Evidence map›Paper›PMID 41941507›Full record

ArticlePloS one2026

Synthesis of substituted biphenyls and in vitro evaluation of antimicrobial and anti-biofilm activities supported by in silico ADMET prediction.

Saad Alghamdi, Ahmed Hassen Shntaif, Yasser Hussein Issa Mohammed

Abstract read
In one paragraph

Article in PloS one, 2026. 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
–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

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

3 authors.

Saad AlghamdiDepartment of Clinical Laboratory Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.ORCID https://orcid.org/0000-0003-4532-9128
Ahmed Hassen ShntaifDepartment of Chemistry, College of Science for Women, University of Babylon, Alhilla, Iraq.ORCID https://orcid.org/0000-0003-0723-5622
Yasser Hussein Issa MohammedDepartment of Pharmacy, Collage of Medicine and Health Science, Hajjah University, Hajjah, Yemen.ORCID https://orcid.org/0000-0003-1086-7292

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Antibiotic resistance represents a critical global health challenge, necessitating the development of innovative antimicrobial agents. This research focuses on the design and evaluation of antimicrobial compounds through chemical synthesis and computational methodologies. Biaryl analogues were synthesized via Suzuki coupling reactions and assessed for in vitro antimicrobial activity against Staphylococcus aureus, Escherichia coli, and Candida albicans. Computational approaches, including molecular docking, crystal structure optimization, and toxicity profiling, were employed to explore potential molecular interactions and preliminary safety profiles. The synthesized biaryl derivatives demonstrated variable antimicrobial activity across the tested microorganisms. Among these, 2-methoxy-4'-nitro-1,1'-biphenyl (3i) exhibited the most potent antibacterial activity against both Gram-positive and Gram-negative strains. As a preliminary screening, these findings highlight the potential of selected biaryl derivatives as lead candidates for further investigation. Future studies are required to validate activity against resistant strains and to evaluate efficacy in vivo.

Indexed as

Anti-Bacterial AgentsAnti-Infective AgentsBiofilmsBiphenyl CompoundsCandida albicansComputer SimulationEscherichia coliMicrobial Sensitivity TestsMolecular Docking SimulationStaphylococcus aureusStructure-Activity RelationshipAnti-Bacterial AgentsAnti-Infective AgentsBiphenyl Compounds

Identifiers

PMID41941507
PMCPMC13052900

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.