scholarly journals Investigating the Conformational Ensembles of Intrinsically-Disordered Proteins with a Simple Physics-Based Model

2020 ◽  
Author(s):  
Yani Zhao ◽  
Robinson Cortes-Huerto ◽  
Kurt Kremer ◽  
Joseph F. Rudzinski
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Conformational Dynamics ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Side Chain ◽  
Conformational Ensemble ◽  
Single Chain ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
The Impact

Intrinsically disordered proteins (IDPs) play an important role in an array of biological processes but present a number of fundamental challenges for computational modeling. Recently, simple polymer models have re-gained popularity for interpreting the experimental characterization of IDPs. Homopolymer theory provides a strong foundation for understanding generic features of phenomena ranging from single-chain conformational dynamics to the properties of entangled polymer melts, but is difficult to extend to the copolymer context. This challenge is magnified for proteins due to the variety of competing interactions and large deviations in side-chain properties. In this work, we apply a simple physics-based coarse-grained model for describing largely disordered conformational ensembles of peptides, based on the premise that sampling sterically-forbidden conformations can compromise the faithful description of both static and dynamical properties. The Hamiltonian of the employed model can be easily adjusted to investigate the impact of distinct interactions and sequence specificity on the randomness of the resulting conformational ensemble. In particular, starting with a bead-spring-like model and then adding more detailed interactions one by one, we construct a hierarchical set of models and perform a detailed comparison of their properties. Our analysis clarifies the role of generic attractions, electrostatics and side-chain sterics, while providing a foundation for developing efficient models for IDPs that retain an accurate description of the hierarchy of conformational dynamics, which is nontrivially influenced by interactions with surrounding proteins and solvent molecules.

scholarly journals Information theoretic measures for quantifying sequence–ensemble relationships of intrinsically disordered proteins

2019 ◽  
Vol 32 (4) ◽  
pp. 191-202 ◽  
Author(s):  
Megan C Cohan ◽  
Kiersten M Ruff ◽  
Rohit V Pappu
Keyword(s):  
Intrinsically Disordered Proteins ◽  
De Novo ◽  
Disordered Proteins ◽  
Specific Sequence ◽  
Information Theoretic ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
Information Theoretic Measures ◽  
Modulating Functions ◽  
The Impact

Abstract Intrinsically disordered proteins (IDPs) contribute to a multitude of functions. De novo design of IDPs should open the door to modulating functions and phenotypes controlled by these systems. Recent design efforts have focused on compositional biases and specific sequence patterns as the design features. Analysis of the impact of these designs on sequence-function relationships indicates that individual sequence/compositional parameters are insufficient for describing sequence-function relationships in IDPs. To remedy this problem, we have developed information theoretic measures for sequence–ensemble relationships (SERs) of IDPs. These measures rely on prior availability of statistically robust conformational ensembles derived from all atom simulations. We show that the measures we have developed are useful for comparing sequence-ensemble relationships even when sequence is poorly conserved. Based on our results, we propose that de novo designs of IDPs, guided by knowledge of their SERs, should provide improved insights into their sequence–ensemble–function relationships.

scholarly journals Phosphorylation-induced conformational dynamics in an intrinsically disordered protein and potential role in phenotypic heterogeneity

2017 ◽  
Vol 114 (13) ◽  
pp. E2644-E2653 ◽  
Author(s):  
Prakash Kulkarni ◽  
Mohit Kumar Jolly ◽  
Dongya Jia ◽  
Steven M. Mooney ◽  
Ajay Bhargava ◽  
...  
Keyword(s):  
Single Molecule ◽  
Intrinsically Disordered Proteins ◽  
Large Fraction ◽  
Conformational Dynamics ◽  
3D Structure ◽  
Random Coil ◽  
Disordered Proteins ◽  
Conformational Ensemble ◽  
Intrinsically Disordered ◽  
Androgen Independent

Intrinsically disordered proteins (IDPs) that lack a unique 3D structure and comprise a large fraction of the human proteome play important roles in numerous cellular functions. Prostate-Associated Gene 4 (PAGE4) is an IDP that acts as a potentiator of the Activator Protein-1 (AP-1) transcription factor. Homeodomain-Interacting Protein Kinase 1 (HIPK1) phosphorylates PAGE4 at S9 and T51, but only T51 is critical for its activity. Here, we identify a second kinase, CDC-Like Kinase 2 (CLK2), which acts on PAGE4 and hyperphosphorylates it at multiple S/T residues, including S9 and T51. We demonstrate that HIPK1 is expressed in both androgen-dependent and androgen-independent prostate cancer (PCa) cells, whereas CLK2 and PAGE4 are expressed only in androgen-dependent cells. Cell-based studies indicate that PAGE4 interaction with the two kinases leads to opposing functions. HIPK1-phosphorylated PAGE4 (HIPK1-PAGE4) potentiates c-Jun, whereas CLK2-phosphorylated PAGE4 (CLK2-PAGE4) attenuates c-Jun activity. Consistent with the cellular data, biophysical measurements (small-angle X-ray scattering, single-molecule fluorescence resonance energy transfer, and NMR) indicate that HIPK1-PAGE4 exhibits a relatively compact conformational ensemble that binds AP-1, whereas CLK2-PAGE4 is more expanded and resembles a random coil with diminished affinity for AP-1. Taken together, the results suggest that the phosphorylation-induced conformational dynamics of PAGE4 may play a role in modulating changes between PCa cell phenotypes. A mathematical model based on our experimental data demonstrates how differential phosphorylation of PAGE4 can lead to transitions between androgen-dependent and androgen-independent phenotypes by altering the AP-1/androgen receptor regulatory circuit in PCa cells.

