Published

2022-07-05

A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE

TEORÍA DEL FUNCIONAL DE LA DENSIDAD (DFT) SOBRE NANOTUBOS DE CARBONO DOPADOS CON SILICIO Si-CNT COMO PORTADOR DEL FÁRMACO BMSF-BENZ UTILIZADO PARA LA ENFERMEDAD DE OSTEOPOROSIS

DOI:

https://doi.org/10.15446/mo.n65.99010

Keywords:

BMSF-BENZ, Drug adsorption, Drug delivery system, Density functional theory, Thermodynamic properties (en)
BMSF-BENZ, adsorción de fármacos, sistema de administración de fármacos, teoría del funcional de la densidad, propiedades termodinámicas (es)

Downloads

Authors

  • Zaid H. Al-Sawaff Material Science & Engineering Dept., Faculty of Engineering and Architecture, Kastamonu University, Turkey. Medical Instrumentation Technology, Technical Engineering College, Northern Technical University, Mosul. https://orcid.org/0000-0001-8789-4905
  • Serap Senturk Dalgic Department of Physics, Faculty of Science, Trakya University, 22030, Edirne. https://orcid.org/0000-0003-2541-9214
  • Fatma Kandemirli Biomedical Engineering Department, Faculty of Engineering & Architecture, Kastamonu University, Kastamonu.

This study aims to investigate the capability of Silicon-Doped Carbon Nanotube (Si-CNT) to detect and adsorb the BMSF-BENZ ((4-Bromo-7-methoxy-1-(2-methoxyethyl)-5-{[3-(methylsulfonyl)phenyl]methyl}-2-[4- (propane-2-))yl)phenyl]-1H-1,3-benzothiazole) molecular. For this purpose, we considered different configurations for adsorbing BMSF-BENZ drugs on the surface of the Si-CNT nanotube. All considered configurations are optimized using the density functional theory (DFT) at the 6-31G∗∗ basis set and B3LYP-B97D level of theory. Then from optimized structures, for each nanoparticle, we selected seven stable locations for the adsorption of BMSF-BENZ in (Br, N8, N9, N58, O35, O41 and S) active atoms on the surface of the selected nanoparticle. The quantum theory of atoms in molecules (QTAIM), reduced density gradient (RDG) analysis, and molecular orbital (MO) analysis were also established. The calculated results indicate that the distance between nanotube and drug from the N8 site is lower than from all other locations sites for all investigated complexes, and adsorption of BMSF-BENZ from the N8 site is more favorable for the Si-CNT nanotube. The adsorption energy, hardness, softness, and fermi energy results reveal that the interaction of BMSF-BENZ with Si-CNT is a promising adsorbent for this drug as Adsorption energy Eads of BMSF-BENZ/Si-CNT complexes are (-13.08, -43.50, -17.90, -31.29, -25.57, -16.56, and -28.05) kcal/mol in the gas phase. As well, the appropriate and spontaneous interaction between the BMSF-BENZ drug and Si-CNT nanoparticle was confirmed by investigating the quantum chemical molecular descriptors and solvation Gibbs free energies of all atoms.

Este estudio tiene como objetivo investigar la capacidad de los nanotubos de carbono dopados con silicio (Si-CNT) para detectar y adsorber el BMSF-BENZ ((4-Bromo-7-metoxi-1-(2-metoxietil)-5-{[3-(metilsulfonil)fenil]metil}-2-[4-(propano-2-))il)fenil]-1H-1,3-benzotiazol) molecular. Para ello, consideramos diferentes configuraciones para adsorber fármacos BMSF-BENZ en la superficie del nanotubo Si-CNT. Todas las configuraciones consideradas se optimizan utilizando la teoría del funcional de la densidad (DFT) en el conjunto básico 6-31G ∗∗ y los niveles de teoría B3LYP-B97D. Luego, a partir de estructuras optimizadas para cada nanopartícula, seleccionamos siete ubicaciones estables para la adsorción de BMSF-BENZ en (Br, N8, N9, N58, O35, O41 y S) átomos activos en la superficie de la nanopartícula seleccionada. También se establecieron la teoría cuántica de átomos en moléculas (QTAIM), el análisis de gradiente de densidad reducida (RDG) y el análisis orbital molecular (MO). Los resultados calculados indican que la distancia entre el nanotubo y el fármaco desde el sitio N8 es menor que desde todos los demás sitios de ubicación para todos los complejos investigados y la adsorción de BMSF-BENZ desde el sitio N8 es más favorable para el nanotubo Si-CNT. Los resultados de energía de adsorción, dureza, suavidad y energía de Fermi revelan que la interacción de BMSF-BENZ con Si-CNT es un adsorbente prometedor para este fármaco, ya que los Eads de energía de absorción de los complejos BMSF-BENZ/Si-CNT son (-13.08, - 43.50, -17.90, -31.29, -25.57, -16.56, y -28.05) kcal/mol en la fase gaseosa. Además, la interacción adecuada y espontanea entre el fármaco BMSF-BENZ y la nanopartícula Si-CNT se confirmó investigando los descriptores moleculares químicos cuánticos y las energías libres de Gibbs de solvatación de todos los átomos.

