Evidence map›Paper›PMID 37055578›Full record

ArticleJournal of molecular modeling2023

Exploring potential SARS-CoV-2 Mpro non-covalent inhibitors through docking, pharmacophore profile matching, molecular dynamic simulation, and MM-GBSA.

Yunfan Shi, Liting Dong, Zhuang Ju, Qiufu Li, Yanru Cui, Yiran Liu, Jiaoyu He, Xianping Ding

Abstract read
In one paragraph

Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. SARS-CoV-2 Mpro inhibitors fromFrontiers in chemistry · 2026
    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

8 authors.

Yunfan ShiCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China. shiyunfan2022@163.com.
Liting DongCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Zhuang JuCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Qiufu LiCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Yanru CuiCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Yiran LiuCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Jiaoyu HeCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China.
Xianping DingCollege of Life Sciences, Sichuan University, Chengdu, 610065, Sichuan, China. brainding@scu.edu.cn.

Funding

Branch Office of Science and Technology in Sichuan Province 2020JDS0039
6 · The paper itself

Abstract

contextIn the replication of SARS-CoV-2, the main protease (Mpro/3CLpro) is significant. It is conserved in a number of novel coronavirus variations, and no known human proteases share its cleavage sites. Therefore, 3CLpro is an ideal target. In the report, we screened five potential inhibitors (1543, 2308, 3717, 5606, and 9000) of SARS-CoV-2 Mpro through a workflow. The calculation of MM-GBSA binding free energy showed that three of the five potential inhibitors (1543, 2308, 5606) had similar inhibitor effects to X77 against Mpro of SARS-CoV-2. In conclusion, the manuscript lays the groundwork for the design of Mpro inhibitors.

methodsIn the virtual screening phase, we used structure-based virtual screening (Qvina2.1) and ligand-based virtual screening (AncPhore). In the molecular dynamic simulation part, we used the Amber14SB + GAFF force field to perform molecular dynamic simulation of the complex for 100 ns (Gromacs2021.5) and performed MM-GBSA binding free energy calculation according to the simulation trajectory.

Indexed as

Coronavirus 3C ProteasesCoronavirus Protease InhibitorsMolecular Dynamics SimulationSARS-CoV-2EndopeptidasesHumansMolecular Docking SimulationPharmacophore3C-like proteinase, SARS-CoV-2Coronavirus 3C ProteasesCoronavirus Protease InhibitorsEndopeptidases3CLproMDMM-GBSAVirtual screening

Identifiers

PMID37055578
PMCPMC10100623

What OpenQuestion holds

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Registered trials

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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.