Tuning surface properties of thiophene-based thin films on glass substrates for cancer cell adhesion, drug release control, and computational analysis

This study explores the potential of six novel thiophene derivative thin films (THIOs) for reducing cancer cell adhesion and enhancing controlled drug release on inert glass substrates. Thiophene derivatives 3a-c and 5a-c were synthesized and characterized using IR, <sup>1</sup>H NMR, <sup>13</sup>C NMR, and elemental analysis before being spin-coated onto glass to form thin films. SEM analysis and roughness measurements were used to assess their structural and functional properties. Biological evaluations demonstrated that the films significantly reduced HepG2 liver cancer cell adhesion (~ 78% decrease vs. control) and enabled controlled drug release, validated through the Korsmeyer-Peppas model (R<sup>2</sup> > 0.99). Theoretical studies, including in-silico target prediction, molecular docking with JAK1 (PDB: 4E4L), and DFT calculations, provided insights into the electronic properties and chemical reactivity of these compounds. Notably, compound 5b exhibited the best binding energy (-7.59 kcal/mol) within the JAK1 pocket, aligning with its observed apoptotic behavior in cell culture. DFT calculations further revealed that 5b had the lowest calculated energy values; -4.89 eV (HOMO) and - 3.22 eV (LUMO), and the energy gap was found to be 1.66 eV, supporting its role in JAK1 inhibition and cancer cell adhesion reduction. These findings underscore the promise of thiophene derivatives in biomedical applications, potentially leading to safer surgical procedures and more effective localized drug delivery systems.

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Publication Details

Journal
Scientific Reports
Published
2025-06-20
DOI
https://doi.org/10.1038/s41598-025-05691-w
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Tuning surface properties of thiophene-based thin films on glass substrates for cancer cell adhesion, drug release control, and computational analysis

Raghda Abo Gabal, Heba M. Metwally, Ehab Abdel‐Latif, Omar M El-Banna
Scientific Reports
Computational Drug Discovery Methods
article

Tuning surface properties of thiophene-based thin films on glass substrates for cancer cell adhesion, drug release control, and computational analysis

Raghda Abo Gabal, Heba M. Metwally, Ehab Abdel‐Latif, Omar M El-Banna
article en

Abstract

This study explores the potential of six novel thiophene derivative thin films (THIOs) for reducing cancer cell adhesion and enhancing controlled drug release on inert glass substrates. Thiophene derivatives 3a-c and 5a-c were synthesized and characterized using IR, <sup>1</sup>H NMR, <sup>13</sup>C NMR, and elemental analysis before being spin-coated onto glass to form thin films. SEM analysis and roughness measurements were used to assess their structural and functional properties. Biological evaluations demonstrated that the films significantly reduced HepG2 liver cancer cell adhesion (~ 78% decrease vs. control) and enabled controlled drug release, validated through the Korsmeyer-Peppas model (R<sup>2</sup> > 0.99). Theoretical studies, including in-silico target prediction, molecular docking with JAK1 (PDB: 4E4L), and DFT calculations, provided insights into the electronic properties and chemical reactivity of these compounds. Notably, compound 5b exhibited the best binding energy (-7.59 kcal/mol) within the JAK1 pocket, aligning with its observed apoptotic behavior in cell culture. DFT calculations further revealed that 5b had the lowest calculated energy values; -4.89 eV (HOMO) and - 3.22 eV (LUMO), and the energy gap was found to be 1.66 eV, supporting its role in JAK1 inhibition and cancer cell adhesion reduction. These findings underscore the promise of thiophene derivatives in biomedical applications, potentially leading to safer surgical procedures and more effective localized drug delivery systems.

Scientific ReportsVol. 15(1)
Mansoura University (EG)
Science and Technology Development Fund, Mansoura University
Good health and well-being
Openalex Percentile: Top 84%
Computational Drug Discovery Methods
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