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 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 Disorder Atlas: web-based software for the proteome-based interpretation of intrinsic disorder predictions

2016 ◽  
Author(s):  
Michael Vincent ◽  
Santiago Schnell
Keyword(s):  
Large Scale ◽  
Intrinsically Disordered Proteins ◽  
Three Dimensional ◽  
Intrinsic Disorder ◽  
Query Protein ◽  
Disordered Proteins ◽  
Dimensional Structure ◽  
Web Based ◽  
Intrinsically Disordered ◽  
Eukaryotic Proteomes

AbstractIntrinsically disordered proteins lack a stable three-dimensional structure under physiological conditions. While this property has gained considerable interest within the past two decades, disorder poses substantial challenges to experimental characterization efforts. In effect, numerous computational tools have been developed to predict disorder from primary sequences, however, interpreting the output of these algorithms remains a challenge. To begin to bridge this gap, we present Disorder Atlas, web-based software that facilitates the interpretation of intrinsic disorder predictions using proteome-based descriptive statistics. This service is also equipped to facilitate large-scale systematic exploratory searches for proteins encompassing disorder features of interest, and further allows users to browse the prevalence of multiple disorder features at the proteome level. As a result, Disorder Atlas provides a user-friendly tool that places algorithm-generated disorder predictions in the context of the proteome, thereby providing an instrument to compare the results of a query protein against predictions made for an entire population. Disorder Atlas currently supports ten eukaryotic proteomes and is freely available for non-commercial users at http://www.disorderatlas.org.

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 Proteasomal degradation of the intrinsically disordered protein tau at single-residue resolution

2020 ◽  
Vol 6 (30) ◽  
pp. eaba3916 ◽  
Author(s):  
T. Ukmar-Godec ◽  
P. Fang ◽  
A. Ibáñez de Opakua ◽  
F. Henneberg ◽  
A. Godec ◽  
...  
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Degradation Products ◽  
Degradation Kinetics ◽  
Intrinsically Disordered Protein ◽  
Disordered Proteins ◽  
Dependent Protein Kinase ◽  
Intrinsically Disordered ◽  
Disordered Protein ◽  
Dependent Protein ◽  
Independent Process

Intrinsically disordered proteins (IDPs) can be degraded in a ubiquitin-independent process by the 20S proteasome. Decline in 20S activity characterizes neurodegenerative diseases. Here, we examine 20S degradation of IDP tau, a protein that aggregates into insoluble deposits in Alzheimer’s disease. We show that cleavage of tau by the 20S proteasome is most efficient within the aggregation-prone repeat region of tau and generates both short, aggregation-deficient peptides and two long fragments containing residues 1 to 251 and 1 to 218. Phosphorylation of tau by the non-proline–directed Ca2+/calmodulin-dependent protein kinase II inhibits degradation by the 20S proteasome. Phosphorylation of tau by GSK3β, a major proline-directed tau kinase, modulates tau degradation kinetics in a residue-specific manner. The study provides detailed insights into the degradation products of tau generated by the 20S proteasome, the residue specificity of degradation, single-residue degradation kinetics, and their regulation by posttranslational modification.

Sequence Specificity Despite Intrinsic Disorder: How a Disease-Associated Val/Met Polymorphism Shifts Tertiary Interactions in a Long Disordered Protein

2019 ◽  
Author(s):  
Ruchi Lohia ◽  
Reza Salari ◽  
Grace Brannigan
Keyword(s):  
Secondary Structure ◽  
Electrostatic Interactions ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Sequence Specificity ◽  
Intrinsically Disordered ◽  
Specific Effects ◽  
Heterogeneous Polymer ◽  
Non Local ◽  
Dynamics Simulations

<div>The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) encodes a hydrophobic-to-hydrophobic mutation at the midpoint of the prodomain of precursor brain-derived neurotrophic factor (BDNF), one of the earliest SNPs to be associated with neuropsychiatric disorders, for which the underlying molecular mechanism is unknown. Here we report on over 250 μs of fully-atomistic, explicit solvent, temperature replica exchange molecular dynamics simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence.</div><div>The simulations were able to correctly reproduce the location of both local and non-local secondary changes due to the Val66Met mutation when compared with NMR spectroscopy. We find that the local structure change is mediated via entropic and sequence specific effects. We show that the highly disordered prodomain can be meaningfully divided into domains based on sequence alone. Monte Carlo simulations of a self-excluding heterogeneous polymer, with monomers representing each domain, suggest the sequence would be effectively segmented by the long, highly disordered polyampholyte near the sequence midpoint. This is qualitatively consistent with observed interdomain contacts within the BDNF prodomain, although contacts between the two segments are enriched relative to the self-excluding polymer. The Val66Met mutation increases interactions across the boundary between the two segments, due in part to a specific Met-Met interaction with a Methionine in the other segment. This effect propagates to cause the non-local change in secondary structure around the second methionine, previously observed in NMR. The effect is not mediated simply via changes in inter-domain contacts but is also dependent on secondary structure formation around residue 66, indicating a mechanism for secondary structure coupling in disordered proteins. </div>

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