FSATOOL 2.0: An integrated molecular dynamics simulation and trajectory data analysis program

2021 ◽  
Author(s):  
Zirui Shu ◽  
Mincong Wu ◽  
Jun Liao ◽  
Changjun Chen
Keyword(s):  
Molecular Dynamics ◽  
Data Analysis ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Analysis Program ◽  
Trajectory Data ◽  
Data Analysis Program

Hadoop Spark Based Hydrogen Bond Analysis Tool (H-BAT) for Molecular Dynamics Simulation Trajectory Data

2020 ◽  
Author(s):  
Sandeep Surendra Malviya ◽  
Ramakrishnan Edyapatti Periyasamy ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne V N ◽  
Ankita Sonawane ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Hydrogen Bond ◽  
Molecular Dynamics Simulation ◽  
High Performance ◽  
Dynamics Simulation ◽  
Mode Analysis ◽  
Trajectory Data ◽  
Simulation Data ◽  
Hydrogen Bond Formation ◽  
Spark Framework

Molecular dynamics (MD) is a computational technique that works on the Newton's equations of motion to study the dynamics of various biomolecules and, is commonly used by structural biologists. With the development of advanced simulation techniques and increasing computing power, large amounts of data are being generated from these simulations. Various enhanced sampling techniques are currently being used, that are able to capture rare events and generate simulation data in the form of multiple trajectories. Analyzing the simulation trajectory data and extracting meaningful information using the traditional sequential post-simulation data analysis methods are becoming increasingly untenable. Currently, molecular dynamics simulation algorithms that are scalable on high-performance computing clusters are available which generate a huge amount of MD data in short span of time. The need of the hour lies in developing a advanced and high-performance analytics platform based tool that can analyze this huge simulation data in a faster and more efficient way. The Hadoop Spark framework, provides an excellent platform that meets these requirements of handling large amounts of data parallely and perform analytics with high scalability. In this study, a tool name H-BAT has been developed using the Hadoop Spark platform to calculate hydrogen bonding within all solute-solute, solute-solvent and solvent-solvent molecules in large MD simulation trajectories. Vector geometry has been used for calculation of angle and distance between the atoms which are present in the form of triplets of filtered atoms taking part in hydrogen bond formation. The benchmarking was performed up to a data size of 48 GB which showed linear scalability. Additionally, the tool is capable of handling multiple similar trajectories simultaneously. Future enhancement of the tool would include various other analysis like normal mode analysis, RMSD, 2DRMSD and Water Density Analysis using the Hadoop Spark framework.<br>

scholarly journals Drug Binding Dynamics of the Dimeric SARS-CoV-2 Main Protease, Determined by Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Teruhisa S. KOMATSU ◽  
Noriaki Okimoto ◽  
Yohei M. KOYAMA ◽  
Yoshinori HIRANO ◽  
Gentaro MORIMOTO ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Main Protease ◽  
Dynamic Sampling

<div> <div> <div> <p>We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein- ligand complexes and suggest the possibilities of further drug optimisations. <br></p><p><br></p><p><br> </p><div> <div> <div> <p>Raw trajectory data analysed in this paper and movie examples are available at the zenodo repository.<br></p> </div> </div> </div> </div> </div> </div>

scholarly journals Drug Binding Dynamics of the Dimeric SARS-CoV-2 Main Protease, Determined by Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Teruhisa S. KOMATSU ◽  
Noriaki Okimoto ◽  
Yohei M. KOYAMA ◽  
Yoshinori HIRANO ◽  
Gentaro MORIMOTO ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Main Protease ◽  
Dynamic Sampling

<div> <div> <div> <p>We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein- ligand complexes and suggest the possibilities of further drug optimisations. <br></p><p><br></p><p><br> </p><div> <div> <div> <p>Raw trajectory data analysed in this paper and movie examples are available at the zenodo repository.<br></p> </div> </div> </div> </div> </div> </div>

Hadoop Spark Based Hydrogen Bond Analysis Tool (H-BAT) for Molecular Dynamics Simulation Trajectory Data

2020 ◽  
Author(s):  
Sandeep Surendra Malviya ◽  
Ramakrishnan Edyapatti Periyasamy ◽  
Vinod Jani ◽  
Mallikarjunachari Uppuladinne V N ◽  
Ankita Sonawane ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Hydrogen Bond ◽  
Molecular Dynamics Simulation ◽  
High Performance ◽  
Dynamics Simulation ◽  
Mode Analysis ◽  
Trajectory Data ◽  
Simulation Data ◽  
Hydrogen Bond Formation ◽  
Spark Framework

