides within 4.0 Å LRMSD among top10, similar to another state-of-the-art template-based method which positioned 54 peptides correctly. However, InterPep2 displays a superior ability to evaluate the quality of its own predictions. On a previously established set of 27 non-redundant unbound-to-bound peptide–protein complexes, InterPep2 performs on-par with leading methods. The extended InterPep2-Refined protocol managed to correctly model 15 of these complexes within 4.0 Å LRMSD among top10, without using templates from homologs. In addition, combining the template-based predictions from InterPep2 with ab initio predictions from PIPER-FlexPepDock resulted in 22% more near-native predictions compared to the best single method (22 versus 18). Availability and implementation The program is available from: http://wallnerlab.org/InterPep2. Supplementary information Supplementary data are available at Bioinformatics online.


2018 ◽  
Author(s):  
Annamária Kiss-Tóth ◽  
Laszlo Dobson ◽  
Bálint Péterfia ◽  
Annamária F. Ángyán ◽  
Balázs Ligeti ◽  
...  

AbstractThe human postsynaptic density is an elaborate network comprising thousands of proteins, playing a vital role in the molecular events of learning and the formation of memory. Despite our growing knowledge of specific proteins and their interactions, atomic-level details of their full three-dimensional structure and their rearrangements are mostly elusive. Advancements in structural bioinformatics enabled us to depict the characteristic features of proteins involved in different processes aiding neurotransmission. We show that postsynaptic protein-protein interactions are mediated through the delicate balance of intrinsically disordered regions and folded domains, and this duality is also imprinted in the amino acid sequence. We introduce Diversity of Potential Interactions (DPI), a structure and regulation based descriptor to assess the diversity of interactions. Our approach reveals that the postsynaptic proteome has its own characteristic features and these properties reliably discriminate them from other proteins of the human proteome. Our results suggest that postsynaptic proteins are especially susceptible to forming diverse interactions with each other, which might be key in the reorganization of the PSD in molecular processes related to learning and memory.


2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Hao He ◽  
Jiaxiang Zhao ◽  
Guiling Sun

Abstract Background Molecular recognition features (MoRFs) are one important type of disordered segments that can promote specific protein-protein interactions. They are located within longer intrinsically disordered regions (IDRs), and undergo disorder-to-order transitions upon binding to their interaction partners. The functional importance of MoRFs and the limitation of experimental identification make it necessary to predict MoRFs accurately with computational methods. Results In this study, a new sequence-based method, named as MoRFMPM, is proposed for predicting MoRFs. MoRFMPM uses minimax probability machine (MPM) to predict MoRFs based on 16 features and 3 different windows, which neither relying on other predictors nor calculating the properties of the surrounding regions of MoRFs separately. Comparing with ANCHOR, MoRFpred and MoRFCHiBi on the same test sets, MoRFMPM not only obtains higher AUC, but also obtains higher TPR at low FPR. Conclusions The features used in MoRFMPM can effectively predict MoRFs, especially after preprocessing. Besides, MoRFMPM uses a linear classification algorithm and does not rely on results of other predictors which makes it accessible and repeatable.


2018 ◽  
Vol 19 (12) ◽  
pp. 3860 ◽  
Author(s):  
Keiichi Homma ◽  
Hiroto Anbo ◽  
Tamotsu Noguchi ◽  
Satoshi Fukuchi

Eukaryotic proteins consist of structural domains (SDs) and intrinsically disordered regions (IDRs), i.e., regions that by themselves do not assume unique three-dimensional structures. IDRs are generally subject to less constraint and evolve more rapidly than SDs. Proteins with a lower number of protein-to-protein interactions (PPIs) are also less constrained and tend to evolve fast. Extracellular proteins of mammals, especially immune-related extracellular proteins, on average have relatively high evolution rates. This article aims to examine if a high evolution rate in IDRs or that in SDs accounts for the rapid evolution of extracellular proteins. To this end, we classified eukaryotic proteins based on their cellular localizations and analyzed them. Moreover, we divided proteins into SDs and IDRs and calculated the respective evolution rate. Fractional IDR content is positively correlated with evolution rate. For their fractional IDR content, immune-related extracellular proteins show an aberrantly high evolution rate. IDRs evolve more rapidly than SDs in most subcellular localizations. In extracellular proteins, however, the difference is diminished. For immune-related proteins in mammals in particular, the evolution rates in SDs come close to those in IDRs. Thus high evolution rates in both IDRs and SDs account for the rapid evolution of immune-related proteins.


Biomolecules ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 1413
Author(s):  
Kristina Kastano ◽  
Gábor Erdős ◽  
Pablo Mier ◽  
Gregorio Alanis-Lobato ◽  
Vasilis J. Promponas ◽  
...  

Intrinsically disordered proteins (IDPs) contain regions lacking intrinsic globular structure (intrinsically disordered regions, IDRs). IDPs are present across the tree of life, with great variability of IDR type and frequency even between closely related taxa. To investigate the function of IDRs, we evaluated and compared the distribution of disorder content in 10,695 reference proteomes, confirming its high variability and finding certain correlation along the Euteleostomi (bony vertebrates) lineage to number of cell types. We used the comparison of orthologs to study the function of disorder related to increase in cell types, observing that multiple interacting subunits of protein complexes might gain IDRs in evolution, thus stressing the function of IDRs in modulating protein-protein interactions, particularly in the cell nucleus. Interestingly, the conservation of local compositional biases of IDPs follows residue-type specific patterns, with E- and K-rich regions being evolutionarily stable and Q- and A-rich regions being more dynamic. We provide a framework for targeted evolutionary studies of the emergence of IDRs. We believe that, given the large variability of IDR distributions in different species, studies using this evolutionary perspective are required.


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