References

C. Cooper, G. Campion, and L. J. Melton, Osteoporosis INT 2, 285–289 (1992). https://doi.org/10.1007/BF01623184 DOI: https://doi.org/10.1007/BF01623184

S. P. Tuck and R. M. Francis, Postgrad. Med. J. 78, 526 (2002). https://pmj.bmj.com/content/78/923/526 DOI: https://doi.org/10.1136/pmj.78.923.526

R. Eastell, I. T. Boyle, and et al., Int. J. Med. 91, 71 (1998). https://doi.org/10.1093/qjmed/91.2.71 DOI: https://doi.org/10.1093/qjmed/91.2.71

M. Gerspacher, E. Altmann, and et al., Bioorg. Med. Chem. Lett. 20, 5161 (2010). https://www.sciencedirect.com/science/article/pii/S0960894X10009728

M. Gu, Q. Zhang, and S. Lamon, Nat. Rev. Mater. 1, 16070 (2016). https://doi.org/10.1038/natrevmats.2016.70 DOI: https://doi.org/10.1038/natrevmats.2016.70

S. S. Varghese, S. Lonkar, K. K. Singh, S. Swaminathan, and A. Abdala, Sens. Actuators B Chem. 218, 160 (2015). https://www.sciencedirect.com/science/article/pii/S0925400515005146 DOI: https://doi.org/10.1016/j.snb.2015.04.062

A. S. Rad and K. Ayub, J. Alloy. Compd. 678, 317 (2016). https://doi.org/10.1016/j.jallcom.2016.03.175 DOI: https://doi.org/10.1016/j.jallcom.2016.03.175

P. Pannopard, P. Khongpracha, M. Probst, and J. Limtrakul, J. Mol. Graph. Model. 28, 62 (2009). https://doi.org/10.1016/j.jmgm.2009.04.005 DOI: https://doi.org/10.1016/j.jmgm.2009.04.005

M. Conti, V. Tazzari, C. Baccini, G. Pertici, L. P. Serino, and U. De Giorgi, In Vivo 20, 697 (2006). https://pubmed.ncbi.nlm.nih.gov/17203748/

R. Singh and J. Lillard, Exp. Mol. Pathol. 86, 215 (2009). https://doi.org/10.1016/j.yexmp.2008.12.004 DOI: https://doi.org/10.1016/j.yexmp.2008.12.004

R. Bakry, R. M. Vallant, and et al., Int. J. Nanomedicine 2, 639 (2007). https://pubmed.ncbi.nlm.nih.gov/18203430/

T. Zhang, S. Mubeen, M. V. Myung, and M. Deshusses, Nanotechnology 19, 332001 (2008). https://doi.org/10.1088/0957-4484/19/33/332001 DOI: https://doi.org/10.1088/0957-4484/19/33/332001

S. M. Haidary, E. P. Córcoles, and N. K. Ali, J. Nanomater. 2012, 1 (2012). https://doi.org/10.1155/2012/830503 DOI: https://doi.org/10.1155/2012/830503

P. A. Gowri Sankar and K. Udhayakumar, J. Nanomater. 2013, 1 (2013). https://doi.org/10.1155/2013/293936 DOI: https://doi.org/10.1155/2013/293936

