Eukaryotic transcription factors: paradigms of protein intrinsic disorder

2017 ◽  
Vol 474 (15) ◽  
pp. 2509-2532 ◽  
Author(s):  
Lasse Staby ◽  
Charlotte O'Shea ◽  
Martin Willemoës ◽  
Frederik Theisen ◽  
Birthe B. Kragelund ◽  
...  
Keyword(s):  
Transcription Factors ◽  
Stress Responses ◽  
Tertiary Structure ◽  
Intrinsic Disorder ◽  
Molecular Structures ◽  
Sequence Motifs ◽  
Short Sequence ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Protein Intrinsic Disorder

Gene-specific transcription factors (TFs) are key regulatory components of signaling pathways, controlling, for example, cell growth, development, and stress responses. Their biological functions are determined by their molecular structures, as exemplified by their structured DNA-binding domains targeting specific cis-acting elements in genes, and by the significant lack of fixed tertiary structure in their extensive intrinsically disordered regions. Recent research in protein intrinsic disorder (ID) has changed our understanding of transcriptional activation domains from ‘negative noodles’ to ID regions with function-related, short sequence motifs and molecular recognition features with structural propensities. This review focuses on molecular aspects of TFs, which represent paradigms of ID-related features. Through specific examples, we review how the ID-associated flexibility of TFs enables them to participate in large interactomes, how they use only a few hydrophobic residues, short sequence motifs, prestructured motifs, and coupled folding and binding for their interactions with co-activators, and how their accessibility to post-translational modification affects their interactions. It is furthermore emphasized how classic biochemical concepts like allostery, conformational selection, induced fit, and feedback regulation are undergoing a revival with the appreciation of ID. The review also describes the most recent advances based on computational simulations of ID-based interaction mechanisms and structural analysis of ID in the context of full-length TFs and suggests future directions for research in TF ID.

Troponins, intrinsic disorder, and cardiomyopathy

2016 ◽  
Vol 397 (8) ◽  
pp. 731-751 ◽  
Author(s):  
Insung Na ◽  
Min J. Kong ◽  
Shelby Straight ◽  
Jose R. Pinto ◽  
Vladimir N. Uversky
Keyword(s):  
Posttranslational Modifications ◽  
Cardiac Troponin ◽  
Troponin I ◽  
Troponin T ◽  
Intrinsic Disorder ◽  
Functional Changes ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Structural And Functional Properties ◽  
Protein Intrinsic Disorder

Abstract Cardiac troponin is a dynamic complex of troponin C, troponin I, and troponin T (TnC, TnI, and TnT, respectively) found in the myocyte thin filament where it plays an essential role in cardiac muscle contraction. Mutations in troponin subunits are found in inherited cardiomyopathies, such as hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM). The highly dynamic nature of human cardiac troponin and presence of numerous flexible linkers in its subunits suggest that understanding of structural and functional properties of this important complex can benefit from the consideration of the protein intrinsic disorder phenomenon. We show here that mutations causing decrease in the disorder score in TnI and TnT are significantly more abundant in HCM and DCM than mutations leading to the increase in the disorder score. Identification and annotation of intrinsically disordered regions in each of the troponin subunits conducted in this study can help in better understanding of the roles of intrinsic disorder in regulation of interactomes and posttranslational modifications of these proteins. These observations suggest that disease-causing mutations leading to a decrease in the local flexibility of troponins can trigger a whole plethora of functional changes in the heart.

Functional roles of intrinsic disorder in CRISPR-associated protein Cas9

2017 ◽  
Vol 13 (9) ◽  
pp. 1770-1780 ◽  
Author(s):  
Zhihua Du ◽  
Vladimir N. Uversky
Keyword(s):  
Dna Binding ◽  
Intrinsic Disorder ◽  
Dna Binding Proteins ◽  
Functional Roles ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
P Protein ◽  
Protein Intrinsic Disorder ◽  
Rna And Dna ◽  
Different Origin

Protein intrinsic disorder is an important characteristic commonly detected in multifunctional or RNA- and DNA-binding proteins. We show here that the CRISPR-associated Cas9 proteins of different origin contain functionally important intrinsically disordered regions.

scholarly journals Critical Assessment of Protein Intrinsic Disorder Prediction

2020 ◽  
Author(s):  
Marco Necci ◽  
Damiano Piovesan ◽  
Silvio C.E. Tosatto ◽  
◽  
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Intrinsic Disorder ◽  
Critical Assessment ◽  
Disordered Proteins ◽  
Blind Test ◽  
Disorder Prediction ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Binding Regions ◽  
Protein Intrinsic Disorder

