scholarly journals DispHred: A Server to Predict pH-Dependent Order–Disorder Transitions in Intrinsically Disordered Proteins

2020 ◽  
Vol 21 (16) ◽  
pp. 5814 ◽  
Author(s):  
Jaime Santos ◽  
Valentín Iglesias ◽  
Carlos Pintado ◽  
Juan Santos-Suárez ◽  
Salvador Ventura
Keyword(s):  
Intrinsically Disordered Proteins ◽  
State Of The Art ◽  
Disordered Proteins ◽  
Protein Disorder ◽  
Net Charge ◽  
Intrinsically Disordered ◽  
Linear Boundary Condition ◽  
Natively Unfolded ◽  
Ph Dependent ◽  
Very High

The natively unfolded nature of intrinsically disordered proteins (IDPs) relies on several physicochemical principles, of which the balance between a low sequence hydrophobicity and a high net charge appears to be critical. Under this premise, it is well-known that disordered proteins populate a defined region of the charge–hydropathy (C–H) space and that a linear boundary condition is sufficient to distinguish between folded and disordered proteins, an approach widely applied for the prediction of protein disorder. Nevertheless, it is evident that the C–H relation of a protein is not unalterable but can be modulated by factors extrinsic to its sequence. Here, we applied a C–H-based analysis to develop a computational approach that evaluates sequence disorder as a function of pH, assuming that both protein net charge and hydrophobicity are dependent on pH solution. On that basis, we developed DispHred, the first pH-dependent predictor of protein disorder. Despite its simplicity, DispHred displays very high accuracy in identifying pH-induced order/disorder protein transitions. DispHred might be useful for diverse applications, from the analysis of conditionally disordered segments to the synthetic design of disorder tags for biotechnological applications. Importantly, since many disorder predictors use hydrophobicity as an input, the here developed framework can be implemented in other state-of-the-art algorithms.

scholarly journals Prediction of the effect of pH on the aggregation and conditional folding of intrinsically disordered proteins with SolupHred and DispHred.

2021 ◽  
Author(s):  
Valentin Iglesias ◽  
Carlos Pintado-Grima ◽  
Jaime Santos ◽  
Marc Fornt ◽  
Salvador Ventura
Keyword(s):  
Conformational Changes ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Net Charge ◽  
Software Applications ◽  
Intrinsically Disordered ◽  
Binding Partners ◽  
Dissolved Ions ◽  
Ph Dependent ◽  
User Friendly

Proteins microenvironments modulate their structures. Binding partners, organic molecules, or dissolved ions can alter the protein's compaction, inducing aggregation or order-disorder conformational transitions. Surprisingly, bioinformatic platforms often disregard the protein context in their modeling. In recent work, we proposed that modeling how pH affects protein net charge and hydrophobicity might allow us to forecast pH-dependent aggregation and conditional disorder in intrinsically disordered proteins (IDPs). As these approaches showed remarkable success in recapitulating the available bibliographical data, we made these prediction methods available for the scientific community as two user-friendly web servers. SolupHred is the first dedicated software to predict pH-dependent aggregation, and DispHred is the first pH-dependent predictor of protein disorder. Here we dissect the features of these two software applications to train and assist scientists in studying pH-dependent conformational changes in IDPs.

scholarly journals The Mysterious Unfoldome: Structureless, Underappreciated, Yet Vital Part of Any Given Proteome

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Vladimir N. Uversky
Keyword(s):  
Large Scale ◽  
Intrinsically Disordered Proteins ◽  
Biologically Active ◽  
Disordered Proteins ◽  
Unfolded Proteins ◽  
Intrinsically Disordered ◽  
Proteome Level ◽  
Natively Unfolded ◽  
Natively Unfolded Proteins

Contrarily to the general believe, many biologically active proteins lack stable tertiary and/or secondary structure under physiological conditions in vitro. These intrinsically disordered proteins (IDPs) are highly abundant in nature and many of them are associated with various human diseases. The functional repertoire of IDPs complements the functions of ordered proteins. Since IDPs constitute a significant portion of any given proteome, they can be combined in an unfoldome; which is a portion of the proteome including all IDPs (also known as natively unfolded proteins, therefore, unfoldome), and describing their functions, structures, interactions, evolution, and so forth. Amino acid sequence and compositions of IDPs are very different from those of ordered proteins, making possible reliable identification of IDPs at the proteome level by various computational means. Furthermore, IDPs possess a number of unique structural properties and are characterized by a peculiar conformational behavior, including their high stability against low pH and high temperature and their structural indifference toward the unfolding by strong denaturants. These peculiarities were shown to be useful for elaboration of the experimental techniques for the large-scale identification of IDPs in various organisms. Some of the computational and experimental tools for the unfoldome discovery are discussed in this review.

