Evidence map›Paper›PMID 33132747›Full record

ArticleJournal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology2020

First principle study of silver nanoparticle interactions with antimalarial drugs extracted from

Mahmood Akbari, Razieh Morad, Malik Maaza

Open access · bronzeAbstract read
In one paragraph

Article in Journal of nanoparticle research : an interdisciplinary forum for nanoscale science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

9 citing papers in PubMed, 26 citations in OpenAlex.

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  8. Plants (Basel, Switzerland) · 2021
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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

3 authors at 1 institution in 1 country.

Mahmood AkbariUNESCO-UNISA Africa Chair in Nanoscience & Nanotechnology (U2ACN2), College of Graduate Studies, University of South Africa (UNISA), Pretoria, South Africa.ORCID 0000-0003-1875-2721
Razieh MoradUNESCO-UNISA Africa Chair in Nanoscience & Nanotechnology (U2ACN2), College of Graduate Studies, University of South Africa (UNISA), Pretoria, South Africa.
Malik MaazaUNESCO-UNISA Africa Chair in Nanoscience & Nanotechnology (U2ACN2), College of Graduate Studies, University of South Africa (UNISA), Pretoria, South Africa.
University of South Africa · ZA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Silver nanoparticles have a great potential in a broad range of applications such as drug-delivery carriers because of their antiviral and antibacterial properties. In this study, the coating properties of silver nanoparticle (size range of 1.6 nm) with three common anti-malarial drugs, Artemisinin, Artemether, and Artesunate have been studied by using the quantum mechanical and classical atomistic molecular dynamics simulation in order to use as the drug delivery to treat malaria and COVID-19 diseases. The optimized structure, frequencies, charge distribution, and the electrostatic potential maps of the three drug molecules were simulated by using the density functional theory (DFT) at the B3LYP/6-311++g(d,p) level of theory. Then, molecular dynamics simulation was used to study the coating of AgNP with each of these drugs. The affinity of interaction was obtained as Artesunate > Artemether > Artemisinin which is in agreement with the DFT results on the adsorption of drugs on the Ag(111) slab.

Indexed as

ArtemetherArtemisia annua plantArtemisininArtesunateDensity functional theoryDrug deliveryMolecular dynamics simulationsSilver nanoparticle

Identifiers

PMID33132747
PMCPMC7588957
OpenAlexW3095131484

What OpenQuestion holds

Textmetadata
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.