scholarly journals Desmosome architecture derived from molecular dynamics simulations and cryo-electron tomography

2020 ◽  
Vol 117 (44) ◽  
pp. 27132-27140
Author(s):  
Mateusz Sikora ◽  
Utz H. Ermel ◽  
Anna Seybold ◽  
Michael Kunz ◽  
Giulia Calloni ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Md Simulation ◽  
Electron Tomography ◽  
Md Simulations ◽  
Cell Junctions ◽  
Biophysical Properties ◽  
In Silico Screening ◽  
Desmosomal Cadherins ◽  
Cryo Electron Tomography ◽  
Dynamics Simulations

Desmosomes are cell–cell junctions that link tissue cells experiencing intense mechanical stress. Although the structure of the desmosomal cadherins is known, the desmosome architecture—which is essential for mediating numerous functions—remains elusive. Here, we recorded cryo-electron tomograms (cryo-ET) in which individual cadherins can be discerned; they appear variable in shape, spacing, and tilt with respect to the membrane. The resulting sub-tomogram average reaches a resolution of ∼26 Å, limited by the inherent flexibility of desmosomes. To address this challenge typical of dynamic biological assemblies, we combine sub-tomogram averaging with atomistic molecular dynamics (MD) simulations. We generate models of possible cadherin arrangements and perform an in silico screening according to biophysical and structural properties extracted from MD simulation trajectories. We find a truss-like arrangement of cadherins that resembles the characteristic footprint seen in the electron micrograph. The resulting model of the desmosomal architecture explains their unique biophysical properties and strength.

scholarly journals Neural relational inference to learn allosteric long-range interactions in proteins from molecular dynamics simulations

2021 ◽  
Author(s):  
Jingxuan Zhu ◽  
Juexin Wang ◽  
Weiwei Han ◽  
Dong Xu
Keyword(s):  
Molecular Dynamics ◽  
Long Range ◽  
Md Simulation ◽  
Biological Process ◽  
Dynamic Networks ◽  
Md Simulations ◽  
Amino Acid Mutation ◽  
Long Range Interactions ◽  
Decoder Architecture ◽  
Dynamics Simulations

Abstract Protein allostery is a biological process facilitated by spatially long-range intra-protein communication, whereby ligand binding or amino acid mutation at a distant site affects the active site remotely. Molecular dynamics (MD) simulation provides a powerful computational approach to probe the allosteric effect. However, current MD simulations cannot reach the time scales of whole allosteric processes. The advent of deep learning made it possible to evaluate both spatially short and long-range communications for understanding allostery. For this purpose, we applied a neural relational inference (NRI) model based on a graph neural network (GNN), which adopts an encoder-decoder architecture to simultaneously infer latent interactions to probe protein allosteric processes as dynamic networks of interacting residues. From the MD trajectories, this model successfully learned the long-range interactions and pathways that can mediate the allosteric communications between the two distant sites in the Pin1, SOD1, and MEK1 systems.

scholarly journals A New Algorithm for Contact Angle Estimation in Molecular Dynamics Simulations

2015 ◽  
Author(s):  
Sumith Yd ◽  
Shalabh C. Maroo
Keyword(s):  
Molecular Dynamics ◽  
Contact Angle ◽  
Md Simulation ◽  
Spline Interpolation ◽  
Vertical Axis ◽  
Md Simulations ◽  
Computationally Efficient ◽  
B Spline ◽  
Wetting Properties ◽  
Dynamics Simulations

It is important to study contact angle of a liquid on a solid surface to understand its wetting properties, capillarity and surface interaction energy. While performing transient molecular dynamics (MD) simulations it requires calculating the time evolution of contact angle. This is a tedious effort to do manually or with image processing algorithms. In this work we propose a new algorithm to estimate contact angle from MD simulations directly and in a computationally efficient way. This algorithm segregates the droplet molecules from the vapor molecules using Mahalanobis distance (MND) technique. Then the density is smeared onto a 2D grid using 4th order B-spline interpolation function. The vapor liquid interface data is estimated from the grid using density filtering. With the interface data a circle is fitted using Landau method. The equation of this circle is solved for obtaining the contact angle. This procedure is repeated by rotating the droplet about the vertical axis. We have applied this algorithm to a number of studies (different potentials and thermostat methods) which involves the MD simulation of water.