Molecular simulations of protein disorderThis paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular & Cellular Biology 52nd Annual Meeting — Protein Folding: Principles and Diseases” and has undergone the Journal's usual peer review process.

2010 ◽  
Vol 88 (2) ◽  
pp. 269-290 ◽  
Author(s):  
Sarah Rauscher ◽  
Régis Pomès
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Peer Review Process ◽  
Structural Heterogeneity ◽  
Disordered Proteins ◽  
Cellular Biology ◽  
Protein Disorder ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
Simulation Techniques ◽  
Selection Of

Protein disorder is abundant in proteomes throughout all kingdoms of life and serves many biologically important roles. Disordered states of proteins are challenging to study experimentally due to their structural heterogeneity and tendency to aggregate. Computer simulations, which are not impeded by these properties, have recently emerged as a useful tool to characterize the conformational ensembles of intrinsically disordered proteins. In this review, we provide a survey of computational studies of protein disorder with an emphasis on the interdisciplinary nature of these studies. The application of simulation techniques to the study of disordered states is described in the context of experimental and bioinformatics approaches. Experimental data can be incorporated into simulations, and simulations can provide predictions for experiment. In this way, simulations have been integrated into the existing methodologies for the study of disordered state ensembles. We provide recent examples of simulations of disordered states from the literature and our own work. Throughout the review, we emphasize important predictions and biophysical understanding made possible through the use of simulations. This review is intended as both an overview and a guide for structural biologists and theoretical biophysicists seeking accurate, atomic-level descriptions of disordered state ensembles.

scholarly journals Charge fluctuation effects on the shape of flexible polyampholytes with applications to Intrinsically disordered proteins

2018 ◽  
Author(s):  
Himadri S. Samanta ◽  
Debayan Chakraborty ◽  
D. Thirumalai
Keyword(s):  
Electrostatic Interactions ◽  
Intrinsically Disordered Proteins ◽  
Debye Length ◽  
Disordered Proteins ◽  
Radius Of Gyration ◽  
Charge Fluctuation ◽  
Net Charge ◽  
Intrinsically Disordered ◽  
X Ray Scattering ◽  
Theoretical Predictions

Random polyampholytes (PAs) contain positively and negatively charged monomers that are distributed randomly along the polymer chain. The interaction between charges is assumed to be given by the Debye-Huckel potential. We show that the size of the PA is determined by an interplay between electrostatic interactions, giving rise to the polyelectrolyte (PE) effect due to net charge per monomer (σ), and an effective attractive PA interaction due to charge fluctuations, δσ. The interplay between these terms gives rise to non-monotonic dependence of the radius of gyration, Rg on the inverse Debye length, κ when PA effects are important . In the opposite limit, Rg decreases monotonically with increasing κ. Simulations of PA chains, using a charged bead-spring model, further corroborates our theoretical predictions. The simulations unambiguously show that conformational heterogeneity manifests itself among sequences that have identical PA parameters. A clear implication is that the phases of PA sequences, and by inference IDPs, cannot be determined using only the bare PA parameters (σ and δσ).The theory is used to calculate the changes in Rg on N, the number of residues for a set of Intrinsically Disordered Proteins (IDPs). For a certain class of IDPs, with N between 24 to 441, the size grows as Rg ~ N0.6, which agrees with data from Small Angle X-ray Scattering (SAXS) experiments.

scholarly journals DisProt: intrinsic protein disorder annotation in 2020

2019 ◽  
Author(s):  
András Hatos ◽  
Borbála Hajdu-Soltész ◽  
Alexander M Monzon ◽  
Nicolas Palopoli ◽  
Lucía Álvarez ◽  
...  
Keyword(s):  
Text Mining ◽  
Search Engine ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Protein Disorder ◽  
Graphical Interface ◽  
Intrinsically Disordered ◽  
Intrinsic Protein Disorder ◽  
Recent Developments ◽  
Programmatic Access

Abstract The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome.

