Molecular Dynamic Modeling of Pharmacological Vector-Receptor Pairs for Specific Drug Delivery to the Tumor: Atomic-Molecular Mechanisms of RGD-Peptide Embedding in the αvβ3-Integrin Receptor

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

In this work, computer-based molecular dynamics studies of the interaction of the pharmacological pair “vector–receptor” have been carried out to model promising mechanisms and processes of specific drug delivery to the tumor. The purpose of these computational molecular dynamic calculations is to study the interaction processes and determine the spatial positions of the RGD peptide + αvβ3-integrin receptor system, which is solvated with water. The configuration positions of the RGD-peptide + αvβ3-integrin system in 100 ns relaxed states were obtained from molecular dynamic modeling. In this case, two RGD peptides were modeled located outside and inside the αvβ3-integrin receptor. One of the two RGDs is a peptide of the original PDB file localized inside the αvβ3-integrin receptor. The other RGD peptide is located outside the receptor in its initial position, freely diffuses throughout the entire area of the modeling cell, and naturally comes into contact and binds to αvβ3-integrin.

About the authors

I. A Baigunov

Dubna State University

Dubna, Russia

Kh. T Kholmurodov

Dubna State University; Frank Laboratory of Neutron Physics, Joint Institute for Nuclear Research; Lomonosov Moscow State University; S.U. Umarov Physical-Technical Institute

Email: kholnirzg@gmail.com
Dubna, Russia; Dubna, Russia; Moscow, Russia; Dushanbe, Republic of Tajikistan

M. A Khusenzoda

Tajik Technical University named after academician M. Osimi

Dushanbe, Republic of Tajikistan

E. D Gribova

Dubna State University

Dubna, Russia

N. A Polotnyanko

Dubna State University

Dubna, Russia

I. V Mukhina

Dubna State University

Dubna, Russia

P. P Gladyshev

Dubna State University; Institute of Macromolecular Compounds, Russian Academy of Sciences

Dubna, Moscow Region, Russia; Moscow, Russia

A. A Lipengolts

National Medical Research Center of Oncology named after N.N. Blokhin, Ministry of Health of the Russian