scholarly journals Mutagenesis of DsbAss is Crucial for the Signal Recognition Particle Mechanism in Escherichia coli: Insights from Molecular Dynamics Simulations

Biomolecules ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 133 ◽  
Author(s):  
Faiza Durrani ◽  
Roquyya Gul ◽  
Muhammad Mirza ◽  
Naheed Kaderbhai ◽  
Matheus Froeyen ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Molecular Dynamics ◽  
Md Simulation ◽  
Simulation Analysis ◽  
Signal Sequence ◽  
Binding Free Energy ◽  
Signal Recognition Particle ◽  
Md Simulations ◽  
Free Energy Calculations ◽  
Dynamics Simulations

The disulfide bond signal sequence (DsbAss) protein is characterized as an important virulence factor in gram-negative bacteria. This study aimed to analyze the “alanine” alteration in the hydrophobic (H) region of DsbAss and to understand the conformational DsbAss alteration(s) inside the fifty-four homolog (Ffh)-binding groove which were revealed to be crucial for translocation of ovine growth hormone (OGH) to the periplasmic space in Escherichia coli via the secretory (Sec) pathway. An experimental design was used to explore the hydrophobicity and alteration of alanine (Ala) to isoleucine (Ile) in the tripartite structure of DsbAss. As a result, two DsbAss mutants (Ala at positions -11 and -13) with same hydrophobicity of 1.539 led to the conflicting translocation of the active OGH gene. We performed molecular dynamics (MD) simulations and molecular mechanics generalized born surface area (MM-GBSA) binding free energy calculations to examine the interaction energetic and dynamic aspects of DsbAss/signal repetition particle 54 (SRP54) binding, which has a principle role in Escherichia coli Sec pathways. Although both DsbAss mutants retained helicity, the MD simulation analysis evidenced that altering Ala-13 changed the orientation of the signal peptide in the Ffh M binding domain groove, favored more stable interaction energies (MM-GBSA ΔGtotal = −140.62 kcal mol−1), and hampered the process of OGH translocation, while Ala-11 pointed outward due to unstable conformation and less binding energy (ΔGtotal = −124.24 kcal mol−1). Here we report the dynamic behavior of change of “alanine” in the H-domain of DsbAss which affects the process of translocation of OGH, where MD simulation and MM-GBSA can be useful initial tools to investigate the virulence of bacteria.

scholarly journals Spontaneous self-assembly and structure of perfluoroalkylalkane surfactant hemimicelles by molecular dynamics simulations

2019 ◽  
Vol 116 (30) ◽  
pp. 14868-14873 ◽  
Author(s):  
Gonçalo M. C. Silva ◽  
Pedro Morgado ◽  
Pedro Lourenço ◽  
Michel Goldmann ◽  
Eduardo J. M. Filipe
Keyword(s):  
Molecular Dynamics ◽  
Self Assembly ◽  
Md Simulation ◽  
Grazing Incidence ◽  
Md Simulations ◽  
X Ray Diffraction ◽  
X Ray ◽  
Spontaneous Formation ◽  
Rational Explanation ◽  
Dynamics Simulations

Fully atomistic molecular-dynamics (MD) simulations of perfluoroalkylalkane molecules at the surface of water show the spontaneous formation of aggregates whose size and topography closely resemble the experimentally observed hemimicelles for this system. Furthermore, the grazing incidence X-ray diffraction (GIXD) pattern calculated from the simulation trajectories reproduces the experimental GIXD spectra previously obtained, fully validating the MD simulation results. The detailed analysis of the internal structure of the aggregates obtained by the MD simulations supports a definite rational explanation for the spontaneous formation, stability, size, and shape of perfluoroalkylalkane hemimicelles at the surface of water.