SolupHred: a server to predict the pH-dependent aggregation of intrinsically disordered proteins

2020 ◽  
Author(s):  
Carlos Pintado ◽  
Jaime Santos ◽  
Valentín Iglesias ◽  
Salvador Ventura
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Solution Ph ◽  
Predictive Tool ◽  
Web Based ◽  
Intrinsically Disordered ◽  
Dependent Protein ◽  
Ph Dependent

Abstract Summary Polypeptides are exposed to changing environmental conditions that modulate their intrinsic aggregation propensities. Intrinsically disordered proteins (IDPs) constitutively expose their aggregation determinants to the solvent, thus being especially sensitive to its fluctuations. However, solvent conditions are often disregarded in computational aggregation predictors. We recently developed a phenomenological model to predict IDPs' solubility as a function of the solution pH, which is based on the assumption that both protein lipophilicity and charge depend on this parameter. The model anticipated solubility changes in different IDPs accurately. In this application note, we present SolupHred, a web-based interface that implements the aforementioned theoretical framework into a predictive tool able to compute IDPs aggregation propensities as a function of pH. SolupHred is the first dedicated software for the prediction of pH-dependent protein aggregation. Availability and implementation The SolupHred web server is freely available for academic users at: https://ppmclab.pythonanywhere.com/SolupHred. It is platform-independent and does not require previous registration. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals pH-Dependent Aggregation in Intrinsically Disordered Proteins Is Determined by Charge and Lipophilicity

Cells ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 145 ◽  
Author(s):  
Jaime Santos ◽  
Valentín Iglesias ◽  
Juan Santos-Suárez ◽  
Marco Mangiagalli ◽  
Stefania Brocca ◽  
...  
Keyword(s):  
Large Scale ◽  
Intrinsically Disordered Proteins ◽  
Phenomenological Approach ◽  
Premature Aging ◽  
Disordered Proteins ◽  
Solution Ph ◽  
Intrinsically Disordered ◽  
Large Scale Analysis ◽  
Human Disorders ◽  
Ph Dependent

Protein aggregation is associated with an increasing number of human disorders and premature aging. Moreover, it is a central concern in the manufacturing of recombinant proteins for biotechnological and therapeutic applications. Nevertheless, the unique architecture of protein aggregates is also exploited by nature for functional purposes, from bacteria to humans. The relevance of this process in health and disease has boosted the interest in understanding and controlling aggregation, with the concomitant development of a myriad of algorithms aimed to predict aggregation propensities. However, most of these programs are blind to the protein environment and, in particular, to the influence of the pH. Here, we developed an empirical equation to model the pH-dependent aggregation of intrinsically disordered proteins (IDPs) based on the assumption that both the global protein charge and lipophilicity depend on the solution pH. Upon its parametrization with a model IDP, this simple phenomenological approach showed unprecedented accuracy in predicting the dependence of the aggregation of both pathogenic and functional amyloidogenic IDPs on the pH. The algorithm might be useful for diverse applications, from large-scale analysis of IDPs aggregation properties to the design of novel reversible nanofibrillar materials.

scholarly journals A Unified De Novo Approach for Predicting the Structures of Ordered and Disordered Proteins

2020 ◽  
Author(s):  
John J. Ferrie ◽  
E. James Petersson
Keyword(s):  
Intrinsically Disordered Proteins ◽  
De Novo ◽  
State Of The Art ◽  
Md Simulations ◽  
Disordered Proteins ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
Structural Ensembles ◽  
Recent Developments ◽  
Fold Prediction

AbstractAs recognition of the abundance and relevance of intrinsically disordered proteins (IDPs) continues to grow, demand increases for methods that can rapidly predict the conformational ensembles populated by these proteins. To date, IDP simulations have largely been dominated by molecular dynamics (MD) simulations, which require significant compute times and/or complex hardware. Recent developments in MD have afforded methods capable of simulating both ordered and disordered proteins, yet to date accurate fold prediction from sequence has been dominated by Monte-Carlo (MC) based methods such as Rosetta. To overcome the limitations of current approaches in IDP simulation using Rosetta while maintaining its utility for modeling folded domains, we developed PyRosetta-based algorithms that allow for the accurate de novo prediction of proteins across all degrees of foldedness along with structural ensembles of disordered proteins. Our simulations have an accuracy comparable to state-of-the-art MD with vastly reduced computational demands.

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