scholarly journals Constructing Structure Ensembles of Intrinsically Disordered Proteins from Chemical Shift Data

2016 ◽  
Vol 23 (5) ◽  
pp. 300-310 ◽  
Author(s):  
Huichao Gong ◽  
Sai Zhang ◽  
Jiangdian Wang ◽  
Haipeng Gong ◽  
Jianyang Zeng
Keyword(s):  
Chemical Shift ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Intrinsically Disordered ◽  
Chemical Shift Data ◽  
Shift Data

scholarly journals Random coil chemical shifts for serine, threonine and tyrosine phosphorylation over a broad pH range

2019 ◽  
Vol 73 (12) ◽  
pp. 713-725 ◽  
Author(s):  
Ruth Hendus-Altenburger ◽  
Catarina B. Fernandes ◽  
Katrine Bugge ◽  
Micha B. A. Kunze ◽  
Wouter Boomsma ◽  
...  
Keyword(s):  
Chemical Shift ◽  
Secondary Structure ◽  
Intrinsically Disordered Proteins ◽  
Chemical Shifts ◽  
Random Coil ◽  
Disordered Proteins ◽  
Phosphoryl Group ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Secondary Chemical

Abstract Phosphorylation is one of the main regulators of cellular signaling typically occurring in flexible parts of folded proteins and in intrinsically disordered regions. It can have distinct effects on the chemical environment as well as on the structural properties near the modification site. Secondary chemical shift analysis is the main NMR method for detection of transiently formed secondary structure in intrinsically disordered proteins (IDPs) and the reliability of the analysis depends on an appropriate choice of random coil model. Random coil chemical shifts and sequence correction factors were previously determined for an Ac-QQXQQ-NH2-peptide series with X being any of the 20 common amino acids. However, a matching dataset on the phosphorylated states has so far only been incompletely determined or determined only at a single pH value. Here we extend the database by the addition of the random coil chemical shifts of the phosphorylated states of serine, threonine and tyrosine measured over a range of pH values covering the pKas of the phosphates and at several temperatures (www.bio.ku.dk/sbinlab/randomcoil). The combined results allow for accurate random coil chemical shift determination of phosphorylated regions at any pH and temperature, minimizing systematic biases of the secondary chemical shifts. Comparison of chemical shifts using random coil sets with and without inclusion of the phosphoryl group, revealed under/over estimations of helicity of up to 33%. The expanded set of random coil values will improve the reliability in detection and quantification of transient secondary structure in phosphorylation-modified IDPs.

scholarly journals Structure determination of protein-peptide complexes from NMR chemical shift data using MELD.

2022 ◽  
Author(s):  
Arup Mondal ◽  
G.V.T. Swapna ◽  
Jingzhou Hao ◽  
LiChung Ma ◽  
Monica J. Roth ◽  
...  
Keyword(s):  
Chemical Shift ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Bound State ◽  
Nmr Chemical Shift ◽  
Modeling Tools ◽  
Intrinsically Disordered ◽  
Intrinsically Disordered Regions ◽  
Chemical Shift Data ◽  
Shift Data

Intrinsically disordered regions of proteins often mediate important protein-protein interactions. However, the folding upon binding nature of many polypeptide-protein interactions limits the ability of modeling tools to predict structures of such complexes. To address this problem, we have taken a tandem approach combining NMR chemical shift data and molecular simulations to determine structures of peptide-protein complexes. Here, we demonstrate this approach for polypeptide com-plexes formed with the extraterminal (ET) domain of bromo and extraterminal domain (BET) proteins, which exhibit a high degree of binding plasticity. This system is particularly challenging as the binding process includes allosteric changes across the ET receptor upon binding, and the polypeptide binding partners can form different conformations (e.g., helices and hair-pins) in the complex. In a blind study, the new approach successfully modeled bound-state conformations and binding pos-es, using only backbone chemical shift data, in excellent agreement with experimentally-determined structures. The approach also predicts relative binding affinities of different peptides. This hybrid MELD-NMR approach provides a powerful new tool for structural analysis of protein-polypeptide complexes in the low NMR information content regime, which can be used successfully for flexible systems where one polypeptide binding partner folds upon complex formation.

Prediction of the Disordered Regions of Intrinsically Disordered Proteins Based on the Molecular Functions

2020 ◽  
Vol 27 (4) ◽  
pp. 279-286 ◽  
Author(s):  
WeiXia Xie ◽  
Yong E. Feng
Keyword(s):  
Chemical Shift ◽  
Intrinsically Disordered Proteins ◽  
Chemical Shifts ◽  
Disordered Proteins ◽  
Dimensional Structure ◽  
Support Vector ◽  
Functional Sites ◽  
Intrinsically Disordered ◽  
Molecular Functions ◽  
Disordered Regions

Background: Intrinsically disordered proteins lack a well-defined three dimensional structure under physiological conditions while possessing the essential biological functions. They take part in various physiological processes such as signal transduction, transcription and posttranslational modifications and etc. The disordered regions are the main functional sites for intrinsically disordered proteins. Therefore, the research of the disordered regions has become a hot issue. Objective: In this paper, our motivation is to analysis of the features of disordered regions with different molecular functions and predict of different disordered regions using valid features. Methods: In this article, according to the different molecular function, we firstly divided intrinsically disordered proteins into six classes in DisProt database. Then, we extracted four features using bioinformatics methods, namely, Amino Acid Index (AAIndex), codon frequency (Codon), three kinds of protein secondary structure compositions (3PSS) and Chemical Shifts (CSs), and used these features to predict the disordered regions of the different functions by Support Vector Machine (SVM). Results: The best overall accuracy was 99.29% using the chemical shift (CSs) as feature. In feature fusion, the overall accuracy can reach 88.70% by using CSs+AAIndex as features. The overall accuracy was up to 86.09% by using CSs+AAIndex+Codon+3PSS as features. Conclusion: We predicted and analyzed the disordered regions based on the molecular functions. The results showed that the prediction performance can be improved by adding chemical shifts and AAIndex as features, especially chemical shifts. Moreover, the chemical shift was the most effective feature in the prediction. We hoped that our results will be constructive for the study of intrinsically disordered proteins.

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