scholarly journals Recent Advances in Computational Protocols Addressing Intrinsically Disordered Proteins

Biomolecules ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 146 ◽  
Author(s):  
Supriyo Bhattacharya ◽  
Xingcheng Lin
Keyword(s):  
Single Molecule ◽  
Degrees Of Freedom ◽  
Intrinsically Disordered Proteins ◽  
Structural Information ◽  
Conformational Dynamics ◽  
Resonance Energy ◽  
Structural Data ◽  
Disordered Proteins ◽  
Conformational Ensemble ◽  
Intrinsically Disordered

Intrinsically disordered proteins (IDP) are abundant in the human genome and have recently emerged as major therapeutic targets for various diseases. Unlike traditional proteins that adopt a definitive structure, IDPs in free solution are disordered and exist as an ensemble of conformations. This enables the IDPs to signal through multiple signaling pathways and serve as scaffolds for multi-protein complexes. The challenge in studying IDPs experimentally stems from their disordered nature. Nuclear magnetic resonance (NMR), circular dichroism, small angle X-ray scattering, and single molecule Förster resonance energy transfer (FRET) can give the local structural information and overall dimension of IDPs, but seldom provide a unified picture of the whole protein. To understand the conformational dynamics of IDPs and how their structural ensembles recognize multiple binding partners and small molecule inhibitors, knowledge-based and physics-based sampling techniques are utilized in-silico, guided by experimental structural data. However, efficient sampling of the IDP conformational ensemble requires traversing the numerous degrees of freedom in the IDP energy landscape, as well as force-fields that accurately model the protein and solvent interactions. In this review, we have provided an overview of the current state of computational methods for studying IDP structure and dynamics and discussed the major challenges faced in this field.

scholarly journals Dual roles of electrostatic-steering and conformational dynamics in the binding of calcineurin’s intrinsically-disordered recognition domain to calmodulin

2018 ◽  
Author(s):  
Bin Sun ◽  
Eric C. Cook ◽  
Trevor P. Creamer ◽  
Peter M. Kekenes-Huskey
Keyword(s):  
Long Range ◽  
Electrostatic Interactions ◽  
Intrinsically Disordered Proteins ◽  
Conformational Dynamics ◽  
Disordered Proteins ◽  
Conformational Ensemble ◽  
Regulatory Domain ◽  
Intrinsically Disordered ◽  
Diffusion Limited ◽  
Conformational Diversity

calcineurin (CaN) is a serine/threonine phosphatase that regulates a variety of physiological and pathophysiological processes in mammalian tissue. The CaN regulatory domain (RD) is responsible for regulating the enzyme’s phosphatase activity, and is believed to be highly-disordered when inhibiting CaN, but undergoes a disorderto-order transition upon diffusion-limited binding with the regulatory protein calmodulin (CaM). The prevalence of polar and charged amino acids in the regulatory domain (RD) suggests electrostatic interactions are involved in mediating CaM binding, yet the lack of atomistic-resolution data for the bound complex has stymied efforts to probe how the RD sequence controls its conformational ensemble and long-range attractions contribute to target protein binding. In the present study, we investigated via computational modeling the extent to which electrostatics and structural disorder cofacilitate or hinder CaM/CaN association kinetics. Specifically, we examined several RD constructs that contain the CaM binding region (CAMBR) to characterize the roles of electrostatics versus conformational diversity in controlling diffusion-limited association rates, via microsecond-scale molecular dynamics (MD) and Brownian dynamic (BD) simulations. Our results indicate that the RD amino acid composition and sequence length influence both the dynamic availability of conformations amenable to CaM binding, as well as long-range electrostatic interactions to steer association. These findings provide intriguing insight into the interplay between conformational diversity and electrostatically-driven protein-protein association involving CaN, which are likely to extend to wide-ranging diffusion-limited processes regulated by intrinsically-disordered proteins.

scholarly journals Improving the global dimensions of intrinsically disordered proteins in Martini 3

2021 ◽  
Author(s):  
F. Emil Thomasen ◽  
Francesco Pesce ◽  
Mette Ahrensback Roesgaard ◽  
Giulio Tesei ◽  
Kresten Lindorff-Larsen
Keyword(s):  
Molecular Dynamics ◽  
Intrinsically Disordered Proteins ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Saxs Data ◽  
X Ray ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
X Ray Scattering ◽  
Dynamics Simulations

AbstractCoarse-grained molecular dynamics simulations are a useful tool to determine conformational ensembles of intrinsically disordered proteins (IDPs). Here, we show that the coarse-grained force field Martini 3 underestimates the global dimensions of IDPs when compared with small angle X-ray scattering (SAXS) data. Increasing the strength of protein-water interactions favors more expanded conformations, improving agreement with SAXS data and alleviating problems with overestimated IDP-IDP interactions.