Molecular dynamics (MD) is a computational technique that works on the Newton's equations of motion to study the dynamics of various biomolecules and, is commonly used by structural biologists. With the development of advanced simulation techniques and increasing computing power, large amounts of data are being generated from these simulations. Various enhanced sampling techniques are currently being used, that are able to capture rare events and generate simulation data in the form of multiple trajectories. Analyzing the simulation trajectory data and extracting meaningful information using the traditional sequential post-simulation data analysis methods are becoming increasingly untenable. Currently, molecular dynamics simulation algorithms that are scalable on high-performance computing clusters are available which generate a huge amount of MD data in short span of time. The need of the hour lies in developing a advanced and high-performance analytics platform based tool that can analyze this huge simulation data in a faster and more efficient way. The Hadoop Spark framework, provides an excellent platform that meets these requirements of handling large amounts of data parallely and perform analytics with high scalability. In this study, a tool name H-BAT has been developed using the Hadoop Spark platform to calculate hydrogen bonding within all solute-solute, solute-solvent and solvent-solvent molecules in large MD simulation trajectories. Vector geometry has been used for calculation of angle and distance between the atoms which are present in the form of triplets of filtered atoms taking part in hydrogen bond formation. The benchmarking was performed up to a data size of 48 GB which showed linear scalability. Additionally, the tool is capable of handling multiple similar trajectories simultaneously. Future enhancement of the tool would include various other analysis like normal mode analysis, RMSD, 2DRMSD and Water Density Analysis using the Hadoop Spark framework.<br>

scholarly journals Drug Binding Dynamics of the Dimeric SARS-CoV-2 Main Protease, Determined by Molecular Dynamics Simulation

2020 ◽  
Author(s):  
Teruhisa S. KOMATSU ◽  
Noriaki Okimoto ◽  
Yohei M. KOYAMA ◽  
Yoshinori HIRANO ◽  
Gentaro MORIMOTO ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Active Site ◽  
Binding Sites ◽  
Complex Structure ◽  
Drug Binding ◽  
Dynamics Simulation ◽  
Trajectory Data ◽  
Main Protease ◽  
Dynamic Sampling

<div> <div> <div> <p>We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein- ligand complexes and suggest the possibilities of further drug optimisations. <br></p><p><br></p><p><br> </p><div> <div> <div> <p>Raw trajectory data analysed in this paper and movie examples are available at the zenodo repository.<br></p> </div> </div> </div> </div> </div> </div>

DASH:  A Novel Analysis Method for Molecular Dynamics Simulation Data. Analysis of Ligands of PPAR-γ

2005 ◽  
Vol 48 (9) ◽  
pp. 3214-3220 ◽  
Author(s):  
David W. Salt ◽  
Brian D. Hudson ◽  
Lee Banting ◽  
Matthew J. Ellis ◽  
Martyn G. Ford
Keyword(s):  
Molecular Dynamics ◽  
Data Analysis ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Analysis Method ◽  
Simulation Data ◽  
Ppar Γ

scholarly journals Intuitive, reproducible high-throughput molecular dynamics in Galaxy: a tutorial

2020 ◽  
Author(s):  
Simon A. Bray ◽  
Tharindu Senapathi ◽  
Christopher B. Barnett ◽  
Björn A. Grüning
Keyword(s):  
Molecular Dynamics ◽  
Data Analysis ◽  
Molecular Dynamics Simulation ◽  
High Throughput ◽  
Md Simulation ◽  
Dynamics Simulation ◽  
Computational Data ◽  
Multiple Ligands ◽  
Analysis Platform ◽  
Hsp90 Protein

This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.

scholarly journals Intuitive, reproducible high-throughput molecular dynamics in Galaxy: a tutorial

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Simon A. Bray ◽  
Tharindu Senapathi ◽  
Christopher B. Barnett ◽  
Björn A. Grüning
Keyword(s):  
Molecular Dynamics ◽  
Data Analysis ◽  
Molecular Dynamics Simulation ◽  
High Throughput ◽  
Md Simulation ◽  
Dynamics Simulation ◽  
Computational Data ◽  
Multiple Ligands ◽  
Analysis Platform ◽  
Hsp90 Protein

Abstract This paper is a tutorial developed for the data analysis platform Galaxy. The purpose of Galaxy is to make high-throughput computational data analysis, such as molecular dynamics, a structured, reproducible and transparent process. In this tutorial we focus on 3 questions: How are protein-ligand systems parameterized for molecular dynamics simulation? What kind of analysis can be carried out on molecular trajectories? How can high-throughput MD be used to study multiple ligands? After finishing you will have learned about force-fields and MD parameterization, how to conduct MD simulation and analysis for a protein-ligand system, and understand how different molecular interactions contribute to the binding affinity of ligands to the Hsp90 protein.

Recent advances in polymer molecular dynamics simulation and data analysis

1997 ◽  
Vol 6 (5) ◽  
pp. 855-880 ◽  
Author(s):  
Robert E. Tuzun ◽  
Donald W. Noid ◽  
Bobby G. Sumpter ◽  
Christopher E. Wozny
Keyword(s):  
Molecular Dynamics ◽  
Data Analysis ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Recent Advances
Sign in / Sign up

Export Citation Format

Share Document