F. J. Martínez-Vázquez, M. V. Cabañas, and et al., Acta Biomaterialia 15, 200 (2015). https://doi.org/10.1016/j.actbio.2014.12.021 DOI: https://doi.org/10.1016/j.actbio.2014.12.021

R. Bagheri, M. Babazadeh, E. Vessally, M. Es’haghi, and A. Bekhradnia, Inorg. Chem. Commun. 90, 8 (2018). https://doi.org/10.1016/j.inoche.2018.01.020 DOI: https://doi.org/10.1016/j.inoche.2018.01.020

A. Allouche, J. Comput. Chem. 32, 174 (2010). https://doi.org/10.1002/jcc.21600 DOI: https://doi.org/10.1002/jcc.21600

A. I. Alrawashdeh and J. B. Lagowski, RSC Adv. 8, 30520 (2018). https://doi.org/10.1039/C8RA02460J DOI: https://doi.org/10.1039/C8RA02460J

M. Athar, S. Das, P. Jha, and A. M. Jha, Supramol. Chem. 30, 982 (2018). https://doi.org/10.1080/10610278.2018.1517876 DOI: https://doi.org/10.1080/10610278.2018.1517876

L. De Souza, H. Da Silva, and W. De Almedia, ChemistryOpen 7, 902 (2018). https://doi.org/10.1002/open.201800209 DOI: https://doi.org/10.1002/open.201800209

N. Wazzan, K. Soliman, and W. Halim, J. Mol. Model. 25, 265 (2019). https://doi.org/10.1007/s00894-019-4147-8 DOI: https://doi.org/10.1007/s00894-019-4147-8

M. Bilge, Anadolu University Journal of Science and Technology A - Applied Sciences and Engineering 18, 398 (2017). https://doi.org/10.18038/aubtda.281646 DOI: https://doi.org/10.18038/aubtda.273802

A. H. Shntaif, Z. M. Rashi, Z. Al-Sawaff, and F. Kandemirli, Russ. J. Bioorg. Chem. 47, 777 (2021). https://doi.org/10.1134/S106816202103016X DOI: https://doi.org/10.1134/S106816202103016X

J. S. Al-Otaibi, Y. S. Mary, and et al., J. Mol. Model. 27, 113 (2021). https://doi.org/10.1007/s00894-021-04742-z DOI: https://doi.org/10.1007/s00894-021-04742-z

S. Bashiri, E. Vessally, and et al., Vacuum 136, 156 (2017). https://doi.org/10.1016/j.vacuum.2016.12.003 DOI: https://doi.org/10.1016/j.vacuum.2016.12.003

M. A. Hossain, M. R. Hossain, and et al., Chem. Phys. Lett. 754, 137701 (2020). https://doi.org/10.1016/j.cplett.2020.137701 DOI: https://doi.org/10.1016/j.cplett.2020.137701

J. Li, Y. Lu, and et al., Nano Letters 3, 929 (2003). https://doi.org/10.1021/nl034220x DOI: https://doi.org/10.1021/nl034220x

Z. Qiao, Z. Wang, C. Zhang, S. Yuan, Y. Zhu, J. Wang, and S. Wang, AIChE Journal 59, 215 (2013). https://doi.org/10.1002/aic.13781 DOI: https://doi.org/10.1002/aic.13781

C. F. Matta and R. F. W. Bader, Proteins: Structure, Function, and Bioinformatics 52, 360 (2003). https://doi.org/10.1002/prot.10414 DOI: https://doi.org/10.1002/prot.10414

T. Lu and F. Chen, J. Comput. Chem. 33, 580 (2011). https://doi.org/10.1002/jcc.22885 DOI: https://doi.org/10.1002/jcc.22885

T. Williams and C. Kelley, Gnuplot 4.4 user manual (2011). http://www.gnuplot.info/docs_4.4/gnuplot.pdf

S. U. D. Shamim, T. Hussain, and et al., J. Mol. Model. 26, 153 (2020). https://doi.org/10.1007/s00894-020-04419-z. DOI: https://doi.org/10.1007/s00894-020-04419-z

Z. Al-Sawaff, S. S. Dalgic, and F. Kandemirli, Eur. J. Chem. 12, 314 (2021). https://doi.org/10.5155/eurjchem.12.3.314-322.2143 DOI: https://doi.org/10.5155/eurjchem.12.3.314-322.2143

