Evidence map›Paper›PMID 27919903›Full record

ArticleAntimicrobial agents and chemotherapy2017

High-Throughput Screening and Prediction Model Building for Novel Hemozoin Inhibitors Using Physicochemical Properties.

Nguyen Tien Huy, Pham Lan Chi, Jun Nagai, Tran Ngoc Dang, Evaristus Chibunna Mbanefo, Ali Mahmoud Ahmed, Nguyen Phuoc Long, Le Thi Bich Thoa, Le Phi Hung, Afaf Titouna and 3 more

Abstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

13 authors.

Nguyen Tien HuyDepartment of Clinical Product Development, Institute of Tropical Medicine (NEKKEN), Nagasaki University, Sakamoto, Nagasaki, Japan tienhuy@nagasaki-u.ac.jp hiraken@nagasaki-u.ac.jp.
Pham Lan ChiGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan.
Jun NagaiGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan.
Tran Ngoc DangUniversity of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam.
Evaristus Chibunna MbanefoGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan.
Ali Mahmoud AhmedFaculty of Medicine, Al-Azhar University, Cairo, Egypt.
Nguyen Phuoc LongOnline Research Club, Nagasaki University, Sakamoto, Nagasaki, Japan.
Le Thi Bich ThoaOnline Research Club, Nagasaki University, Sakamoto, Nagasaki, Japan.
Le Phi HungOnline Research Club, Nagasaki University, Sakamoto, Nagasaki, Japan.
Afaf TitounaGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan.
Kaeko KameiDepartment of Biomolecular Engineering, Kyoto Institute of Technology, Sakyo-ku, Kyoto, Japan.
Hiroshi UedaGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan.
Kenji HirayamaGraduate School of Biomedical Sciences, Nagasaki University, Bunkyo-machi, Nagasaki, Japan tienhuy@nagasaki-u.ac.jp hiraken@nagasaki-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is essential to continue the search for novel antimalarial drugs due to the current spread of resistance against artemisinin by Plasmodium falciparum parasites. In this study, we developed in silico models to predict hemozoin inhibitors as a potential first-step screening for novel antimalarials. An in vitro colorimetric high-throughput screening assay of hemozoin formation was used to identify hemozoin inhibitors from 9,600 structurally diverse compounds. The physicochemical properties of positive hits and randomly selected compounds were extracted from the ChemSpider database; they were used for developing prediction models to predict hemozoin inhibitors using two different approaches, i.e., traditional multivariate logistic regression and Bayesian model averaging. Our results showed that a total of 224 positive-hit compounds exhibited the ability to inhibit hemozoin formation, with 50% inhibitory concentrations (IC

Indexed as

Models, TheoreticalAntimalarialsBayes TheoremComputer SimulationDose-Response Relationship, DrugHemeHemeproteinsHigh-Throughput Screening AssaysLogistic ModelsPlasmodium falciparumReproducibility of ResultsAntimalarialsHemeHemeproteinshemozoinantimalarialcompoundshematinhemehemozoinHTSin silico modelphysical propertiesscreening

Identifiers

PMID27919903
PMCPMC5278743

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.