Evidence map›Paper›PMID 40743310›Full record

ArticlePloS one2025

Structure-based virtual screening, molecular docking, and MD simulation studies: An in-silico approach for identifying potential MBL inhibitors.

Emira Noumi, Mejdi Snoussi, Nouha Bouali, Mamdouh M Alshammari, Hisham N Altayb, Muhammad Afzal, Vincenzo De Feo

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Review
  3. Frontiers in bioinformatics · 2026
    Review
  4. Review
  5. Review
  6. 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

7 authors.

Emira NoumiDepartment of Biology, College of Science, University of Ha'il, Hail, Saudi Arabia.
Mejdi SnoussiDepartment of Biology, College of Science, University of Ha'il, Hail, Saudi Arabia.ORCID https://orcid.org/0000-0002-2309-2601
Nouha BoualiDepartment of Biology, College of Science, University of Ha'il, Hail, Saudi Arabia.
Mamdouh M AlshammariDepartment of Biology, College of Science, University of Ha'il, Hail, Saudi Arabia.
Hisham N AltaybDepartment of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Muhammad AfzalDepartment of Pharmaceutical Sciences, Batterjee Medical College, Pharmacy Program, Jeddah, Saudi Arabia.
Vincenzo De FeoDepartment of Pharmacy, University of Salerno, Salerno, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global rise of antibiotic-resistant infections has been driven in part by the spread of bacteria producing metallo-β-lactamase (MBL), particularly New Delhi metallo-β-lactamase-1 (NDM-1). Currently, there are no clinically approved inhibitors targeting NDM-1 or other MBLs, highlighting the urgent need for novel therapeutic agents. This study addresses this gap by identifying potential NDM-1 inhibitors through a comprehensive in silico workflow. A total of 4,561 natural product compounds were screened using a machine learning (ML)-based quantitative structure-activity relationship (QSAR) model. Molecular docking was then performed to prioritize hits, followed by Tanimoto similarity-based clustering to identify representative compounds. The three most promising compounds identified were S721-1034, S904-0022, and N118-0137. 300 ns molecular dynamics (MD) simulation was used to examine binding interactions and stability of a control molecule (meropenem (0RV)) and the three selected compounds (S721-1034, S904-0022, and N118-0137) with the target protein. Among the three compounds evaluated, S904-0022 demonstrated consistent root mean square deviation (RMSD) values throughout the molecular dynamics (MD) simulation compared to the other two ligands. Additionally, S904-0022 exhibited considerable affinity with key residues, including Gln123, His250, Trp93, and Val73, indicating robust interactions with NDM-1. The strength of this interaction was further validated by a significantly favorable binding free energy of -35.77 kcal/mol, markedly better than the control compound (-18.90 kcal/mol). The strength of this interaction was further validated by a significantly favorable binding free energy of -35.77 kcal/mol, markedly better than the control compound (-18.90 kcal/mol). The findings of this study provide valuable insights into the molecular interactions and stability of these compounds, which can be used to improve drug development and explore the interactions between proteins and ligands. The study concluded that S904-0022 exhibited substantial therapeutic potential and requires additional experimental exploration as a potential NDM-1 inhibitor.

Indexed as

beta-Lactamase Inhibitorsbeta-LactamasesMolecular Docking SimulationMolecular Dynamics SimulationDrug Evaluation, PreclinicalQuantitative Structure-Activity Relationshipbeta-Lactamase Inhibitorsbeta-lactamase NDM-1beta-Lactamases

Identifiers

PMID40743310
PMCPMC12312920

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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.