Large-Scale Molecular Dynamics Simulations of Cellular Compartments

Eric Wilson; John Vant; Jacob Layton; Ryan Boyd; Hyungro Lee; Matteo Turilli; Benjamín Hernández; Sean Wilkinson; Shantenu Jha; Chitrak Gupta; Daipayan Sarkar; Abhishek Singharoy

doi:10.1007/978-1-0716-1394-8_18

Large-Scale Molecular Dynamics Simulations of Cellular Compartments

Eric Wilson, John Vant, Jacob Layton, Ryan Boyd, Hyungro Lee, Matteo Turilli, Benjamín Hernández, Sean Wilkinson, Shantenu Jha, Chitrak Gupta, Daipayan Sarkar, Abhishek Singharoy

Workflow and Ecosystem Services

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Scopus citations

Abstract

Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

Original language	English
Title of host publication	Methods in Molecular Biology
Publisher	Humana Press Inc.
Pages	335-356
Number of pages	22
DOIs	https://doi.org/10.1007/978-1-0716-1394-8_18
State	Published - 2021

Publication series

Name	Methods in Molecular Biology
Volume	2302
ISSN (Print)	1064-3745
ISSN (Electronic)	1940-6029

Funding

The authors acknowledge start-up funds from the School of Molecular Sciences and Center for Applied Structure Discovery at Arizona State University, and the resources of the OLCF at the Oak Ridge National Laboratory, which is supported by the Office of Science at DOE under Contract No. DEAC05-00OR22725, made available via the INCITE program. We also acknowledge NAMD and VMD developments supported by NIH (P41GM104601) and R01GM098243-02 for supporting our study of membrane proteins.

Funders	Funder number
School of Molecular Sciences and Center for Applied Structure Discovery at Arizona State University
National Institutes of Health	P41GM104601
U.S. Department of Energy	DEAC05-00OR22725
National Institute of General Medical Sciences	R01GM098243
Office of Science

Keywords

Ensemble toolkit
High-performance computing
Molecular dynamics
Multiscale simulation
NAMD
Photosynthetic chromatophore
VMD

Access to Document

10.1007/978-1-0716-1394-8_18

Cite this

Wilson, E., Vant, J., Layton, J., Boyd, R., Lee, H., Turilli, M., Hernández, B., Wilkinson, S., Jha, S., Gupta, C., Sarkar, D., & Singharoy, A. (2021). Large-Scale Molecular Dynamics Simulations of Cellular Compartments. In Methods in Molecular Biology (pp. 335-356). (Methods in Molecular Biology; Vol. 2302). Humana Press Inc.. https://doi.org/10.1007/978-1-0716-1394-8_18

@inbook{789ca41089d74fbb8a73623d82de1ef3,

title = "Large-Scale Molecular Dynamics Simulations of Cellular Compartments",

abstract = "Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.",

keywords = "Ensemble toolkit, High-performance computing, Molecular dynamics, Multiscale simulation, NAMD, Photosynthetic chromatophore, VMD",

author = "Eric Wilson and John Vant and Jacob Layton and Ryan Boyd and Hyungro Lee and Matteo Turilli and Benjam{\'i}n Hern{\'a}ndez and Sean Wilkinson and Shantenu Jha and Chitrak Gupta and Daipayan Sarkar and Abhishek Singharoy",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Science+Business Media, LLC, part of Springer Nature.",

year = "2021",

doi = "10.1007/978-1-0716-1394-8_18",

language = "English",

series = "Methods in Molecular Biology",

publisher = "Humana Press Inc.",

pages = "335--356",

booktitle = "Methods in Molecular Biology",

}

TY - CHAP

T1 - Large-Scale Molecular Dynamics Simulations of Cellular Compartments

AU - Wilson, Eric

AU - Vant, John

AU - Layton, Jacob

AU - Boyd, Ryan

AU - Lee, Hyungro

AU - Turilli, Matteo

AU - Hernández, Benjamín

AU - Wilkinson, Sean

AU - Jha, Shantenu

AU - Gupta, Chitrak

AU - Sarkar, Daipayan

AU - Singharoy, Abhishek

PY - 2021

Y1 - 2021

N2 - Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

AB - Molecular dynamics or MD simulation is gradually maturing into a tool for constructing in vivo models of living cells in atomistic details. The feasibility of such models is bolstered by integrating the simulations with data from microscopic, tomographic and spectroscopic experiments on exascale supercomputers, facilitated by the use of deep learning technologies. Over time, MD simulation has evolved from tens of thousands of atoms to over 100 million atoms comprising an entire cell organelle, a photosynthetic chromatophore vesicle from a purple bacterium. In this chapter, we present a step-by-step outline for preparing, executing and analyzing such large-scale MD simulations of biological systems that are essential to life processes. All scripts are provided via GitHub.

KW - Ensemble toolkit

KW - High-performance computing

KW - Molecular dynamics

KW - Multiscale simulation

KW - NAMD

KW - Photosynthetic chromatophore

KW - VMD

UR - http://www.scopus.com/inward/record.url?scp=85104729819&partnerID=8YFLogxK

U2 - 10.1007/978-1-0716-1394-8_18

DO - 10.1007/978-1-0716-1394-8_18

M3 - Chapter

C2 - 33877636

AN - SCOPUS:85104729819

T3 - Methods in Molecular Biology

SP - 335

EP - 356

BT - Methods in Molecular Biology

PB - Humana Press Inc.

ER -

Large-Scale Molecular Dynamics Simulations of Cellular Compartments

Abstract

Publication series

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this