Using chemical shifts to generate structural ensembles for intrinsically disordered proteins with converged distributions of secondary structure

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.

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Using NMR Chemical Shifts to Determine Residue-Specific Secondary Structure Populations for Intrinsically Disordered Proteins

Methods in Enzymology - Intrinsically Disordered Proteins ◽

10.1016/bs.mie.2018.09.011 ◽

2018 ◽

pp. 101-136 ◽

Cited By ~ 4

Author(s):

Wade M. Borcherds ◽

Gary W. Daughdrill

Keyword(s):

Secondary Structure ◽

Intrinsically Disordered Proteins ◽

Chemical Shifts ◽

Disordered Proteins ◽

Nmr Chemical Shifts ◽

Intrinsically Disordered

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The accuracy of force fields on the simulation of intrinsically disordered proteins: A benchmark test on the human p53 tumor suppressor

Journal of Theoretical and Computational Chemistry ◽

10.1142/s021963362050011x ◽

2020 ◽

Vol 19 (04) ◽

pp. 2050011

Author(s):

Shangbo Ning ◽

Jun Liu ◽

Na Liu ◽

Dazhong Yan

Keyword(s):

Md Simulation ◽

Intrinsically Disordered Proteins ◽

Force Fields ◽

Chemical Shifts ◽

Disordered Proteins ◽

Experimental Measurements ◽

Intrinsically Disordered ◽

Structural Ensembles ◽

Water Models ◽

Structural Ensemble

Intrinsically disordered proteins (IDPs) are a class of proteins without stable three-dimensional structures under physiological conditions. IDPs exhibit high dynamic nature and could be described by structural ensembles. As one of the most widely used tools, molecular dynamics (MD) simulation could provide the atomic descriptions of the structural ensemble of IDPs. However, the accuracy of the MD simulation largely depends on the accuracy of the force field. In this paper, we compared the structural ensembles of the activation domain 1 (AD1) in p53 tumor suppressor obtained from the widely used force fields, AMBER99SB-ILDN, CHARMM27, CHARMM36m with different water models. The results show that CHARMM36m generates more extended conformations than other force fields, while CHARMM27 prefers to sample the [Formula: see text]-helical structure. Moreover, the chemical shifts obtained by CHARMM36m are the closest to the experimental measurements. These results indicate that the CHARMM36m force field performs best in characterizing the structure properties of p53 AD1. Water models are also critical to describe the structural ensemble of IDPs. TIP4P water model can obtain more extended conformations and produce more local helical conformations than the TIP3P model in our simulation. In addition, we also compare the chemical shifts predicted by different chemical shift predicting programs with experimental measurements, the results show that SHIFTX2 obtains the best performance in the chemical shifts prediction.

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Using Chemical Shifts to Assess Transient Secondary Structure and Generate Ensemble Structures of Intrinsically Disordered Proteins

Methods in Molecular Biology - Intrinsically Disordered Protein Analysis ◽

10.1007/978-1-61779-927-3_11 ◽

2012 ◽

pp. 139-152 ◽

Cited By ~ 9

Author(s):

Stepan Kashtanov ◽

Wade Borcherds ◽

Hongwei Wu ◽

Gary W. Daughdrill ◽

F. Marty Ytreberg

Keyword(s):

Secondary Structure ◽

Intrinsically Disordered Proteins ◽

Chemical Shifts ◽

Disordered Proteins ◽

Intrinsically Disordered ◽

Transient Secondary Structure

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

10.26434/chemrxiv.8135777.v1 ◽

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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Generation of the configurational ensemble of an intrinsically disordered protein from unbiased molecular dynamics simulation

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1907251116 ◽

2019 ◽

Vol 116 (41) ◽

pp. 20446-20452 ◽

Cited By ~ 9

Author(s):

Utsab R. Shrestha ◽

Puneet Juneja ◽

Qiu Zhang ◽

Viswanathan Gurumoorthy ◽

Jose M. Borreguero ◽

...