J. Aarons, L. G. Verga, N. D. M. Hine, and C. K. Skylaris, Electron. Struct. 1, 035002 (2019). https://doi.org/10.1088/2516-1075/ab34f5 DOI: https://doi.org/10.1088/2516-1075/ab34f5

M. Shahabi and H. Raissi, J. Biomol. Struct. Dyn. 36, 2517 (2017). https://doi.org/10.1080/07391102.2017.1360209 DOI: https://doi.org/10.1080/07391102.2017.1360209

How to Cite

APA

Al-Sawaff, Z. H., Senturk Dalgic, S. and Kandemirli, F. . (2022). A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE. MOMENTO, (65), 1–24. https://doi.org/10.15446/mo.n65.99010

ACM

[1]
Al-Sawaff, Z.H., Senturk Dalgic, S. and Kandemirli, F. 2022. A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE. MOMENTO. 65 (Jul. 2022), 1–24. DOI:https://doi.org/10.15446/mo.n65.99010.

ACS

(1)
Al-Sawaff, Z. H.; Senturk Dalgic, S.; Kandemirli, F. . A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE. Momento 2022, 1-24.

ABNT

AL-SAWAFF, Z. H.; SENTURK DALGIC, S.; KANDEMIRLI, F. . A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE. MOMENTO, [S. l.], n. 65, p. 1–24, 2022. DOI: 10.15446/mo.n65.99010. Disponível em: https://revistas.unal.edu.co/index.php/momento/article/view/99010. Acesso em: 31 mar. 2025.

Chicago

Al-Sawaff, Zaid H., Serap Senturk Dalgic, and Fatma Kandemirli. 2022. “A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE”. MOMENTO, no. 65 (July):1-24. https://doi.org/10.15446/mo.n65.99010.

Harvard

Al-Sawaff, Z. H., Senturk Dalgic, S. and Kandemirli, F. . (2022) “A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE”, MOMENTO, (65), pp. 1–24. doi: 10.15446/mo.n65.99010.

IEEE

[1]
Z. H. Al-Sawaff, S. Senturk Dalgic, and F. . Kandemirli, “A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE”, Momento, no. 65, pp. 1–24, Jul. 2022.

MLA

Al-Sawaff, Z. H., S. Senturk Dalgic, and F. . Kandemirli. “A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE”. MOMENTO, no. 65, July 2022, pp. 1-24, doi:10.15446/mo.n65.99010.

Turabian

Al-Sawaff, Zaid H., Serap Senturk Dalgic, and Fatma Kandemirli. “A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE”. MOMENTO, no. 65 (July 5, 2022): 1–24. Accessed March 31, 2025. https://revistas.unal.edu.co/index.php/momento/article/view/99010.

Vancouver

1.
Al-Sawaff ZH, Senturk Dalgic S, Kandemirli F. A DENSITY FUNCTIONAL THEORY (DFT) STUDY ON SILICON DOPED CARBON NANOTUBE Si-CNT AS A CARRIER FOR BMSF-BENZ DRUG USED FOR OSTEOPOROSIS DISEASE. Momento [Internet]. 2022 Jul. 5 [cited 2025 Mar. 31];(65):1-24. Available from: https://revistas.unal.edu.co/index.php/momento/article/view/99010

Download Citation

CrossRef Cited-by

CrossRef citations2

1. Serap Dalgic, Fatma Kandemirli. (2025). Comparison of the Electron Donor-Acceptor and Sensing Capacity of The Selected CNTs in Drug Delivery Applications. Proceedings of the Technical University of Sofia, 74(3) https://doi.org/10.47978/TUS.2024.74.03.001.

2. Serap Senturk Dalgic, Zaid H. Al-Sawaff, Seyfettin Dalgic, Fatma Kandemirli. (2023). A comparative DFT study on Al- and Si- doped single-wall carbon nanotubes (SWCNTs) for Ribavirin drug sensing and detection. Materials Science in Semiconductor Processing, 158, p.107360. https://doi.org/10.1016/j.mssp.2023.107360.

Dimensions

PlumX

  • Citations
  • Scopus - Citation Indexes: 1
  • Captures
  • Mendeley - Readers: 1

Article abstract page views

394

Downloads