Unveiling the Anticancer Potential of Formylbenzyl‐N,N‐Dimethylmethanaminium‐Based Ionic Liquids via Cheminformatics Approaches

Inhibiting tubulin polymerisation, an essential step for cell proliferation, can control cell division. Our in silico study aims to screen out the derivatives of 1,3‐benzodioxole‐tagged formylbenzyl‐N, N‐dimethylmethanaminium ionic liquid for their potential as anticancer agents. All parameters requisite for a compound to act as a pertinent drug candidate are sequentially measured. A library of fifteen 1,3‐benzodioxole‐based ionic liquids with different anions has been designed for molecular docking. Based on binding affinity obtained from protein–ligand molecular docking, ionic liquid comprising of anion bistrifluoromethylamide, octyl sulphate, trifluoromethanesulphonate, dichloroacetate and trifluoroacetate, with common cation—1‐(benzo[d][1,3] dioxol‐5‐yl)‐N‐(4‐formylbenzyl)‐N,N‐dimethylmethanaminium, was found potent among all. The hydrogen bonding and nonbond interactions among ligands and proteins were analysed to determine the efficacy of ligands. The docking results revealed that Compounds 7 and 10 (binding energy −361.33 and −345.4 kcal/mol) might pave the way for potential pharmaceutical candidates. The physicochemical and absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of selected compounds were studied to know their potential as drug candidates. The docked complexes of screened compounds were further commenced for dynamic simulation to fathom the compatibility of compounds. These potent compounds can be synthesised and biologically evaluated for their inhibition effect on microtubule formation.

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Publication Details

Journal
Journal of Chemistry
Published
2025-01-01
DOI
https://doi.org/10.1155/joch/6967930
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.01

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article

Unveiling the Anticancer Potential of Formylbenzyl‐N,N‐Dimethylmethanaminium‐Based Ionic Liquids via Cheminformatics Approaches

Anshul Singh, Mozhgan Afshari, Ravi Tomar, Sonaxi
2 citations
Journal of Chemistry
Computational Drug Discovery Methods
3.01
article

Unveiling the Anticancer Potential of Formylbenzyl‐N,N‐Dimethylmethanaminium‐Based Ionic Liquids via Cheminformatics Approaches

Anshul Singh, Mozhgan Afshari, Ravi Tomar, Sonaxi
article en
2 citations

Abstract

Inhibiting tubulin polymerisation, an essential step for cell proliferation, can control cell division. Our in silico study aims to screen out the derivatives of 1,3‐benzodioxole‐tagged formylbenzyl‐N, N‐dimethylmethanaminium ionic liquid for their potential as anticancer agents. All parameters requisite for a compound to act as a pertinent drug candidate are sequentially measured. A library of fifteen 1,3‐benzodioxole‐based ionic liquids with different anions has been designed for molecular docking. Based on binding affinity obtained from protein–ligand molecular docking, ionic liquid comprising of anion bistrifluoromethylamide, octyl sulphate, trifluoromethanesulphonate, dichloroacetate and trifluoroacetate, with common cation—1‐(benzo[d][1,3] dioxol‐5‐yl)‐N‐(4‐formylbenzyl)‐N,N‐dimethylmethanaminium, was found potent among all. The hydrogen bonding and nonbond interactions among ligands and proteins were analysed to determine the efficacy of ligands. The docking results revealed that Compounds 7 and 10 (binding energy −361.33 and −345.4 kcal/mol) might pave the way for potential pharmaceutical candidates. The physicochemical and absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of selected compounds were studied to know their potential as drug candidates. The docked complexes of screened compounds were further commenced for dynamic simulation to fathom the compatibility of compounds. These potent compounds can be synthesised and biologically evaluated for their inhibition effect on microtubule formation.

Journal of ChemistryVol. 2025(1)
Institute of Management Technology (IN), Baba Mastnath University (IN), Islamic Azad University, Shoushtar Branch (IR)
Islamic Azad University, Council of Science and Technology, U.P.
Openalex Percentile: Top 10%
Computational Drug Discovery Methods
3.01
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