scholarly journals Coarse-graining molecular dynamics: stochastic models with non-Gaussian force distributions

2019 ◽  
Vol 80 (1-2) ◽  
pp. 457-479 ◽  
Author(s):  
Radek Erban
Keyword(s):  
Molecular Dynamics ◽  
Linear Models ◽  
Coarse Graining ◽  
Md Simulations ◽  
Coarse Grained ◽  
Spatial And Temporal Scales ◽  
Coarse Grained Model ◽  
Non Gaussian ◽  
Low Dimensional ◽  
Cellular Behaviour

Abstract Incorporating atomistic and molecular information into models of cellular behaviour is challenging because of a vast separation of spatial and temporal scales between processes happening at the atomic and cellular levels. Multiscale or multi-resolution methodologies address this difficulty by using molecular dynamics (MD) and coarse-grained models in different parts of the cell. Their applicability depends on the accuracy and properties of the coarse-grained model which approximates the detailed MD description. A family of stochastic coarse-grained (SCG) models, written as relatively low-dimensional systems of nonlinear stochastic differential equations, is presented. The nonlinear SCG model incorporates the non-Gaussian force distribution which is observed in MD simulations and which cannot be described by linear models. It is shown that the nonlinearities can be chosen in such a way that they do not complicate parametrization of the SCG description by detailed MD simulations. The solution of the SCG model is found in terms of gamma functions.

scholarly journals Coupling all-atom molecular dynamics simulations of ions in water with Brownian dynamics

2016 ◽  
Vol 472 (2186) ◽  
pp. 20150556 ◽  
Author(s):  
Radek Erban
Keyword(s):  
Molecular Dynamics ◽  
Differential Equations ◽  
Aqueous Solutions ◽  
Molecular Dynamics Simulations ◽  
Brownian Dynamics ◽  
Md Simulations ◽  
Coarse Grained ◽  
Computational Domain ◽  
Coarse Grained Model ◽  
Dynamics Simulations

Molecular dynamics (MD) simulations of ions (K + , Na + , Ca 2+ and Cl − ) in aqueous solutions are investigated. Water is described using the SPC/E model. A stochastic coarse-grained description for ion behaviour is presented and parametrized using MD simulations. It is given as a system of coupled stochastic and ordinary differential equations, describing the ion position, velocity and acceleration. The stochastic coarse-grained model provides an intermediate description between all-atom MD simulations and Brownian dynamics (BD) models. It is used to develop a multiscale method which uses all-atom MD simulations in parts of the computational domain and (less detailed) BD simulations in the remainder of the domain.

scholarly journals Coarse-graining auto-encoders for molecular dynamics

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Wujie Wang ◽  
Rafael Gómez-Bombarelli
Keyword(s):  
Molecular Dynamics ◽  
Coarse Graining ◽  
Computational Design ◽  
Model Systems ◽  
Coarse Grained ◽  
Modeling Framework ◽  
Predictive Tool ◽  
Reduced Representation ◽  
Spatial And Temporal Scales ◽  
Dynamics Simulations

AbstractMolecular dynamics simulations provide theoretical insight into the microscopic behavior of condensed-phase materials and, as a predictive tool, enable computational design of new compounds. However, because of the large spatial and temporal scales of thermodynamic and kinetic phenomena in materials, atomistic simulations are often computationally infeasible. Coarse-graining methods allow larger systems to be simulated by reducing their dimensionality, propagating longer timesteps, and averaging out fast motions. Coarse-graining involves two coupled learning problems: defining the mapping from an all-atom representation to a reduced representation, and parameterizing a Hamiltonian over coarse-grained coordinates. We propose a generative modeling framework based on variational auto-encoders to unify the tasks of learning discrete coarse-grained variables, decoding back to atomistic detail, and parameterizing coarse-grained force fields. The framework is tested on a number of model systems including single molecules and bulk-phase periodic simulations.

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 Molecular Dynamics Study of Ganglioside GM3/DPPC Membrane by Using Coarse-Grained Model

2016 ◽  
Vol 110 (3) ◽  
pp. 323a
Author(s):  
Kento Inoue ◽  
Eiji Ymamoto ◽  
Daisuke Takaiwa ◽  
Kenji Yasuoka ◽  
Masuhiro Mikami
Keyword(s):  
Molecular Dynamics ◽  
Coarse Grained ◽  
Ganglioside Gm3 ◽  
Coarse Grained Model

scholarly journals Molecular Dynamics Scoring of Protein–Peptide Models Derived from Coarse-Grained Docking

Molecules ◽  
2021 ◽  
Vol 26 (11) ◽  
pp. 3293
Author(s):  
Mateusz Zalewski ◽  
Sebastian Kmiecik ◽  
Michał Koliński
Keyword(s):  
Molecular Dynamics ◽  
Geometry Optimization ◽  
Computational Prediction ◽  
Md Simulations ◽  
Coarse Grained ◽  
Ligand Interaction ◽  
Vast Number ◽  
Docking Simulations ◽  
Peptide Models ◽  
Peptide Complexes

One of the major challenges in the computational prediction of protein–peptide complexes is the scoring of predicted models. Usually, it is very difficult to find the most accurate solutions out of the vast number of sometimes very different and potentially plausible predictions. In this work, we tested the protocol for Molecular Dynamics (MD)-based scoring of protein–peptide complex models obtained from coarse-grained (CG) docking simulations. In the first step of the scoring procedure, all models generated by CABS-dock were reconstructed starting from their original C-alpha trace representations to all-atom (AA) structures. The second step included geometry optimization of the reconstructed complexes followed by model scoring based on receptor–ligand interaction energy estimated from short MD simulations in explicit water. We used two well-known AA MD force fields, CHARMM and AMBER, and a CG MARTINI force field. Scoring results for 66 different protein–peptide complexes show that the proposed MD-based scoring approach can be used to identify protein–peptide models of high accuracy. The results also indicate that the scoring accuracy may be significantly affected by the quality of the reconstructed protein receptor structures.

