Evidence map›Paper›PMID 36355278›Full record

ArticleJournal of microbiology (Seoul, Korea)2022

Coumarin-based combined computational study to design novel drugs against Candida albicans.

Akhilesh Kumar Maurya, Nidhi Mishra

Abstract read
In one paragraph

Article in Journal of microbiology (Seoul, Korea), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Frontiers in cellular and infection microbiology · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. 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

2 authors.

Akhilesh Kumar MauryaChemistry Laboratory, Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, Prayagraj, 211015, India.
Nidhi MishraChemistry Laboratory, Department of Applied Sciences, Indian Institute of Information Technology, Allahabad, Prayagraj, 211015, India. nidhimishra@iiita.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Candida species cause the most prevalent fungal illness, candidiasis. Candida albicans is known to cause bloodstream infections. This species is a commensal bacterium, but it can cause hospital-acquired diseases, particularly in COVID-19 patients with impaired immune systems. Candida infections have increased in patients with acute respiratory distress syndrome. Coumarins are both naturally occurring and synthetically produced. In this study, the biological activity of 40 coumarin derivatives was used to create a three-dimensional quantitative structure activity relationship (3D-QSAR) model. The training and test minimum inhibitory concentration values of C. albicans active compounds were split, and a regression model based on statistical data was established. This model served as a foundation for the creation of coumarin derivative QSARs. This is a unique way to create new therapeutic compounds for various ailments. We constructed novel structural coumarin derivatives using the derived QSAR model, and the models were confirmed using molecular docking and molecular dynamics simulation.

Indexed as

CandidiasisCOVID-19Antifungal AgentsCandida albicansCoumarinsHumansMolecular Docking SimulationQuantitative Structure-Activity RelationshipAntifungal AgentsCoumarinsCandida albicansCoumarinCOVID-19dockingMD simulationQSAR modelling

Identifiers

PMID36355278
PMCPMC9647762

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.