scholarly journals Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories

2020 ◽  
Vol 153 (13) ◽  
pp. 134104 ◽  
Author(s):  
Marcelo C. R. Melo ◽  
Rafael C. Bernardi ◽  
Cesar de la Fuente-Nunez ◽  
Zaida Luthey-Schulten
Keyword(s):  
Molecular Dynamics ◽  
Network Analysis ◽  
High Performance ◽  
Dynamical Network ◽  
Generalized Correlation

scholarly journals Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories

2020 ◽  
Author(s):  
Marcelo C. R. Melo ◽  
Rafael C. Bernardi ◽  
Cesar de la Fuente-Nunez ◽  
Zaida Luthey-Schulten
Keyword(s):  
Network Analysis ◽  
High Performance ◽  
Molecular Complexes ◽  
Trna Synthetase ◽  
Biomolecular Systems ◽  
Dynamical Network ◽  
Cellular Processes ◽  
Molecular Features ◽  
Community Clustering ◽  
Generalized Correlation

AbstractMolecular interactions are essential for regulation of cellular processes, from the formation of multiprotein complexes, to the allosteric activation of enzymes. Identifying the essential residues and molecular features that regulate such interactions is paramount for understanding the biochemical process in question, allowing for suppression of a reaction through drug interventions, or optimization of a chemical process using bioengineered molecules. In order to identify important residues and information pathways within molecular complexes, the Dynamical Network Analysis method was developed and has since been broadly applied in the literature. However, in the dawn of exascale computing, this method is generally limited to relatively small biomolecular systems. In this work we provide an evolution of the method, application and interface. All data processing and analysis is conducted through Jupyter notebooks, providing automatic detection of important solvent and ion residues, an optimized and parallel generalized correlation implementation that is linear with respect to the number of nodes in the system, and subsequent community clustering, calculation of betweenness of contacts, and determination optimal paths. Using the popular visualization program VMD, high-quality renderings of the networks over the biomolecular structures can be produced. Our new implementation was employed to investigate three different systems, with up to 2.5 M atoms, namely the OMP-decarboxylase, the Leucyl-tRNA synthetase complexed with its cognate tRNA and adenylate, and the respiratory complex I in a membrane environment. Our enhanced and updated protocol provides the community with an intuitive and interactive interface, which can be easily applied to large macromolecular complexes.

GPU-accelerated molecular dynamics: State-of-art software performance and porting from Nvidia CUDA to AMD HIP

2021 ◽  
pp. 109434202110082
Author(s):  
Nikolay Kondratyuk ◽  
Vsevolod Nikolskiy ◽  
Daniil Pavlov ◽  
Vladimir Stegailov
Keyword(s):  
Molecular Dynamics ◽  
High Performance ◽  
Software Performance ◽  
Computing Systems ◽  
Accelerated Molecular Dynamics ◽  
Nvidia Cuda ◽  
Software And Hardware ◽  
Management Capabilities ◽  
Utilization Time ◽  
Performance Computing

Classical molecular dynamics (MD) calculations represent a significant part of the utilization time of high-performance computing systems. As usual, the efficiency of such calculations is based on an interplay of software and hardware that are nowadays moving to hybrid GPU-based technologies. Several well-developed open-source MD codes focused on GPUs differ both in their data management capabilities and in performance. In this work, we analyze the performance of LAMMPS, GROMACS and OpenMM MD packages with different GPU backends on Nvidia Volta and AMD Vega20 GPUs. We consider the efficiency of solving two identical MD models (generic for material science and biomolecular studies) using different software and hardware combinations. We describe our experience in porting the CUDA backend of LAMMPS to ROCm HIP that shows considerable benefits for AMD GPUs comparatively to the OpenCL backend.

THE ATOMIC FINITE ELEMENT METHOD AS A BRIDGE BETWEEN MOLECULAR DYNAMICS AND CONTINUUM MECHANICS

2011 ◽  
Vol 03 (01n02) ◽  
pp. 39-47 ◽  
Author(s):  
R. NEUGEBAUER ◽  
R. WERTHEIM ◽  
U. SEMMLER
Keyword(s):  
Finite Element Method ◽  
Molecular Dynamics ◽  
Finite Element ◽  
High Performance ◽  
Cutting Tools ◽  
Deposition Process ◽  
Dislocation Behavior ◽  
Crystal Plasticity Fem ◽  
The Continuum ◽  
Element Method

