Evidence map›Paper›PMID 34168762›Full record

ArticleChemical science2021

High-resolution mining of the SARS-CoV-2 main protease conformational space: supercomputer-driven unsupervised adaptive sampling.

Théo Jaffrelot Inizan, Frédéric Célerse, Olivier Adjoua, Dina El Ahdab, Luc-Henri Jolly, Chengwen Liu, Pengyu Ren, Matthieu Montes, Nathalie Lagarde, Louis Lagardère and 2 more

Abstract read
In one paragraph

Article in Chemical science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

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  10. Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case.Wiley interdisciplinary reviews. Computational molecular science · 2022
    Article
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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

12 authors.

Théo Jaffrelot InizanSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.ORCID https://orcid.org/0000-0002-2433-1619
Frédéric CélerseSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.ORCID https://orcid.org/0000-0001-8584-6547
Olivier AdjouaSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.
Dina El AhdabSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.ORCID https://orcid.org/0000-0002-6583-9216
Luc-Henri JollySorbonne Université, IP2CT, FR 2622 CNRS Paris France.
Chengwen LiuUniversity of Texas at Austin, Department of Biomedical Engineering Texas USA.
Pengyu RenUniversity of Texas at Austin, Department of Biomedical Engineering Texas USA.
Matthieu MontesLaboratoire GBCM, EA 7528, CNAM, Hésam Université Paris France.
Nathalie LagardeLaboratoire GBCM, EA 7528, CNAM, Hésam Université Paris France.
Louis LagardèreSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.
Pierre MonmarchéSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.
Jean-Philip PiquemalSorbonne Université, LCT, UMR 7616 CNRS Paris France louis.lagardere@sorbonne-universite.fr pierre.monmarche@sorbonne-universite.fr jean-philip.piquemal@sorbonne-universite.fr.ORCID https://orcid.org/0000-0001-6615-9426

Funding

DEVELOPMENT OF A NEXT-GENERATION NUCLEIC ACID FORCE FIELDR01GM106137 · NIGMS · WASHINGTON UNIVERSITY · PI JAY PONDER, Pengyu Ren · 2013 to 2026
$3.5M
Specificity and Selectivity in Protein-Ion BindingR01GM114237 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI PONDER, JAY, REN, PENGYU · 2015 to 2023
$2.6M
NIGMS NIH HHS R01 GM106137NIGMS NIH HHS R01 GM114237
6 · The paper itself

Abstract

We provide an unsupervised adaptive sampling strategy capable of producing μs-timescale molecular dynamics (MD) simulations of large biosystems using many-body polarizable force fields (PFFs). The global exploration problem is decomposed into a set of separate MD trajectories that can be restarted within a selective process to achieve sufficient phase-space sampling. Accurate statistical properties can be obtained through reweighting. Within this highly parallel setup, the Tinker-HP package can be powered by an arbitrary large number of GPUs on supercomputers, reducing exploration time from years to days. This approach is used to tackle the urgent modeling problem of the SARS-CoV-2 Main Protease (M

Identifiers

PMID34168762
PMCPMC8179654

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.