scholarly journals Conformational and functional characterization of artificially conjugated non-canonical ubiquitin dimers

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Tobias Schneider ◽  
Andrej Berg ◽  
Zeynel Ulusoy ◽  
Martin Gamerdinger ◽  
Christine Peter ◽  
...  
Keyword(s):  
Experimental Data ◽  
Functional Characterization ◽  
Isotopic Labeling ◽  
Md Simulations ◽  
Conformational Space ◽  
Coarse Grained ◽  
Covalent Attachment ◽  
Binding Studies ◽  
Polyubiquitin Chains ◽  
Polypeptide Chains

AbstractUbiquitylation is an eminent posttranslational modification referring to the covalent attachment of single ubiquitin molecules or polyubiquitin chains to a target protein dictating the fate of such labeled polypeptide chains. Here, we have biochemically produced artificially Lys11-, and Lys27-, and Lys63-linked ubiquitin dimers based on click-chemistry generating milligram quantities in high purity. We show that the artificial linkage used for the conjugation of two ubiquitin moieties represents a fully reliable surrogate of the natural isopeptide bond by acquiring highly resolved nuclear magnetic resonance (NMR) spectroscopic data including ligand binding studies. Extensive coarse grained and atomistic molecular dynamics (MD) simulations allow to extract structures representing the ensemble of domain-domain conformations used to verify the experimental data. Advantageously, this methodology does not require individual isotopic labeling of both ubiquitin moieties as NMR data have been acquired on the isotopically labeled proximal moiety and complementary MD simulations have been used to fully interpret the experimental data in terms of domain-domain conformation. This combined approach intertwining NMR spectroscopy with MD simulations makes it possible to describe the conformational space non-canonically Lys11-, and Lys27-linked ubiquitin dimers occupy in a solution averaged ensemble by taking atomically resolved information representing all residues in ubiquitin dimers into account.

scholarly journals Dynamical Behavior and Conformational Selection Mechanism of the Intrinsically Disordered Sic1 Kinase-Inhibitor Domain

Life ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 110 ◽  
Author(s):  
Davide Sala ◽  
Ugo Cosentino ◽  
Anna Ranaudo ◽  
Claudio Greco ◽  
Giorgio Moro
Keyword(s):  
Kinase Inhibitor ◽  
Dynamical Behavior ◽  
Md Simulations ◽  
Molecular Shape ◽  
Conformational Space ◽  
Coarse Grained ◽  
Conformational Ensemble ◽  
Selection Mechanism ◽  
Conformational Selection ◽  
Intrinsically Disordered

Intrinsically Disordered Peptides and Proteins (IDPs) in solution can span a broad range of conformations that often are hard to characterize by both experimental and computational methods. However, obtaining a significant representation of the conformational space is important to understand mechanisms underlying protein functions such as partner recognition. In this work, we investigated the behavior of the Sic1 Kinase-Inhibitor Domain (KID) in solution by Molecular Dynamics (MD) simulations. Our results point out that application of common descriptors of molecular shape such as Solvent Accessible Surface (SAS) area can lead to misleading outcomes. Instead, more appropriate molecular descriptors can be used to define 3D structures. In particular, we exploited Weighted Holistic Invariant Molecular (WHIM) descriptors to get a coarse-grained but accurate definition of the variegated Sic1 KID conformational ensemble. We found that Sic1 is able to form a variable amount of folded structures even in absence of partners. Among them, there were some conformations very close to the structure that Sic1 is supposed to assume in the binding with its physiological complexes. Therefore, our results support the hypothesis that this protein relies on the conformational selection mechanism to recognize the correct molecular partners.

UNRES-Dock—protein–protein and peptide–protein docking by coarse-grained replica-exchange MD simulations

2020 ◽  
Author(s):  
Paweł Krupa ◽  
Agnieszka S Karczyńska ◽  
Magdalena A Mozolewska ◽  
Adam Liwo ◽  
Cezary Czaplewski
Keyword(s):  
Protein Complexes ◽  
Md Simulations ◽  
Protein Docking ◽  
Conformational Space ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Replica Exchange ◽  
Variable Degree ◽  
Single Chain ◽  
Simulation Speed