scholarly journals Accurate model of liquid-liquid phase behaviour of intrinsically-disordered proteins from data-driven optimization of single-chain properties

2021 ◽  
Author(s):  
Giulio Tesei ◽  
Thea K. Schulze ◽  
Ramon Crehuet ◽  
Kresten Lindorff-Larsen
Keyword(s):  
Liquid Phase ◽  
Intrinsically Disordered Proteins ◽  
Molecular Simulations ◽  
Phase Behaviour ◽  
Data Driven ◽  
Coarse Grained ◽  
Disordered Proteins ◽  
Model Parameters ◽  
Single Chain ◽  
Intrinsically Disordered

Many intrinsically disordered proteins (IDPs) may undergo liquid-liquid phase separation (LLPS) and participate in the formation of membraneless organelles in the cell, thereby contributing to the regulation and compartmentalisation of intracellular biochemical reactions. The phase behaviour of IDPs is sequence-dependent, and its investigation through molecular simulations requires protein models that combine computational efficiency with an accurate description of intra- and intermolecular interactions. We developed a general coarse-grained model of IDPs, with residue-level detail, based on an extensive set of experimental data on single-chain properties. Ensemble-averaged experimental observables are predicted from molecular simulations, and a data-driven parameter-learning procedure is used to identify the residue-specific model parameters that minimize the discrepancy between predictions and experiments. The model accurately reproduces the experimentally observed conformational propensities of a set of IDPs. Through two-body as well as large-scale molecular simulations, we show that the optimization of the intramolecular interactions results in improved predictions of protein self-association and LLPS.

scholarly journals Properties of protein unfolded states suggest broad selection for expanded conformational ensembles

2020 ◽  
Vol 117 (38) ◽  
pp. 23356-23364 ◽  
Author(s):  
Micayla A. Bowman ◽  
Joshua A. Riback ◽  
Anabel Rodriguez ◽  
Hongyu Guo ◽  
Jun Li ◽  
...  
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Protein Structures ◽  
Water Soluble ◽  
Disordered Proteins ◽  
Conformational Ensemble ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
Sequence Patterns ◽  
Selection For

Much attention is being paid to conformational biases in the ensembles of intrinsically disordered proteins. However, it is currently unknown whether or how conformational biases within the disordered ensembles of foldable proteins affect function in vivo. Recently, we demonstrated that water can be a good solvent for unfolded polypeptide chains, even those with a hydrophobic and charged sequence composition typical of folded proteins. These results run counter to the generally accepted model that protein folding begins with hydrophobicity-driven chain collapse. Here we investigate what other features, beyond amino acid composition, govern chain collapse. We found that local clustering of hydrophobic and/or charged residues leads to significant collapse of the unfolded ensemble of pertactin, a secreted autotransporter virulence protein fromBordetella pertussis, as measured by small angle X-ray scattering (SAXS). Sequence patterns that lead to collapse also correlate with increased intermolecular polypeptide chain association and aggregation. Crucially, sequence patterns that support an expanded conformational ensemble enhance pertactin secretion to the bacterial cell surface. Similar sequence pattern features are enriched across the large and diverse family of autotransporter virulence proteins, suggesting sequence patterns that favor an expanded conformational ensemble are under selection for efficient autotransporter protein secretion, a necessary prerequisite for virulence. More broadly, we found that sequence patterns that lead to more expanded conformational ensembles are enriched across water-soluble proteins in general, suggesting protein sequences are under selection to regulate collapse and minimize protein aggregation, in addition to their roles in stabilizing folded protein structures.

scholarly journals Computing, analyzing and comparing the radius of gyration and hydrodynamic radius in conformational ensembles of intrinsically disordered proteins

2019 ◽  
Author(s):  
Mustapha Carab Ahmed ◽  
Ramon Crehuet ◽  
Kresten Lindorff-Larsen
Keyword(s):  
Hydrodynamic Radius ◽  
Intrinsically Disordered Proteins ◽  
Intrinsically Disordered Protein ◽  
Disordered Proteins ◽  
Radius Of Gyration ◽  
Conformational Ensemble ◽  
Conformational Ensembles ◽  
Intrinsically Disordered ◽  
Disordered Protein ◽  
Nmr Diffusion

AbstractThe level of compaction of an intrinsically disordered protein may affect both its physical and biological properties, and can be probed via different types of biophysical experiments. Small-angle X-ray scattering (SAXS) probe the radius of gyration (Rg) whereas pulsed-field-gradient nuclear magnetic resonance (NMR) diffusion, fluorescence correlation spectroscopy and dynamic light scattering experiments can be used to determine the hydrodynamic radius (Rh). Here we show how to calculate Rg and Rh from a computationally-generated conformational ensemble of an intrinsically disordered protein. We further describe how to use a Bayesian/Maximum Entropy procedure to integrate data from SAXS and NMR diffusion experiments, so as to derive conformational ensembles in agreement with those experiments.

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