Evidence map›Paper›PMID 35710099›Full record

ReviewJournal of chemical theory and computation2022

Accelerators for Classical Molecular Dynamics Simulations of Biomolecules.

Derek Jones, Jonathan E Allen, Yue Yang, William F Drew Bennett, Maya Gokhale, Niema Moshiri, Tajana S Rosing

Abstract readReview
In one paragraph

Review in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed.

  1. Article
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  5. Review
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  11. ExploringJournal of inflammation research · 2025
    Article
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  14. Review
  15. Review
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  18. Review
  19. Review
  20. Molecular Dynamics and Other HPC Simulations for Drug Discovery.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Derek JonesDepartment of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States.ORCID 0000-0002-9510-6662
Jonathan E AllenGlobal Security Computing Applications Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0002-4359-8263
Yue YangBiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
William F Drew BennettBiosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.ORCID 0000-0003-3993-9077
Maya GokhaleCenter for Applied Scientific Computing, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
Niema MoshiriDepartment of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States.ORCID 0000-0003-2209-8128
Tajana S RosingDepartment of Computer Science and Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atomistic Molecular Dynamics (MD) simulations provide researchers the ability to model biomolecular structures such as proteins and their interactions with drug-like small molecules with greater spatiotemporal resolution than is otherwise possible using experimental methods. MD simulations are notoriously expensive computational endeavors that have traditionally required massive investment in specialized hardware to access biologically relevant spatiotemporal scales. Our goal is to summarize the fundamental algorithms that are employed in the literature to then highlight the challenges that have affected accelerator implementations in practice. We consider three broad categories of accelerators: Graphics Processing Units (GPUs), Field-Programmable Gate Arrays (FPGAs), and Application Specific Integrated Circuits (ASICs). These categories are comparatively studied to facilitate discussion of their relative trade-offs and to gain context for the current state of the art. We conclude by providing insights into the potential of emerging hardware platforms and algorithms for MD.

Indexed as

AlgorithmsMolecular Dynamics SimulationComputers

Identifiers

PMID35710099
PMCPMC9281402

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.