ArticleJournal of molecular modeling2023
Identification of natural diterpenes isolated from Azorella species targeting dispersin B using in silico approaches.
Article in Journal of molecular modeling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- Calendula officinalis as a source of KRAS-targeted anticancer agents: a comprehensive computational assessment.Medical oncology (Northwood, London, England) · 2025Article
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Authors and funding
10 authors at 8 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextA bacterial biofilm is a cluster of bacterial cells embedded in a self-produced matrix of extracellular polymeric substances such as DNA, proteins, and polysaccharides. Several diseases have been reported to cause by bacterial biofilms, and difficulties in treating these infections are of concern. This work aimed to identify the inhibitor with the highest binding affinity for the receptor protein by screening various inhibitors obtained from Azorella species for a potential target to inhibit dispersin B. This work shows that azorellolide has the highest binding affinity (- 8.2 kcal/mol) among the compounds tested, followed by dyhydroazorellolide, mulinone A, and 7-acetoxy-mulin-9,12-diene which all had a binding affinity of - 8.0 kcal/mol. To the best of our knowledge, this is the first study to evaluate and contrast several diterpene compounds as antibacterial biofilm chemicals.
methodsHere, molecular modelling techniques tested 49 diterpene compounds of Azorella and six FDA-approved antibiotics medicines for antibiofilm activity. Since protein-like interactions are crucial in drug discovery, AutoDock Vina was initially employed to carry out structure-based virtual screening. The drug-likeness and ADMET properties of the chosen compounds were examined to assess the antibiofilm activity further. Lipinski's rule of five was then applied to determine the antibiofilm activity. Then, molecular electrostatic potential was used to determine the relative polarity of a molecule using the Gaussian 09 package and GaussView 5.08. Following three replica molecular dynamic simulations (using the Schrodinger program, Desmond 2019-4 package) that each lasted 100 ns on the promising candidates, binding free energy was estimated using MM-GBSA. Structural visualisation was used to test the binding affinity of each compound to the crystal structure of dispersin B protein (PDB: 1YHT), a well-known antibiofilm compound.
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