Evidence map›Paper›PMID 34132436›Full record

ArticleJournal of molecular recognition : JMR2021

Identification of Severe Acute Respiratory Syndrome Coronavirus-2 inhibitors through in silico structure-based virtual screening and molecular interaction studies.

Iqbal Azad, Tahmeena Khan, Akhilesh Kumar Maurya, Mohd Irfan Azad, Nidhi Mishra, Amer M Alanazi

Abstract read
In one paragraph

Article in Journal of molecular recognition : JMR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

6 authors.

Iqbal AzadDepartment of Chemistry, Integral University, Lucknow, India.
Tahmeena KhanDepartment of Chemistry, Integral University, Lucknow, India.ORCID 0000-0002-0467-4315
Akhilesh Kumar MauryaDepartment of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj, India.
Mohd Irfan AzadDepartment of Chemistry, Jamia Milia Islamia, New Delhi, India.
Nidhi MishraDepartment of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj, India.
Amer M AlanaziDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The novel coronavirus Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 has caused a worldwide pandemic. The fatal virus has affected the health of human beings as well as the socio-economic situation all over the world. To date, no concrete medicinal solution has been proposed to combat the viral infection, calling for an urgent, strategic, and cost-effective drug development approach that may be achievable by applying targeted computational and virtual screening protocols. Immunity is the body's natural defense against disease-causing pathogens, which can be boosted by consuming plant-based or natural food products. Active constituents derived from natural sources also scavenge the free radicals and have anti-inflammatory activities. Herbs and spices have been used for various medicinal purposes. In this study, 2,96 365 natural and synthetic derivatives (ligands) belonging to 102 classes of compounds were obtained from PubChem and assessed on Lipinski's parameters for their potential bioavailability. Out of all the derivatives, 3254 obeyed Lipinski's rule and were virtually screened. The 115 top derivatives were docked against SARS-CoV-2, SARS-CoV, MERS-CoV, and HCoV-HKV1 main proteases (M

Indexed as

Antiviral AgentsBiological AvailabilityBlood-Brain BarrierComputer SimulationCoronavirus 3C ProteasesDrug Evaluation, PreclinicalHumansLigandsMolecular Docking SimulationMolecular Dynamics SimulationSARS-CoV-23C-like proteinase, SARS-CoV-2Antiviral AgentsCoronavirus 3C ProteasesLigandsdockingLipinskiproteaseSARS-CoV-2simulationvirtual screening

Identifiers

PMID34132436
PMCPMC8420533

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.