Evidence map›Paper›PMID 33967984›Full record

ArticleFrontiers in microbiology2021

Computational Simulations Identified Marine-Derived Natural Bioactive Compounds as Replication Inhibitors of SARS-CoV-2.

Vikas Kumar, Shraddha Parate, Sanghwa Yoon, Gihwan Lee, Keun Woo Lee

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

19 citing papers in PubMed, 30 citations in OpenAlex.

  1. "Bridging the clinical, molecular and genetic perspectives on myocarditis in post-COVID-19 era".International journal of cardiology. Cardiovascular risk and prevention · 2026
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  10. Marine AlgaMarine drugs · 2022
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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

5 authors at 1 institution in 1 country.

Vikas KumarDivision of Life Sciences, Department of Bio & Medical Big Data (BK4 Program), Research Institute of Natural Science, Gyeongsang National University, Jinju, South Korea.
Shraddha ParateDivision of Applied Life Science, Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Gyeongsang National University (GNU), Jinju, South Korea.
Sanghwa YoonDivision of Life Sciences, Department of Bio & Medical Big Data (BK4 Program), Research Institute of Natural Science, Gyeongsang National University, Jinju, South Korea.
Gihwan LeeDivision of Applied Life Science, Plant Molecular Biology and Biotechnology Research Center (PMBBRC), Gyeongsang National University (GNU), Jinju, South Korea.
Keun Woo LeeDivision of Life Sciences, Department of Bio & Medical Big Data (BK4 Program), Research Institute of Natural Science, Gyeongsang National University, Jinju, South Korea.
Gyeongsang National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid spread of COVID-19, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide health emergency. Unfortunately, to date, a very small number of remedies have been to be found effective against SARS-CoV-2 infection. Therefore, further research is required to achieve a lasting solution against this deadly disease. Repurposing available drugs and evaluating natural product inhibitors against target proteins of SARS-CoV-2 could be an effective approach to accelerate drug discovery and development. With this strategy in mind, we derived Marine Natural Products (MNP)-based drug-like small molecules and evaluated them against three major target proteins of the SARS-CoV-2 virus replication cycle. A drug-like database from MNP library was generated using Lipinski's rule of five and ADMET descriptors. A total of 2,033 compounds were obtained and were subsequently subjected to molecular docking with 3CL

Indexed as

3CLcpsdummyproCOVID-19MM/PBSA binding free energymolecular dynamics simulations (MD)pharmacokinetic propertiesPLcpsdummyproRdRp

Identifiers

PMID33967984
PMCPMC8097174
OpenAlexW3163784911

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.