On cutting tools for high performance cutting (HPC) processes or for hard-to-cut materials, there is an increased importance in so-called superlattice coatings with hundreds of layers each of which is only a few nanometers in thickness. Homogeneity or average material properties based on the properties of single layers are not valid in these dimensions any more. Consequently, continuum mechanical material models cannot be used for modeling the behavior of nanolayers. Therefore, the interaction potentials between the single atoms should be considered. A new, so-called atomic finite element method (AFEM) is presented. In the AFEM the interatomic bonds are modeled as nonlinear spring elements. The AFEM is the connection between the molecular dynamics (MD) method and the crystal plasticity FEM (CPFEM). The MD simulates the atomic deposition process. The CPFEM considers the behavior of anisotropic crystals using the continuum mechanical FEM. On one side, the atomic structure data simulated by MD defines the interface to AFEM. On the other side, the boundary conditions (displacements and tractions) of the AFEM model are interpolated from the CPFEM simulations. In AFEM, the lattice deformation, the crack and dislocation behavior can be simulated and calculated at the nanometer scale.

scholarly journals Big Data and IT Network Data Visualization

2018 ◽  
Vol 3 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Lidong Wang
Keyword(s):  
Big Data ◽  
Network Analysis ◽  
Graphics Processing Units ◽  
Data Analytics ◽  
High Performance ◽  
Big Data Analytics ◽  
Network Visualization ◽  
Network Data ◽  
Graphics Processing ◽  
Performance Computing

Visualization with graphs is popular in the data analysis of Information Technology (IT) networks or computer networks. An IT network is often modelled as a graph with hosts being nodes and traffic being flows on many edges. General visualization methods are introduced in this paper. Applications and technology progress of visualization in IT network analysis and big data in IT network visualization are presented. The challenges of visualization and Big Data analytics in IT network visualization are also discussed. Big Data analytics with High Performance Computing (HPC) techniques, especially Graphics Processing Units (GPUs) helps accelerate IT network analysis and visualization.

WETTING SIMULATIONS OF HIGH-PERFORMANCE POLYMER RESINS ON CARBON NANOTUBE SURFACES USING MOLECULAR DYNAMICS

2021 ◽  
Author(s):  
SWAPNIL BAMANE ◽  
PRASHIK GAIKWAD ◽  
MATTHEW RADUE ◽  
S. GOWTHAM ◽  
GREGORY ODEGARD
Keyword(s):  
Molecular Dynamics ◽  
Contact Angle ◽  
Carbon Nanotube ◽  
High Performance ◽  
Material Design ◽  
High Performance Polymer ◽  
Wide Range ◽  
Structural Applications ◽  
Aliphatic Carbon ◽  
Key Parameter

There is a wide application of carbon nanotube (CNT) based composite materials for structural applications in the aerospace industry. CNT composites are often manufactured with high performance polymer resins as a matrix. Resin wettability with specific reinforcement types is a key parameter in manufacturing CNT composites. Wettability of a liquid resin and reinforcement combination is often measured and quantified by the contact angle. Various experimental methods have been developed to determine the contact angle which can be expensive while working with high-performance resins and CNT materials such as CNT yarns, bundles, or forests. Fortunately, computational simulations can greatly facilitate CNT composite material design by efficiently predicting the contact angle for a wide range of resins. In this study, a molecular dynamics (MD) framework is developed to determine the contact angle value of high-performance polymer resins on aromatic and aliphatic carbon surfaces (Figure 1). It is determined that monomer length and functional groups have a significant impact on the contact angle. Further, based on these results, qualitative deductions of contact angle values of highperformance resins on CNT materials with amorphous carbon content are made.

Designing high performance polymer nanocomposites by incorporating robustness-controlled polymeric nanoparticles: insights from molecular dynamics

2022 ◽  
Author(s):  
Guangyi Hou ◽  
Sai Li ◽  
Jun Liu ◽  
Yun-Xuan Weng ◽  
Liqun Zhang
Keyword(s):  
Molecular Dynamics ◽  
Polymer Nanocomposites ◽  
High Performance ◽  
Polymeric Nanoparticles ◽  
Polymer Nanoparticles ◽  
Polymer Matrices ◽  
Interesting Topic ◽  
High Performance Polymer

Introducing polymer nanoparticles into polymer matrices is an interesting topic, and the robustness of polymeric nanoparticles is very crucial for the properties of polymer nanocomposites (PNCs). In this study, by...

scholarly journals EEG dynamical network analysis method reveals the neural signature of visual-motor coordination

PLoS ONE ◽  
2020 ◽  
Vol 15 (5) ◽  
pp. e0231767
Author(s):  
Xinzhe Li ◽  
Bruno Mota ◽  
Toshiyuki Kondo ◽  
Slawomir Nasuto ◽  
Yoshikatsu Hayashi
Keyword(s):  
Network Analysis ◽  
Motor Coordination ◽  
Analysis Method ◽  
Visual Motor Coordination ◽  
Dynamical Network ◽  
Neural Signature ◽  
Visual Motor
Sign in / Sign up

Export Citation Format

Share Document