RAS PhysicsКристаллография Crystallography Reports

  • ISSN (Print) 0023-4761
  • ISSN (Online) 3034-5510

STRUCTURAL BIOINFORMATICS STUDY OF THE STRUCTURAL BASIS OF SUBSTRATE SPECIFICITY OF PURINE NUCLEOSIDE PHOSPHORYLASE FROM THERMUS THERMOPHILUS

PII
10.31857/S0023476123010101-1
DOI
10.31857/S0023476123010101
Publication type
Status
Published
Authors
Volume/ Edition
Volume 68 / Issue number 2
Pages
268-275
Abstract
Molecular dynamics simulations were performed for wild-type purine nucleoside phosphorylase in complexes with two substrates (adenosine and guanosine). The MD simulations were also performed for the mutant form of the enzyme with the same substrates. The free energy changes upon the formation of the complexes were evaluated from the molecular dynamics trajectories by the MM-GBSA method.
Keywords
MOLECULAR DYNAMICS SIMULATIONS STRUCTURAL BIOINFORMATICS STUDY
Date of publication
14.09.2025
Year of publication
2025
Number of purchasers
0
Views
11

References

  1. 1. Timofeev V.I., Fateev I.V., Kostromina M.A. et al. // J. Biomol. Struct. Dyn. 2020. V. 40. P. 1. https://doi.org/10.1080/07391102.2020.1848628
  2. 2. Tomoike F., Kuramitsu S., Masui R. // Extremophiles. 2013. V. 17. P. 505. https://doi.org/10.1007/s00792-013-0535-7
  3. 3. Погосян Л.Г., Акопян Ж.И. // Биомедицинская химия. 2013. Т. 59. № 5. С. 483. https://doi.org/10.18097/pbmc20135905483
  4. 4. Salomon-Ferrer R., Case D.A., Walker R.C. // WIREs Comput. Mol. Sci. 2013. V. 3. P. 198. https://doi.org/10.1002/wcms.1121
  5. 5. Case D.A., Cheatham T.E., III, Darden T. et al. // J. Comput. Chem. 2005. V. 26. P. 1668. https://doi.org/10.1002/jcc.20290
  6. 6. Maier J.A., Martinez C., Kasavajhala K. et al. // J. Chem. Theory Comput. 2015. V. 11. P. 3696. https://doi.org/10.1021/acs.jctc.5b00255
  7. 7. Salomon-Ferrer R., Goetz A.W., Poole D. et al. // J. Chem. Theory Comput. 2013. V. 9. P. 3878. https://doi.org/10.1021/ct400314y
  8. 8. Jorgensen W. L., Chandrasekhar J., Madura J.D. et al. // J. Chem. Phys. 1983. V. 79. P. 926. https://doi.org/10.1063/1.445869
  9. 9. Allen M.P., Tildesley D.J. Computer simulation of liquids. New York: Oxford university press, 1991. https://doi.org/10.2307/2938686
  10. 10. Berendsen H.J.C., Postma J.P.M., van Gunsteren W.F. et al. // J. Chem. Phys. 1984. V. 81. P. 3684. https://doi.org/10.1063/1.448118
  11. 11. Darden T., York D., Pedersen L. // J. Chem. Phys. 1993. V. 98. P. 10089. https://doi.org/10.1063/1.464397
  12. 12. Kollman P.A., Massova I., Reyes C. et al. // Acc. Chem. Res. 2000. V. 33. P. 889. https://doi.org/10.1021/ar000033j
  13. 13. Srinivasan J., Trevathan M.W., Beroza P. et al. // Theor. Chem. Acc. 1999. V. 101. P. 426. https://doi.org/10.1007/s002140050460
  14. 14. Miller B.R., McGee T.D., Swails J.M. et al. // J. Chemical Theory and Computation. 2012. V. 8. P. 3314. https://doi.org/10.1021/ct300418h
  15. 15. Onufriev A., Bashford D., Case D.A. // Proteins. 2004. V. 55. P. 383. https://doi.org/10.1002/prot.20033
  16. 16. Schrödinger L.L.C. The PyMOL Molecular Graphics System, Version 2.0
  17. 17. Mikhailopulo I.A., Miroshnikov A.I. // Acta Naturae. 2010. V. 2. P. 36. https://doi.org/10.32607/20758251-2017-9-2-47-58
  18. 18. Fateev I.V., Kostromina M.A., Abramchik Y.A. et al. // Biomolecules. 2021. V. 11. P. 586. https://doi.org/10.3390/biom11040586
  19. 19. Roy B., Depaix A., Périgaud C. et al. // Chem. Rev. 2016. V. 116. P. 7854. https://doi.org/10.1021/acs.chemrev.6b00174
  20. 20. Almendros M., Berenguer J., Sinisterra J.V. // Appl. Environmental Microbiology. 2012. V. 78. P. 3128. https://doi.org/10.1128/AEM.07605-11
  21. 21. Fateev I.V., Kharitonova M.I., Antonov K.V. et al. // Chemistry. 2015. V. 21. P. 13401. https://doi.org/10.1002/chem.201501334
QR
Translate

Индексирование

Scopus

Scopus

Scopus

Crossref

Scopus

Higher Attestation Commission

At the Ministry of Education and Science of the Russian Federation

Scopus

Scientific Electronic Library