Evidence map›Paper›PMID 41310171›Full record

ArticleScientific reports2025

High-throughput in vitro screening and in silico analysis for Zika virus inhibitor identification.

Sania Batool, Santosh Chokkakula, Beom Kyu Kim, Ji-Hyun Park, Seong Cheol Min, Ju Ryeong Lee, Gi Chan Lee, Dong Gyu Lee, Se Hee An, Aman Jain and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

15 authors.

Sania BatoolDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Santosh ChokkakulaDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Beom Kyu KimDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Ji-Hyun ParkDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Seong Cheol MinDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Ju Ryeong LeeDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Gi Chan LeeDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Dong Gyu LeeDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Se Hee AnDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Aman JainDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea.
Sang Chul ShinTechnological Convergence Center, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea.
Gyeongmin KimMedicinal Materials Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea.
Byungsun JeonMedicinal Materials Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea.
Yun Hee BaekDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea. microuni@chungbuk.ac.kr.
Min-Suk SongDepartment of Microbiology, Chungbuk National University College of Medicine and Medical Research Institute, Cheongju, Chungbuk, 28644, Republic of Korea. songminsuk@chungbuk.ac.kr.

Funding

National Research Foundation of Korea NRF-2021R1A2C2006961
6 · The paper itself

Abstract

Zika Virus (ZIKV) is a mosquito-borne virus that can cause serious health problems, including birth defects and neurological complications. Unfortunately, there are no antivirals currently approved for its treatments. In this study, we tested a library of 348 chemical compounds to find potential candidates that could block ZIKV infection. Seven compounds showed strong antiviral activity in laboratory experiments. Among them, Cephalotaxine, Docusate Sodium, and Saikosaponin B2 were the most effective. However, Docusate Sodium may pose safety risks at higher doses, and Saikosaponin B2 has poor solubility, which could limit its use as a drug. To better understand how these compounds work, molecular docking was employed to predict interactions between the active compounds and two important ZIKV proteins: NS5 and the NS2B-NS3 protease complex. The docking results supported the in vitro findings, revealing strong binding affinities, particularly for Saikosaponin B2. Molecular dynamics simulations confirmed stable binding of Saikosaponin B2 and Aloperine to NS5, with Saikosaponin B2 showing greater stability and consistent interactions. Drug-likeness and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analysis indicated that while some compounds possess favorable pharmacokinetic properties, others may require structural optimization. Overall, this study identifies several promising lead compounds for further preclinical development and highlights the utility of integrating in vitro screening with computational modeling to accelerate antiviral drug discovery against ZIKV.

Indexed as

Antiviral AgentsHigh-Throughput Screening AssaysZika VirusAnimalsComputer SimulationHumansMolecular Docking SimulationMolecular Dynamics SimulationSaponinsViral Nonstructural ProteinsZika Virus InfectionAntiviral AgentsSaponinsViral Nonstructural ProteinsADMET analysisAntiviral screeningMolecular dockingZika virus

Identifiers

PMID41310171
PMCPMC12749539

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.