AbstractIntrinsically disordered proteins defying the traditional protein structure-function paradigm represent a challenge to study experimentally. As a large part of our knowledge rests on computational predictions, it is crucial for their accuracy to be high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in predicting intrinsically disordered regions in proteins and the subset of disordered residues involved in binding other molecules. A total of 43 methods, 32 for disorder and 11 for binding regions, were evaluated on a dataset of 646 novel manually curated proteins from DisProt. The best methods use deep learning techniques and significantly outperform widely used earlier physicochemical methods across different types of targets. Disordered binding regions remain hard to predict correctly. Depending on the definition used, the top disorder predictor has an FMax of 0.483 (DisProt) or 0.792 (DisProt-PDB). As the top binding predictor only attains an FMax of 0.231, this suggests significant potential for improvement. Intriguingly, computing times among the top performing methods vary by up to four orders of magnitude.

scholarly journals Intrinsic disorder controls two functionally distinct dimers of the master transcription factor PU.1

2020 ◽  
Vol 6 (8) ◽  
pp. eaay3178 ◽  
Author(s):  
Suela Xhani ◽  
Sangchoon Lee ◽  
Hye Mi Kim ◽  
Siming Wang ◽  
Shingo Esaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Transcription Factors ◽  
Intrinsic Disorder ◽  
The Other ◽  
Dna Binding Domain ◽  
Conformational Disorder ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
The One

Transcription factors comprise a major reservoir of conformational disorder in the eukaryotic proteome. The hematopoietic master regulator PU.1 presents a well-defined model of the most common configuration of intrinsically disordered regions (IDRs) in transcription factors. We report that the structured DNA binding domain (DBD) of PU.1 regulates gene expression via antagonistic dimeric states that are reciprocally controlled by cognate DNA on the one hand and by its proximal anionic IDR on the other. The two conformers are mediated by distinct regions of the DBD without structured contributions from the tethered IDRs. Unlike DNA-bound complexes, the unbound dimer is markedly destabilized. Dimerization without DNA is promoted by progressive phosphomimetic substitutions of IDR residues that are phosphorylated in immune activation and stimulated by anionic crowding agents. These results suggest a previously unidentified, nonstructural role for charged IDRs in conformational control by mitigating electrostatic penalties that would mask the interactions of highly cationic DBDs.

scholarly journals Critical assessment of protein intrinsic disorder prediction

2021 ◽  
Author(s):  
Marco Necci ◽  
◽  
Damiano Piovesan ◽  
Silvio C. E. Tosatto ◽  
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Intrinsic Disorder ◽  
Critical Assessment ◽  
Disordered Proteins ◽  
Blind Test ◽  
Disorder Prediction ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Full Dataset ◽  
Protein Intrinsic Disorder

AbstractIntrinsically disordered proteins, defying the traditional protein structure–function paradigm, are a challenge to study experimentally. Because a large part of our knowledge rests on computational predictions, it is crucial that their accuracy is high. The Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment was established as a community-based blind test to determine the state of the art in prediction of intrinsically disordered regions and the subset of residues involved in binding. A total of 43 methods were evaluated on a dataset of 646 proteins from DisProt. The best methods use deep learning techniques and notably outperform physicochemical methods. The top disorder predictor has Fmax = 0.483 on the full dataset and Fmax = 0.792 following filtering out of bona fide structured regions. Disordered binding regions remain hard to predict, with Fmax = 0.231. Interestingly, computing times among methods can vary by up to four orders of magnitude.

Exploring PLAC1 Structure and Underlying Mechanisms to Design a Derivative Vaccine Against Breast Cancer Progression; In-Silico Study

2020 ◽  
Vol 17 (5) ◽  
pp. 379-391
Author(s):  
Farzaneh Afzali ◽  
Parisa Ghahremanifard ◽  
Mohammad Mehdi Ranjbar ◽  
Mahdieh Salimi
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
In Silico ◽  
Tertiary Structure ◽  
Specific Antigen ◽  
Docking Simulation ◽  
Post Translational Modification ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Underlying Mechanisms

Background: The tolerogenic homeostasis in Breast Cancer (BC) can be surpassed by rationally designed immune-encouraging constructs against tumor-specific antigens through immunoinformatics approach. Objective: Availability of high throughput data providing the underlying concept of diseases and awarded computational simulations, lead to screening the potential medications and strategies in less time and cost. Despite the extensive effects of Placenta Specific 1 (PLAC1) in BC progression, immune tolerance, invasion, cell cycle regulation, and being a tumor-specific antigen the fundamental mechanisms and regulatory factors were not fully explored. It is also worth to design an immune response inducing construct to surpass the hurdles of traditional anti-cancer treatments. Methods and Result: The study was initiated by predicting and modelling the PLAC1 secondary and tertiary structures and then engineering the fusion pattern of PLAC1 derived immunodominant predicted CD8+ and B-cell epitopes to form a multi-epitope immunogenic construct. The construct was analyzed considering the physiochemical characterization, safety, antigenicity, post-translational modification, solubility, and intrinsically disordered regions. After modelling its tertiary structure, proteinprotein docking simulation was carried out to ensure the attachment of construct with Toll-Like Receptor 4 (TLR4) as an immune receptor. To guarantee the highest expression of the designed construct in E. coli k12 as an expressional host, the codon optimization and in-silico cloning were performed. The PLAC1 related miRNAs in BC were excavated and validated through TCGA BC miRNA-sequencing and databases; the common pathways then were introduced as other probable mechanisms of PLAC1 activity. Conclusion: Regarding the obtained in-silico results, the designed anti-PLAC1 multi-epitope construct can probably trigger humoral and cellular immune responses and inflammatory cascades, therefore may have the potential of halting BC progression and invasion engaging predicted pathways.