Molecular Dynamics Simulations and the Landauer’s Principle

2018 ◽  
Vol 25 (02) ◽  
pp. 1850006
Author(s):  
Ihab H. Naeim ◽  
J. Batle ◽  
S. Kadry ◽  
O. Tarawneh
Keyword(s):  
Molecular Dynamics ◽  
Information Theory ◽  
Molecular Dynamics Simulations ◽  
Md Simulation ◽  
Canonical Ensemble ◽  
Md Simulations ◽  
Present Contribution ◽  
Bistable Potential ◽  
Landauer’S Principle ◽  
Dynamics Simulations

Landauer’s principle is a fundamental link between thermodynamics and information theory, which implies that the erasure of information comes at an energetic price. In the present contribution we analyze to what extend the usual molecular dynamics (MD) simulation formalism can handle the Landauer’s bound kBT ln 2 in the simplest case of one particle treated classically. The erasure of one bit of information is performed by adiabatically varying the shape of a bistable potential in a full cycle. We will highlight the inadequacy of either the microcanonical or canonical ensemble treatments currently employed in MD simulations and propose potential solutions.

scholarly journals Neural relational inference to learn allosteric long-range interactions in proteins from molecular dynamics simulations

2021 ◽  
Author(s):  
Jingxuan Zhu ◽  
Juexin Wang ◽  
Weiwei Han ◽  
Dong Xu
Keyword(s):  
Molecular Dynamics ◽  
Long Range ◽  
Binding Sites ◽  
Md Simulation ◽  
Dynamic Networks ◽  
Md Simulations ◽  
Amino Acid Mutation ◽  
Long Range Interactions ◽  
Decoder Architecture ◽  
Dynamics Simulations

AbstractProtein allostery is a biological process facilitated by spatially long-range intra-protein communication, whereby ligand binding or amino acid mutation at a distant site affects the active site remotely. Molecular dynamics (MD) simulation provides a powerful computational approach to probe the allostery effect. However, current MD simulations cannot reach the time scales of whole allostery processes. The advent of deep learning made it possible to evaluate both spatially short and long-range communications for understanding allostery. For this purpose, we applied a neural relational inference (NRI) model based on a graph neural network (GNN), which adopts an encoder-decoder architecture to simultaneously infer latent interactions to probe protein allosteric processes as dynamic networks of interacting residues. From the MD trajectories, this model successfully learned the long-range interactions and pathways that can mediate the allosteric communications between the two distant binding sites in the Pin1, SOD1, and MEK1 systems.

Adsorption behavior of Cs+ ions to vermiculite demonstrated by molecular dynamics simulations

2018 ◽  
Vol 28 (01n02) ◽  
pp. 1-5
Author(s):  
Akira Takeuchi
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Md Simulation ◽  
Constant Pressure ◽  
Md Simulations ◽  
Kinetic Process ◽  
Adsorption Behavior ◽  
Simulation Results ◽  
Dynamics Simulations ◽  
Cs Ions

The present paper discusses the simulation results, performed by classical molecular dynamics (MD), for vermiculite. The kinetic process of the [Formula: see text] ions in water that are adsorbed into vermiculite [Formula: see text] was investigated with classical MD simulations utilizing Coulomb and Born–Mayer–Huggins potentials. A monoclinic vermiculite crystal with a [Formula: see text] supercell was placed into 8461 molecules of water to form a rectangular supercell of [Formula: see text]. The water was placed into contact with both sides of the [Formula: see text]–[Formula: see text] planes of the vermiculite crystal, along the [Formula: see text]-axis only. The rectangular supercells, which were prepared with the vermiculite in water with and without an additional 200 [Formula: see text] ions, were simulated. The MD conditions included a constant pressure ensemble for 1 ps at a constant step of 0.1 fs. The results revealed an increase in the distances of the [Formula: see text] layers at the interface between the vermiculite and water. This increase in the separation of the [Formula: see text] layers was suitable for the uptake of [Formula: see text] ions by the vermiculite. The accelerated MD simulation which replaced the interfacial [Formula: see text] ions with [Formula: see text] ions tended to include the [Formula: see text] ions into the vermiculite by excluding the [Formula: see text] ions.

