scholarly journals Distance-based metrics for comparing conformational ensembles of intrinsically disordered proteins

2020 ◽  
Author(s):  
Tamas Lazar ◽  
Mainak Guharoy ◽  
Wim Vranken ◽  
Sarah Rauscher ◽  
Shoshana J. Wodak ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Intrinsically Disordered Proteins ◽  
Statistical Significance ◽  
Protein Structures ◽  
Disordered Proteins ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Conformational Ensembles ◽  
Intrinsically Disordered

AbstractIntrinsically disordered proteins (IDPs) are proteins whose native functional states represent ensembles of highly diverse conformations. Such ensembles are a challenge for quantitative structure comparisons as their conformational diversity precludes optimal superimposition of the atomic coordinates, necessary for deriving common similarity measures such as the root-mean-square deviation (RMSD) of these coordinates. Here we introduce superimposition-free metrics, which are based on computing matrices of Cα-Cα distance distributions within ensembles and comparing these matrices between ensembles. Differences between two matrices yield information on the similarity between specific regions of the polypeptide, whereas the global structural similarity is captured by the ens_dRMS, defined as the root-mean-square difference between the medians of the Cα-Cαdistance distributions of two ensembles. Together, our metrics enable rigorous investigations of structure-function relationships in conformational ensembles of IDPs derived using experimental restraints or by molecular simulations, and for proteins containing both structured and disordered regions.Statement of SignificanceImportant biological insight is obtained from comparing the high-resolution structures of proteins. Such comparisons commonly involve superimposing two protein structures and computing the residual root-mean-square deviation of the atomic positions. This approach cannot be applied to intrinsically disordered proteins (IDPs) because IDPs do not adopt well-defined 3D structures, rather, their native functional state is defined by ensembles of heterogeneous conformations that cannot be meaningfully superimposed. We report new measures that quantify the local and global similarity between different conformational ensembles by evaluating differences between the distributions of residue-residue distances and their statistical significance. Applying these measures to IDP ensembles and to a protein containing both structured and intrinsically disordered domains provides deeper insights into how structural features relate to function.

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 Exploring Curated Conformational Ensembles of Intrinsically Disordered Proteins in the Protein Ensemble Database

2021 ◽  
Vol 1 (7) ◽  
Author(s):  
Federica Quaglia ◽  
Tamas Lazar ◽  
András Hatos ◽  
Peter Tompa ◽  
Damiano Piovesan ◽  
...  
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Conformational Ensembles ◽  
Intrinsically Disordered

scholarly journals GNINA 1.0: molecular docking with deep learning

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew T. McNutt ◽  
Paul Francoeur ◽  
Rishal Aggarwal ◽  
Tomohide Masuda ◽  
Rocco Meli ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Computational Cost ◽  
Scoring Function ◽  
Binding Pocket ◽  
Protein Docking ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Autodock Vina

AbstractMolecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline as they determine the fitness of sampled poses. Here we describe and evaluate the 1.0 release of the Gnina docking software, which utilizes an ensemble of convolutional neural networks (CNNs) as a scoring function. We also explore an array of parameter values for Gnina 1.0 to optimize docking performance and computational cost. Docking performance, as evaluated by the percentage of targets where the top pose is better than 2Å root mean square deviation (Top1), is compared to AutoDock Vina scoring when utilizing explicitly defined binding pockets or whole protein docking. Gnina, utilizing a CNN scoring function to rescore the output poses, outperforms AutoDock Vina scoring on redocking and cross-docking tasks when the binding pocket is defined (Top1 increases from 58% to 73% and from 27% to 37%, respectively) and when the whole protein defines the binding pocket (Top1 increases from 31% to 38% and from 12% to 16%, respectively). The derived ensemble of CNNs generalizes to unseen proteins and ligands and produces scores that correlate well with the root mean square deviation to the known binding pose. We provide the 1.0 version of Gnina under an open source license for use as a molecular docking tool at https://github.com/gnina/gnina.

scholarly journals Co-Evolution of Intrinsically Disordered Proteins with Folded Partners Witnessed by Evolutionary Couplings