Visualising intrinsic disorder and conformational variation in protein ensembles

2014 ◽  
Vol 169 ◽  
pp. 179-193 ◽  
Author(s):  
Julian Heinrich ◽  
Michael Krone ◽  
Seán I. O'Donoghue ◽  
Daniel Weiskopf
Keyword(s):  
Intrinsic Disorder ◽  
Molecular Graphics ◽  
Post Translational Modifications ◽  
3D Structures ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Wide Range ◽  
Conformational Variations ◽  
Protein Ensembles ◽  
Traditional Approaches

Intrinsically disordered regions (IDRs) in proteins are still not well understood, but are increasingly recognised as important in key biological functions, as well as in diseases. IDRs often confound experimental structure determination—however, they are present in many of the available 3D structures, where they exhibit a wide range of conformations, from ill-defined and highly flexible to well-defined upon binding to partner molecules, or upon post-translational modifications. Analysing such large conformational variations across ensembles of 3D structures can be complex and difficult; our goal in this paper is to improve this situation by augmenting traditional approaches (molecular graphics and principal components) with methods from human–computer interaction and information visualisation, especially parallel coordinates. We present a new tool integrating these approaches, and demonstrate how it can dissect ensembles to reveal functional insights into conformational variation and intrinsic disorder.

scholarly journals Intrinsic disorder in biomarkers of insulin resistance, hypoadiponectinemia, and endothelial dysfunction among the type 2 diabetic patients

2015 ◽  
Author(s):  
Osama H. Jiffri ◽  
Fadwa M. Al-Sharif ◽  
Essam H. Jiffri ◽  
Vladimir N. Uversky
Keyword(s):  
Insulin Resistance ◽  
Endothelial Dysfunction ◽  
Adhesion Molecule ◽  
Intrinsic Disorder ◽  
Cellular Adhesion ◽  
Diabetic Patients ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Cellular Adhesion Molecule

Type 2 diabetes mellitus (T2DM) is a chronic and progressive disease that is strongly associated with the all-cause and cardiovascular mortality. The present study aimed to analyze the abundance and functionality of intrinsically disordered regions in several biomarkers of insulin resistance, adiponectin, and endothelial dysfunction found in the T2DM patients. In fact, in comparison to controls, obese T2DM patients are known to have significantly higher levels of inter-cellular adhesion molecule (iCAM-1), vascular cell adhesion molecule (vCAM-1), and E-selectin, whereas their adiponectin levels are relatively low. Bioinformatics analysis revealed that these selected biomarkers (iCAM-1, vCAM-1, E-selectin, and adiponectin) are characterized by the noticeable levels of intrinsic disorder propensity and high binding promiscuity, which are important features expected for proteins serving as biomarkers. Within the limit of studied groups, there is an association between insulin resistance and both hypoadiponectinemia and endothelial dysfunction.

MobiDB-lite 3.0: fast consensus annotation of intrinsic disorder flavors in proteins

2020 ◽  
Author(s):  
Marco Necci ◽  
Damiano Piovesan ◽  
Damiano Clementel ◽  
Zsuzsanna Dosztányi ◽  
Silvio C E Tosatto
Keyword(s):  
Large Scale ◽  
Theoretical Models ◽  
Intrinsic Disorder ◽  
Low Complexity ◽  
Compositional Bias ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Proteome Level ◽  
And Performance

Abstract Motivation The earlier version of MobiDB-lite is currently used in large-scale proteome annotation platforms to detect intrinsic disorder. However, new theoretical models allow for the classification of intrinsically disordered regions into subtypes from sequence features associated with specific polymeric properties or compositional bias. Results MobiDB-lite 3.0 maintains its previous speed and performance but also provides a finer classification of disorder by identifying regions with characteristics of polyolyampholytes, positive or negative polyelectrolytes, low-complexity regions or enriched in cysteine, proline or glycine or polar residues. Subregions are abundantly detected in IDRs of the human proteome. The new version of MobiDB-lite represents a new step for the proteome level analysis of protein disorder. Availability and implementation Both the MobiDB-lite 3.0 source code and a docker container are available from the GitHub repository:https://github.com/BioComputingUP/MobiDB-lite

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