Assessing the Antimalarial Potentials of Phytochemicals: Virtual Screening, Molecular Dynamics and In-Vitro Investigations

2019 ◽  
Vol 16 (3) ◽  
pp. 291-300
Author(s):  
Saumya K. Patel ◽  
Mohd Athar ◽  
Prakash C. Jha ◽  
Vijay M. Khedkar ◽  
Yogesh Jasrai ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Structural Integrity ◽  
Md Simulations ◽  
Tylophora Indica ◽  
Multidrug Resistance Protein 1 ◽  
Receptor Complexes ◽  
Resistance Protein ◽  
Dynamics Simulations ◽  
Stable Trajectory

Background: Combined in-silico and in-vitro approaches were adopted to investigate the antiplasmodial activity of Catharanthus roseus and Tylophora indica plant extracts as well as their isolated components (vinblastine, vincristine and tylophorine). </P><P> Methods: We employed molecular docking to prioritize phytochemicals from a library of 26 compounds against Plasmodium falciparum multidrug-resistance protein 1 (PfMDR1). Furthermore, Molecular Dynamics (MD) simulations were performed for a duration of 10 ns to estimate the dynamical structural integrity of ligand-receptor complexes. </P><P> Results: The retrieved bioactive compounds viz. tylophorine, vinblastin and vincristine were found to exhibit significant interacting behaviour; as validated by in-vitro studies on chloroquine sensitive (3D7) as well as chloroquine resistant (RKL9) strain. Moreover, they also displayed stable trajectory (RMSD, RMSF) and molecular properties with consistent interaction profile in molecular dynamics simulations. </P><P> Conclusion: We anticipate that the retrieved phytochemicals can serve as the potential hits and presented findings would be helpful for the designing of malarial therapeutics.

scholarly journals Unveiling Carbon Dioxide and Ethanol Diffusion in Carbonated Water-Ethanol Mixtures by Molecular Dynamics Simulations

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1711
Author(s):  
Mohamed Ahmed Khaireh ◽  
Marie Angot ◽  
Clara Cilindre ◽  
Gérard Liger-Belair ◽  
David A. Bonhommeau
Keyword(s):  
Carbon Dioxide ◽  
Molecular Dynamics ◽  
Diffusion Coefficients ◽  
Hydrodynamic Radius ◽  
Md Simulations ◽  
Molecular Models ◽  
Experimental Values ◽  
Carbon Dioxide Co2 ◽  
Dynamics Simulations ◽  
Apparent Disagreement

The diffusion of carbon dioxide (CO2) and ethanol (EtOH) is a fundamental transport process behind the formation and growth of CO2 bubbles in sparkling beverages and the release of organoleptic compounds at the liquid free surface. In the present study, CO2 and EtOH diffusion coefficients are computed from molecular dynamics (MD) simulations and compared with experimental values derived from the Stokes-Einstein (SE) relation on the basis of viscometry experiments and hydrodynamic radii deduced from former nuclear magnetic resonance (NMR) measurements. These diffusion coefficients steadily increase with temperature and decrease as the concentration of ethanol rises. The agreement between theory and experiment is suitable for CO2. Theoretical EtOH diffusion coefficients tend to overestimate slightly experimental values, although the agreement can be improved by changing the hydrodynamic radius used to evaluate experimental diffusion coefficients. This apparent disagreement should not rely on limitations of the MD simulations nor on the approximations made to evaluate theoretical diffusion coefficients. Improvement of the molecular models, as well as additional NMR measurements on sparkling beverages at several temperatures and ethanol concentrations, would help solve this issue.

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