2018 ◽  
Vol 19 (11) ◽  
pp. 3315 ◽  
Author(s):  
Rita Pancsa ◽  
Fruzsina Zsolyomi ◽  
Peter Tompa
Keyword(s):  
Large Scale ◽  
Intrinsically Disordered Proteins ◽  
Protein Structures ◽  
Disordered Proteins ◽  
Cellular Interaction ◽  
Structural Constraints ◽  
Protein Residues ◽  
Intrinsically Disordered ◽  
Evolutionary Changes ◽  
Folded Proteins

Although improved strategies for the detection and analysis of evolutionary couplings (ECs) between protein residues already enable the prediction of protein structures and interactions, they are mostly restricted to conserved and well-folded proteins. Whereas intrinsically disordered proteins (IDPs) are central to cellular interaction networks, due to the lack of strict structural constraints, they undergo faster evolutionary changes than folded domains. This makes the reliable identification and alignment of IDP homologs difficult, which led to IDPs being omitted in most large-scale residue co-variation analyses. By preforming a dedicated analysis of phylogenetically widespread bacterial IDP–partner interactions, here we demonstrate that partner binding imposes constraints on IDP sequences that manifest in detectable interprotein ECs. These ECs were not detected for interactions mediated by short motifs, rather for those with larger IDP–partner interfaces. Most identified coupled residue pairs reside close (<10 Å) to each other on the interface, with a third of them forming multiple direct atomic contacts. EC-carrying interfaces of IDPs are enriched in negatively charged residues, and the EC residues of both IDPs and partners preferentially reside in helices. Our analysis brings hope that IDP–partner interactions difficult to study could soon be successfully dissected through residue co-variation analysis.

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 Nanopores to Interrogate the Conformational Ensembles of Intrinsically Disordered Proteins on a Single-Molecule Level

2020 ◽  
Vol 118 (3) ◽  
pp. 214a
Author(s):  
Saurabh Awasthi ◽  
Jared Houghtaling ◽  
Cuifeng Ying ◽  
Aziz Fennouri ◽  
Ivan Shorubalko ◽  
...  
Keyword(s):  
Single Molecule ◽  
Intrinsically Disordered Proteins ◽  
Disordered Proteins ◽  
Single Molecule Level ◽  
Conformational Ensembles ◽  
Intrinsically Disordered

Fast collocation for Moho estimation from GOCE gravity data: the Iran case study

2020 ◽  
Vol 221 (1) ◽  
pp. 651-664
Author(s):  
H Heydarizadeh Shali ◽  
D Sampietro ◽  
A Safari ◽  
M Capponi ◽  
A Bahroudi
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Seismic Data ◽  
Active Faults ◽  
Earth’S Crust ◽  
Arabian Plate ◽  
Moho Depth ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Earth's Crust

SUMMARY The study of the discontinuity between crust and mantle beneath Iran is still an open issue in the geophysical community due to its various tectonic features created by the collision between the Iranian and Arabian Plate. For instance in regions such as Zagros, Alborz or Makran, despite the number of studies performed, both by exploiting gravity or seismic data, the depth of the Moho and also interior structure is still highly uncertain. This is due to the complexity of the crust and to the presence of large short wavelength signals in the Moho depth. GOCE observations are capable and useful products to describe the Earth’s crust structure either at the regional or global scale. Furthermore, it is plausible to retrieve important information regarding the structure of the Earth’s crust by combining the GOCE observations with seismic data and considering additional information. In the current study, we used as observation a grid of second radial derivative of the anomalous gravitational potential computed at an altitude of 221 km by means of the space-wise approach, to study the depth of the Moho. The observations have been reduced for the gravitational effects of topography, bathymetry and sediments. The residual gravity has been inverted accordingly to a simple two-layer model. In particular, this guarantees the uniqueness of the solution of the inverse problem which has been regularized by means of a collocation approach in the frequency domain. Although results of this study show a general good agreement with seismically derived depths with a root mean square deviation of 6 km, there are some discrepancies under the Alborz zone and also Oman sea with a root mean square deviation up 10 km for the former and an average difference of 3 km for the latter. Further comparisons with the natural feature of the study area, for instance, active faults, show that the resulting Moho features can be directly associated with geophysical and tectonic blocks.

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