Abstract Motivation The majority of the proteins in living organisms occur as homo- or hetero-multimeric structures. Although there are many tools to predict the structures of single-chain proteins or protein complexes with small ligands, peptide–protein and protein–protein docking is more challenging. In this work, we utilized multiplexed replica-exchange molecular dynamics (MREMD) simulations with the physics-based heavily coarse-grained UNRES model, which provides more than a 1000-fold simulation speed-up compared with all-atom approaches to predict structures of protein complexes. Results We present a new protein–protein and peptide–protein docking functionality of the UNRES package, which includes a variable degree of conformational flexibility. UNRES-Dock protocol was tested on a set of 55 complexes with size from 43 to 587 amino-acid residues, showing that structures of the complexes can be predicted with good quality, if the sampling of the conformational space is sufficient, especially for flexible peptide–protein systems. The developed automatized protocol has been implemented in the standalone UNRES package and in the UNRES server. Availability and implementation UNRES server: http://unres-server.chem.ug.edu.pl; UNRES package and data used in testing of UNRES-Dock: http://unres.pl. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Structural Investigation of MscL Gating Using Experimental Data and Coarse Grained MD Simulations

2012 ◽  
Vol 8 (9) ◽  
pp. e1002683 ◽  
Author(s):  
Evelyne Deplazes ◽  
Martti Louhivuori ◽  
Dylan Jayatilaka ◽  
Siewert J. Marrink ◽  
Ben Corry
Keyword(s):  
Experimental Data ◽  
Structural Investigation ◽  
Md Simulations ◽  
Coarse Grained

scholarly journals Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Stephan Thaler ◽  
Julija Zavadlav
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Thermodynamic Perturbation Theory ◽  
Top Down ◽  
Bottom Up ◽  
Coarse Grained Model ◽  
Gradient Computation

AbstractIn molecular dynamics (MD), neural network (NN) potentials trained bottom-up on quantum mechanical data have seen tremendous success recently. Top-down approaches that learn NN potentials directly from experimental data have received less attention, typically facing numerical and computational challenges when backpropagating through MD simulations. We present the Differentiable Trajectory Reweighting (DiffTRe) method, which bypasses differentiation through the MD simulation for time-independent observables. Leveraging thermodynamic perturbation theory, we avoid exploding gradients and achieve around 2 orders of magnitude speed-up in gradient computation for top-down learning. We show effectiveness of DiffTRe in learning NN potentials for an atomistic model of diamond and a coarse-grained model of water based on diverse experimental observables including thermodynamic, structural and mechanical properties. Importantly, DiffTRe also generalizes bottom-up structural coarse-graining methods such as iterative Boltzmann inversion to arbitrary potentials. The presented method constitutes an important milestone towards enriching NN potentials with experimental data, particularly when accurate bottom-up data is unavailable.

scholarly journals A multiscale computational study of the conformation of the full-length intrinsically disordered protein MeCP2

2021 ◽  
Author(s):  
Cecilia Chavez-Garcia ◽  
Jerome Henin ◽  
Mikko Karttunen
Keyword(s):  
Experimental Data ◽  
Computational Study ◽  
Intrinsically Disordered Protein ◽  
Full Length ◽  
Conformational Space ◽  
Coarse Grained ◽  
Conformational Ensemble ◽  
Intrinsically Disordered ◽  
Disordered Protein ◽  
Coarse Grained Simulations

The malfunction of the Methyl CpG binding protein 2 (MeCP2) is associated to the Rett syndrome, one of the most common causes of cognitive impairment in females. MeCP2 is an intrinsically disordered protein (IDP), making its experimental characterization a challenge. There is currently no structure available for the full-length MeCP2 in any of the databases, and only the structure of its MBD domain has been solved. We used this structure to build a full-length model of MeCP2 by completing the rest of the protein via ab initio modelling. Using a combination of all-atom and coarse-grained simulations, we characterized its structure and dynamics as well as the conformational space sampled by the ID and TRD domains in the absence of the rest of the protein. The present work is the first computational study of the full-length protein. Two main conformations were sampled in the coarse-grained simulations: a globular structure similar to the one observed in the all-atom force field and a two-globule conformation. Our all-atom model is in good agreement with the available experimental data, predicting amino acid W104 to be buried, amino acids R111 and R133 to be solvent accessible, and having 4.1% of α-helix content, compared to the 4% found experimentally. Finally, we compared the model predicted by AlphaFold to our Modeller model. The model was not stable in water and underwent further folding. Together, these simulations provide a detailed (if perhaps incomplete) conformational ensemble of the full-length MeCP2, which is compatible with experimental data and can be the basis of further studies, e.g., on mutants of the protein or its interactions with its biological partners.

scholarly journals On the Use of the Discrete Constant pH Molecular Dynamics to Describe the Conformational Space of Peptides