Moscow, Russia

References

  1. Zhang Q., Radvak P., Lee J., Xu Y., Cao-Dao V., Zheng W., Chen C. Z., Xie H., and Ye Y. Mitoxantrone modulates a heparan sulfate-spike complex to inhibit SARS-CoV-2 infection. Sci Rep., 12 (1), 6294 (2022). doi: 10.1038/s41598-022-10293-x
  2. Направленный транспорт лекарственных веществ (тематический выпуск). Рос. хим. журнал (Журн. Рос. хим. об-ва им. Д. Н. Менделеева), 56, 1–162 (2012).
  3. Di Cristo L., Grimaldi B., Catelani T., Vazques E., Pompa P. P., and Sabella S. Repeated exposure to aerosolized graphene oxide mediates autophagy inhibition and inflammation in a three-dimensional human airway model. Mater. Today Bio., 6, 100050 (2020). doi: 10.1016/j.mtbio.2020.100050
  4. Yun Y. H., Lee B. K., and Park K. Controlled drug delivery: Historical perspective for the next generation. J. Control. Release, 219, 2–7 (2015). doi: 10.1016/j.jconrel.2015.10.005
  5. Mendes R. G., Bachmatiuk A., Buchner B., Cuniberti G., and Rümmell M. H. Carbon nanostructures as multifunctional drug delivery platforms. J. Mater. Chem. B, 1 (4), 401–428 (2013). doi: 10.1039/c2tb00085g
  6. Klusenov M. A., Dushanov E. B., Kholmurodov Kh. T., Zaki M. M., and Swellam N. H. On correlation effect of the van-der-waals and intramolecular forces for the nucleotide chain - metallic nanoparticles - Carbon nanotube binding. Open. Biochem. J., 10, 17–26 (2016). doi: 10.2174/1874091X016100010017
  7. Каньгин В. В., Кичигин А. И., Губанова Н. В. и Таскаев С. Ю. Возможности бор-нейтронозахватной терапии в лечении злокачественных опухолей головного мозга. Вестн. рентгенологии и радиологии, № 6, 36–42 (2015). doi: 10.20862/0042-4676-2015-0-6-142-142
  8. Taskaev S., Bessmeltsov V., Bikchurina M., Bykov T., Kasatov D., Kolesnikov I., Nikolaev A., Oks E., Ostreinov G., Savinov S., Shuklina A., Sokolova E., and Yushkov G. Measurement of the 10B(d,d0)8Be, 10B(d,d1)8Be*, 10B(d,p2)9Be*, 11B(d,d0)9Be, and 11B(d,d2)9Be* reactions cross-sections at the deuteron energies up to 2.2 MeV. Nucl. Instruments Methods Phys. Res., Section B: Beam Interactions with Materials and Atoms, 557, 165527 (2024).
  9. Kasatov D. A., Kolesnikov Y. A., Konovalova V. D., Porosov V. V., Sokolova E. O., Shchudin I. M., and Taskaev S. Y., Development of a system for forming a beam of cold neutrons for the VITA accelerating neutron source. Phys. Particles Nucl. Lett., 21 (3), 404–409 (2024).
  10. Taskaev S., Bessmeltsov V., Bikchurina M., Bykov T., Kasatov D., Kolesnikov I., Nikolaev A., Oks E., Ostreinov G., Savinov S., Shuklina A., Sokolova E., and Yushkov G. Measurement of the 11B(p,d0)8Be and the 11B(p,d1)8Be* reactions cross-sections at the proton energies up to 2.2 MeV. Nucl. Instruments Methods Phys. Res., Section B: Beam Interactions with Materials and Atoms, 555, 165490 (2024).
  11. Case D. A., Cheatham T. E. 3rd, Darden T., Gohlke H., Luo R., Merz K. M. Jr., Onufriev A., Simmerling C., Wang B., and Woods R. J. The Amber biomolecular simulation programs. J. Comput. Chem., 26 (16), 1668–1688 (2005). doi: 10.1002/jcc.20290
  12. Case D. A., Aktulga H. M., Belfon K., Cerutti D. S., Cisneros G. A., Cruzeiro V. W. D., Forouzesh N., Giese T. J., Gotz A. W., Gohlke H., Izadi S., Kasavajhala K., Kaymak M. C., King E., Kurtzman T., Lee T. S., Li P., Liu J., Luchko T., Luo R., Manathunga M., Machado M. R., Nguyen H. M., O'Hearn K. A., Onufriev A. V., Pan F., Pantano S., Qi R., Rahnamoun A., Risheh A., Schott-Verdugo S., Shajan A., Swails J., Wang J., Wei H., Wu X., Wu Y., Zhang S., Zhao S., Zhu Q., Cheatham T. E. 3rd, Roe D. R., Roitberg A., Simmerling C., York D. M., Nagan M. C., and Merz K. M. Jr. AmberTools. J. Chem. Inf. Model., 63 (20), 6183–6191 (2023). doi: 10.1021/acs.jcim.3c01153
  13. Lee T. S., Cerutti D. S., Mermelstein D., Lin C., LeGrand S., Giese T. J., Roitberg A., Case D. A., Walker R. C., and York D. M. GPU-Accelerated molecular dynamics and free energy methods in Amber18: Performance enhancements and new features. J. Chem. Inf. Model., 58 (10), 2043–2050 (2018). doi: 10.1021/acs.jcim.8b00462
  14. Models in bioscience and materials research: Molecular dynamics and related techniques. Ed. by Kh. Kholmurodov (Nova Science Publ. Ltd., 2013).
  15. Computational Materials and Biological Sciences. Ed. by Kh. Kholmurodov (Nova Science Publ. Ltd., 2015).
  16. PDB ID: 3ZE2. doi: 10.2210/pdb3ZE2/pdb

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Copyright (c) 2025 Russian Academy of Sciences