Keyword(s):

Molecular Dynamics ◽

Intrinsically Disordered Proteins ◽

Chemical Shifts ◽

Intrinsically Disordered Protein ◽

Physical Models ◽

Dynamics Simulation ◽

Disordered Proteins ◽

Intrinsically Disordered ◽

Eukaryotic Proteomes ◽

Heterogeneous Ensemble

Intrinsically disordered proteins (IDPs) are abundant in eukaryotic proteomes, play a major role in cell signaling, and are associated with human diseases. To understand IDP function it is critical to determine their configurational ensemble, i.e., the collection of 3-dimensional structures they adopt, and this remains an immense challenge in structural biology. Attempts to determine this ensemble computationally have been hitherto hampered by the necessity of reweighting molecular dynamics (MD) results or biasing simulation in order to match ensemble-averaged experimental observables, operations that reduce the precision of the generated model because different structural ensembles may yield the same experimental observable. Here, by employing enhanced sampling MD we reproduce the experimental small-angle neutron and X-ray scattering profiles and the NMR chemical shifts of the disordered N terminal (SH4UD) of c-Src kinase without reweighting or constraining the simulations. The unbiased simulation results reveal a weakly funneled and rugged free energy landscape of SH4UD, which gives rise to a heterogeneous ensemble of structures that cannot be described by simple polymer theory. SH4UD adopts transient helices, which are found away from known phosphorylation sites and could play a key role in the stabilization of structural regions necessary for phosphorylation. Our findings indicate that adequately sampled molecular simulations can be performed to provide accurate physical models of flexible biosystems, thus rationalizing their biological function.

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An Evolutionary Algorithm for the Design of Different Degrees of Secondary Structure in Intrinsically Disordered Proteins (IDPs)

Biophysical Journal ◽

10.1016/j.bpj.2014.11.1259 ◽

2015 ◽

Vol 108 (2) ◽

pp. 228a ◽

Cited By ~ 1

Author(s):

Tyler S. Harmon ◽

Rohit V. Pappu

Keyword(s):

Secondary Structure ◽

Evolutionary Algorithm ◽

Intrinsically Disordered Proteins ◽

Disordered Proteins ◽

Intrinsically Disordered

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Sequence Versus Composition: What Prescribes IDP Biophysical Properties?

Entropy ◽

10.3390/e21070654 ◽

2019 ◽

Vol 21 (7) ◽

pp. 654 ◽

Cited By ~ 2

Author(s):

Jiří Vymětal ◽

Jiří Vondrášek ◽

Klára Hlouchová

Keyword(s):

Amino Acid ◽

Secondary Structure ◽

Intrinsically Disordered Proteins ◽

Random Sequence ◽

Bioinformatic Analysis ◽

Globular Proteins ◽

Disordered Proteins ◽

Compositional Bias ◽

Intrinsically Disordered ◽

Sequence Versus

Intrinsically disordered proteins (IDPs) represent a distinct class of proteins and are distinguished from globular proteins by conformational plasticity, high evolvability and a broad functional repertoire. Some of their properties are reminiscent of early proteins, but their abundance in eukaryotes, functional properties and compositional bias suggest that IDPs appeared at later evolutionary stages. The spectrum of IDP properties and their determinants are still not well defined. This study compares rudimentary physicochemical properties of IDPs and globular proteins using bioinformatic analysis on the level of their native sequences and random sequence permutations, addressing the contributions of composition versus sequence as determinants of the properties. IDPs have, on average, lower predicted secondary structure contents and aggregation propensities and biased amino acid compositions. However, our study shows that IDPs exhibit a broad range of these properties. Induced fold IDPs exhibit very similar compositions and secondary structure/aggregation propensities to globular proteins, and can be distinguished from unfoldable IDPs based on analysis of these sequence properties. While amino acid composition seems to be a major determinant of aggregation and secondary structure propensities, sequence randomization does not result in dramatic changes to these properties, but for both IDPs and globular proteins seems to fine-tune the tradeoff between folding and aggregation.

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