Polymers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 99
Author(s):  
Cristian Privat ◽  
Sergio Madurga ◽  
Francesc Mas ◽  
Jaime Rubio-Martínez
Keyword(s):  
Molecular Dynamics ◽  
Amino Acids ◽  
Md Simulations ◽  
Point Of View ◽  
Conformational Space ◽  
Conformational Sampling ◽  
Protonation State ◽  
Constant Ph ◽  
Biochemical Systems ◽  
Constant Ph Molecular Dynamics

Solvent pH is an important property that defines the protonation state of the amino acids and, therefore, modulates the interactions and the conformational space of the biochemical systems. Generally, this thermodynamic variable is poorly considered in Molecular Dynamics (MD) simulations. Fortunately, this lack has been overcome by means of the Constant pH Molecular Dynamics (CPHMD) methods in the recent decades. Several studies have reported promising results from these approaches that include pH in simulations but focus on the prediction of the effective pKa of the amino acids. In this work, we want to shed some light on the CPHMD method and its implementation in the AMBER suitcase from a conformational point of view. To achieve this goal, we performed CPHMD and conventional MD (CMD) simulations of six protonatable amino acids in a blocked tripeptide structure to compare the conformational sampling and energy distributions of both methods. The results reveal strengths and weaknesses of the CPHMD method in the implementation of AMBER18 version. The change of the protonation state according to the chemical environment is presumably an improvement in the accuracy of the simulations. However, the simulations of the deprotonated forms are not consistent, which is related to an inaccurate assignment of the partial charges of the backbone atoms in the CPHMD residues. Therefore, we recommend the CPHMD methods of AMBER program but pointing out the need to compare structural properties with experimental data to bring reliability to the conformational sampling of the simulations.

scholarly journals Conformational Ensembles by NMR and MD Simulations in Model Heptapeptides with Select Tri-Peptide Motifs

2021 ◽  
Vol 22 (3) ◽  
pp. 1364
Author(s):  
V. V. Krishnan ◽  
Timothy Bentley ◽  
Alina Xiong ◽  
Kalyani Maitra
Keyword(s):  
Principal Component ◽  
Md Simulations ◽  
Conformational Space ◽  
Random Coil ◽  
Radius Of Gyration ◽  
Small Peptides ◽  
Conformational Ensembles ◽  
Solution State ◽  
Peptide Motifs ◽  
Explicit Solvent

Both nuclear magnetic resonance (NMR) and molecular dynamics (MD) simulations are routinely used in understanding the conformational space sampled by peptides in the solution state. To investigate the role of single-residue change in the ensemble of conformations sampled by a set of heptapeptides, AEVXEVG with X = L, F, A, or G, comprehensive NMR, and MD simulations were performed. The rationale for selecting the particular model peptides is based on the high variability in the occurrence of tri-peptide E*L between the transmembrane β-barrel (TMB) than in globular proteins. The ensemble of conformations sampled by E*L was compared between the three sets of ensembles derived from NMR spectroscopy, MD simulations with explicit solvent, and the random coil conformations. In addition to the estimation of global determinants such as the radius of gyration of a large sample of structures, the ensembles were analyzed using principal component analysis (PCA). In general, the results suggest that the -EVL- peptide indeed adopts a conformational preference that is distinctly different not only from a random distribution but also from other peptides studied here. The relatively straightforward approach presented herein could help understand the conformational preferences of small peptides in the solution state.

scholarly journals High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling

2021 ◽  
Author(s):  
Théo Jaffrelot Inizan ◽  
Frédéric Célerse ◽  
Olivier Adjoua ◽  
Dina El Ahdab ◽  
Luc-Henri Jolly ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
High Resolution ◽  
Adaptive Sampling ◽  
Force Fields ◽  
Sampling Strategy ◽  
Md Simulations ◽  
Conformational Space ◽  
Many Body ◽  
Polarizable Force Fields ◽  
Main Protease

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs).

scholarly journals Molecular dynamics simulations and CD spectroscopy reveal hydration-induced unfolding of the intrinsically disordered LEA proteins COR15A and COR15B from Arabidopsis thaliana

2016 ◽  
Vol 18 (37) ◽  
pp. 25806-25816 ◽  
Author(s):  
Carlos Navarro-Retamal ◽  
Anne Bremer ◽  
Jans Alzate-Morales ◽  
Julio Caballero ◽  
Dirk K. Hincha ◽  
...  
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Arabidopsis Thaliana ◽  
Molecular Dynamics Simulations ◽  
Md Simulations ◽  
Cd Spectroscopy ◽  
Lea Proteins ◽  
Intrinsically Disordered ◽  
Dynamics Simulations ◽  
Crowded Environment

Unfolding of intrinsically unstructured full-length LEA proteins in a differentially crowded environment can be modeled by 30 ns MD simulations in accordance with experimental data.

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