THE SIMULATION OF POLYSTYRENE/NANOPARTICLES COMPOSITE MICROSPHERES USING DISSIPATIVE PARTICLE DYNAMICS

2013 ◽  
Vol 12 (02) ◽  
pp. 1250111 ◽  
Author(s):  
HAILONG XU ◽  
QIUYU ZHANG ◽  
HEPENG ZHANG ◽  
BAOLIANG ZHANG ◽  
CHANGJIE YIN
Keyword(s):  
Dissipative Particle Dynamics ◽  
Sodium Dodecyl ◽  
Coarse Graining ◽  
Particle Dynamics ◽  
Coarse Grained ◽  
Polystyrene Nanoparticles ◽  
Coarse Grained Model ◽  
Composite Microspheres ◽  
Polystyrene Matrix ◽  
Materials Studio

Dissipative particle dynamics (DPD) was initially used to simulate the polystyrene/nanoparticle composite microspheres (PNCM) in this paper. The coarse graining model of PNCM was established. And the DPD parameterization of the model was represented in detail. The DPD repulsion parameters were calculated from the cohesive energy density which could be calculated by amorphous modules in Materials Studio. The equilibrium configuration of the simulated PNCM shows that the nanoparticles were actually "modified" with oleic acid and the modified nanoparticles were embedded in the bulk of polystyrene. As sodium dodecyl sulfate (SDS) was located in the interface between water and polystyrene, the hydrophilic head of SDS stretched into water while the hydrophobic tailed into polystyrene. All simulated phenomena were consistent with the experimental results in preparation of polystyrene/nanoparticles composite microspheres. The effect of surface modification of nanoparticles on its dispersion in polystyrene matrix was also studied by adjusting the interaction parameters between the OA and NP beads. The final results indicated that the nanoparticles removed from the core of composite microsphere to the surface with increase of a OA-NP . All the simulated results demonstrated that our coarse–grained model was reasonable.

scholarly journals Antimicrobial action of the cationic peptide, chrysophsin-3: a coarse-grained molecular dynamics study

Soft Matter ◽  
2018 ◽  
Vol 14 (15) ◽  
pp. 2796-2807 ◽  
Author(s):  
Andrea Catte ◽  
Mark R. Wilson ◽  
Martin Walker ◽  
Vasily S. Oganesyan
Keyword(s):  
Molecular Dynamics ◽  
Large Scale ◽  
Md Simulations ◽  
Antimicrobial Action ◽  
Coarse Grained ◽  
Cationic Peptide ◽  
Coarse Grained Molecular Dynamics

Antimicrobial action of a cationic peptide is modelled by large scale MD simulations.

scholarly journals Computational Study of C-X-C Chemokine Receptor (CXCR)3 Binding with Its Natural Agonists Chemokine (C-X-C Motif) Ligand (CXCL)9, 10 and 11 and with Synthetic Antagonists: Insights of Receptor Activation towards Drug Design for Vitiligo

Molecules ◽  
2020 ◽  
Vol 25 (19) ◽  
pp. 4413
Author(s):  
Giovanny Aguilera-Durán ◽  
Antonio Romo-Mancillas
Keyword(s):  
Molecular Dynamics ◽  
Computational Study ◽  
Md Simulations ◽  
Receptor Activation ◽  
Activation Mechanism ◽  
Coarse Grained ◽  
Dimensional Structure ◽  
Cytotoxic Lymphocytes ◽  
Ligand Interaction ◽  
Α Subunit

Vitiligo is a hypopigmentary skin pathology resulting from the death of melanocytes due to the activity of CD8+ cytotoxic lymphocytes and overexpression of chemokines. These include CXCL9, CXCL10, and CXCL11 and its receptor CXCR3, both in peripheral cells of the immune system and in the skin of patients diagnosed with vitiligo. The three-dimensional structure of CXCR3 and CXCL9 has not been reported experimentally; thus, homology modeling and molecular dynamics could be useful for the study of this chemotaxis-promoter axis. In this work, a homology model of CXCR3 and CXCL9 and the structure of the CXCR3/Gαi/0βγ complex with post-translational modifications of CXCR3 are reported for the study of the interaction of chemokines with CXCR3 through all-atom (AA-MD) and coarse-grained molecular dynamics (CG-MD) simulations. AA-MD and CG-MD simulations showed the first activation step of the CXCR3 receptor with all chemokines and the second activation step in the CXCR3-CXCL10 complex through a decrease in the distance between the chemokine and the transmembrane region of CXCR3 and the separation of the βγ complex from the α subunit in the G-protein. Additionally, a general protein–ligand interaction model was calculated, based on known antagonists binding to CXCR3. These results contribute to understanding the activation mechanism of CXCR3 and the design of new molecules that inhibit chemokine binding or antagonize the receptor, provoking a decrease of chemotaxis caused by the CXCR3/chemokines axis.

A coarse-grained model of dimethyl sulfoxide for molecular dynamics simulations with lipid membranes

2020 ◽  
Vol 153 (3) ◽  
pp. 035104
Author(s):  
Shobhna ◽  
Monika Kumari ◽  
Hemant K. Kashyap
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulations ◽  
Dimethyl Sulfoxide ◽  
Lipid Membranes ◽  
Coarse Grained ◽  
Coarse Grained Model ◽  
Dynamics Simulations
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