Evidence map›Paper›PMID 41255839›Full record

ArticleIranian journal of biotechnology2025

Structure-Guided Discovery of Drug-like Compounds Targeting HPV16 E6 for Antiviral Therapy Development.

Jingying Shang, Qifan Jiang, Ting Liu, Huifang Cong

Abstract read
In one paragraph

Article in Iranian journal of biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jingying ShangDepartment of Heilongjiang University of Chinese Medicine, Harbin 150040, China.
Qifan JiangDepartment of Qiqihar Center for Disease Control and Prevention, Qiqihar 161006, China.
Ting LiuDepartment of Heilongjiang University of Chinese Medicine, Harbin 150040, China.
Huifang CongDepartment of Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin 150001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Human papillomavirus type 16 (HPV16) E6 oncoprotein is a key factor in the progression of cervical and other HPV-related cancers. Targeting E6 with small molecule inhibitors represents a promising strategy for the development of novel antiviral therapies. Objectives: This study aimed to discover and characterize small-molecule compounds that exhibit high affinity for HPV16 E6, possess favorable drug-like properties, and inhibit HPV16 E6, using advanced computational approaches. Materials and Methods: We integrated molecular dynamics simulations to capture the conformational flexibility of HPV16 E6 and employed structure-based virtual screening to identify potential inhibitors from a large chemical library. The binding stability and interaction patterns of selected compounds were evaluated through molecular docking, binding free energy calculations, and extended molecular dynamics simulations. In silico ADMET profiling was performed to assess the pharmacokinetic and toxicity properties of the top candidates. Results: Nine lead compounds demonstrated stable binding to a key functional residue (CYS51) of HPV16 E6, with strong theoretical binding affinities confirmed by MM-GBSA calculations and molecular dynamics analysis. ADMET predictions indicated that most candidates possessed favorable pharmacokinetic profiles, although two compounds showed potential toxicity concerns. Conclusion: Our findings provide a robust computational framework for the identification of drug-like small molecules targeting HPV16 E6, offering promising candidates for further development as antiviral agents against HPV-associated diseases. Experimental validation is warranted to confirm the inhibitory activity and therapeutic potential of these compounds.

Indexed as

Antiviral agentsDrug discoveryHPV16 E6Molecular dynamicsSmall molecule inhibitorsVirtual screening

Identifiers

PMID41255839
PMCPMC12620837

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