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 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.

Local order and long range correlations in imidazolium halide ionic liquids: a combined molecular dynamics and XAS study

2015 ◽  
Vol 17 (25) ◽  
pp. 16443-16453 ◽  
Author(s):  
Valentina Migliorati ◽  
Alessandra Serva ◽  
Giuliana Aquilanti ◽  
Sakura Pascarelli ◽  
Paola D'Angelo
Keyword(s):  
Molecular Dynamics ◽  
Ionic Liquids ◽  
Molecular Dynamics Simulations ◽  
Long Range ◽  
Exafs Spectroscopy ◽  
Local Order ◽  
Long Range Correlations ◽  
Long Range Interactions ◽  
Dynamics Simulations

EXAFS spectroscopy and molecular dynamics simulations have been combined to unveil the effect of the cation and anion nature on the local order and long range interactions of imidazolium halide ionic liquids.

Mapping Long-Range Interactions in α-Synuclein using Spin-Label NMR and Ensemble Molecular Dynamics Simulations

2005 ◽  
Vol 127 (2) ◽  
pp. 476-477 ◽  
Author(s):  
Matthew M. Dedmon ◽  
Kresten Lindorff-Larsen ◽  
John Christodoulou ◽  
Michele Vendruscolo ◽  
Christopher M. Dobson
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Long Range ◽  
Spin Label ◽  
Long Range Interactions ◽  
Dynamics Simulations

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 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 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.

scholarly journals Molecular dynamics simulations of charged and neutral lipid bilayers: treatment of electrostatic interactions.

2003 ◽  
Vol 50 (3) ◽  
pp. 789-798 ◽  
Author(s):  
Tomasz Róg ◽  
Krzysztof Murzyn ◽  
Marta Pasenkiewicz-Gierula
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Lipid Bilayers ◽  
Long Range ◽  
Electrostatic Interactions ◽  
Md Simulations ◽  
Computational Method ◽  
Simulation Protocol ◽  
Speed Up ◽  
Dynamics Simulations

Molecular dynamics (MD) simulations complement experimental methods in studies of the structure and dynamics of lipid bilayers. The choice of algorithms employed in this computational method represents a trade-off between the accuracy and real calculation time. The largest portion of the simulation time is devoted to calculation of long-range electrostatic interactions. To speed-up evaluation of these interactions, various approximations have been used. The most common ones are the truncation of long-range interactions with the use of cut-offs, and the particle-mesh Ewald (PME) method. In this study, several multi-nanosecond cut-off and PME simulations were performed to establish the influence of the simulation protocol on the bilayer properties. Two bilayers were used. One consisted of neutral phosphatidylcholine molecules. The other was a mixed lipid bilayer consisting of neutral phosphatidylethanolamine and negatively charged phosphatidylglycerol molecules. The study shows that the cut-off simulation of a bilayer containing charge molecules generates artefacts; in particular the mobility and order of the charged molecules are vastly different from those determined experimentally. In the PME simulation, the bilayer properties are in general agreement with experimental data. The cut-off simulation of bilayers containing only uncharged molecules does not generate artefacts, nevertheless, the PME simulation gives generally better agreement with experimental data.

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