Evidence map›Paper›PMID 36097582›Full record

ArticleStructural chemistry2022

A computational study of potential therapeutics for COVID-19 invoking conceptual density functional theory.

Saloni, Dimple Kumari, Prabhat Ranjan, Tanmoy Chakraborty

Abstract read
In one paragraph

Article in Structural chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Biochemistry research international · 2025
    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

4 authors.

SaloniDepartment of Chemistry and Biochemistry, School of Basic Sciences and Research, Sharda University, 201310, Greater Noida, UP India.
Dimple KumariDepartment of Chemistry and Biochemistry, School of Basic Sciences and Research, Sharda University, 201310, Greater Noida, UP India.
Prabhat RanjanDepartment of Mechatronics Engineering, Manipal University Jaipur, Dehmi Kalan-303007, Rajasthan, India.
Tanmoy ChakrabortyDepartment of Chemistry and Biochemistry, School of Basic Sciences and Research, Sharda University, 201310, Greater Noida, UP India.ORCID 0000-0002-3374-8125

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pandemic, COVID-19, has caused social and economic disruption at a larger pace all over the world. Identification of an effective drug for the deadliest disease is still an exigency. One of the most promising approaches to combat the lethal disease is use of repurposed drugs. This study provides insights into some of the potential repurposed drugs viz. camostat mesylate, hydroxychloroquine, nitazoxanide, and oseltamivir in terms of the computational quantum chemical method. Properties of these compounds have been elucidated in terms of Conceptual Density Functional Theory (CDFT)-based descriptors, IR spectra, and thermochemical properties. Computed results specify that hydroxychloroquine is the most reactive drug among them. Thermochemical data reveals that camostat mesylate has the utmost heat capacity, entropy, and thermal energy. Our findings indicate that camostat mesylate and hydroxychloroquine may be investigated further as potential COVID-19 therapeutics. We anticipate that the current study will aid the scientific community to design and develop viable therapeutics against COVID-19.

Indexed as

Camostat mesylateCDFTCOVID-19HOMO–LUMOHydroxychloroquineRepurposed drug

Identifiers

PMID36097582
PMCPMC9452875

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.