Evidence map›Paper›PMID 33200115›Full record

ArticleChemRxiv : the preprint server for chemistry2020

Tuning Proton Transfer Thermodynamics in SARS-Cov-2 Main Protease: Implications for Catalysis and Inhibitor Design.

Laura Zanetti-Polzi, Micholas Dean Smith, Chris Chipot, James C Gumbart, Diane L Lynch, Anna Pavlova, Jeremy C Smith, Isabella Daidone

Open access · greenAbstract readPreprint
In one paragraph

Article in ChemRxiv : the preprint server for chemistry, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 4 countries.

Laura Zanetti-PolziCenter S3, CNR Institute of Nanoscience, Via Campi 213/A, I-41125 Modena, Italy.
Micholas Dean SmithDepartment of Biochemistry, Molecular and Cellular Biology, The University of Tennessee, Knoxville. 309 Ken and Blaire Mossman Bldg. 1311 Cumberland Avenue, Knoxville, TN 37996, United States.
Chris ChipotUMR 7019, Universite de Lorraine, Laboratoire International Associe CNRS.
James C GumbartSchool of Physics, Georgia Institute of Technology, Atlanta GA 30332, United States.
Diane L LynchSchool of Physics, Georgia Institute of Technology, Atlanta GA 30332, United States.
Anna PavlovaSchool of Physics, Georgia Institute of Technology, Atlanta GA 30332, United States.
Jeremy C SmithUT/ORNL Center for Molecular Biophysics, Biosciences Division, Oak Ridge National Laboratory, TN 37831, United States.
Isabella DaidoneDepartment of Physical and Chemical Sciences, University of L'Aquila, Via Vetoio, I-67010 L'Aquila, Italy.
Oak Ridge National Laboratory · USCenter for NanoScience · DEUniversity of L'Aquila · IT

Funding

Altering Hepatitis B Virus assembly through pharmacological interventionR01AI148740 · NIAID · GEORGIA INSTITUTE OF TECHNOLOGY · PI GUMBART, JAMES C. · 2020 to 2024
$2.0M
NIAID NIH HHS R01 AI148740
6 · The paper itself

Abstract

In this comutational work a hybrid quantum mechanics/molecular mechanics approach, the MD-PMM approach, is used to investigate the proton transfer reaction the activates the catalytic activity of SARS-CoV-2 main protease. The proton transfer thermodynamics is investigated for the apo ensyme (i.e., without any bound substrate or inhibitor) and in the presence of a inhibitor, N3, which was previously shown to covalently bind SARS-CoV-2 main protease.

Indexed as

Computational ChemistryCovid 19Main Protease Mproproton transferquantum mechanics molecular mechanicsSARS CoV 2thermodynamics

Identifiers

PMID33200115
PMCPMC7668740
OpenAlexW4230153126

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.