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FDA ONAYLI BAZI İLAÇLARIN SARS-COV-2 PAPAİN-LİKE PROTEAZ İNHİBİTÖR AKTİVİTESİNİN İN SİLİKO DEĞERLENDİRİLMESİ

Yıl 2023, , 978 - 986, 20.09.2023
https://doi.org/10.33483/jfpau.1311496

Öz

Amaç: Bu çalışmada ZINC veri tabanından indirilen 1300 adet FDA onaylı ilacın SARS-CoV-2'nin papain-like proteaz yapısı üzerinde (PDB:7JIT) in siliko çalışmalarının yapılması amaçlanmıştır.
Gereç ve Yöntem: ZINC veri tabanından elde edilen toplam 1300 FDA onaylı ilaç, dört ayrı moleküler doking programı kullanılarak PLpro (PDB ID: 7JIT) ile moleküler doking çalışması gerçekleştirildi. AutoDock Vina ve Sybyl-X ile doking analizinde, sırasıyla conivaptan ve amfoterisin B elde edildi. Glide SP ve Glide XP ile doking analizi sırasıyla fludarabin ve panobinostat ile sonuçlandı. Bu dört ilacın stabilitelerini kontrol etmek için 120 ns'lik bir süre boyunca moleküler dinamik simülasyonları gerçekleştirildi.
Sonuç ve Tartışma: 1300 ilaç molekülünün SARS-CoV-2 papain benzeri proteazı üzerinde dört farklı moleküler doking programı kullanılarak elde edilen sonuçların güvenilirliği, ko-kristal ligandın yeniden yerleştirilmesiyle kontrol edildi. Fludarabin, conivaptan, amphotericin-B, panobinostat ve PLpro arasındaki protein-ligand etkileşimleri verildi. Moleküler dinamik çalışmasında dört sistem için RMSD, RMSF, Rg ve SASA analizleri yapıldı. 120 ns'nin sonlarına doğru hafifçe sapan amfoterisin B hariç, RMSD'nin dört sistemde de 120 ns'nin tamamında sabit kaldığı gözlendi. Dört sistemin tümü için RMSF grafiklerinde önemli bir dalgalanma fark edilmedi.

Kaynakça

  • 1. Celik, I., Erol, M., Duzgun, Z. (2021). In silico evaluation of potential inhibitory activity of remdesivir, favipiravir, ribavirin and galidesivir active forms on SARS-CoV-2 RNA polymerase. Molecular Diversity, 26(1), 279-292. [CrossRef]
  • 2. Rastogi, M., Pandey, N., Shukla, A., Singh, S.K. (2020). SARS coronavirus 2: from genome to infectome. Respiratory Research, 21, 1-15. [CrossRef]
  • 3. Patel, K.P., Vunnam, S.R., Patel, P.A., Krill, K.L., Korbitz, P.M., Gallagher, J.P., Suh, J.E., Vunnam, R.R. (2020). Transmission of SARS-CoV-2: An update of current literature. European Journal of Clinical Microbiology and Infectious Diseases, 39, 2005-2011. [CrossRef]
  • 4. Wang, Z., Fu, Y., Guo, Z., Li, J., Li, J., Cheng, H., Lu, B., Sun, Q. (2020). Transmission and prevention of SARS-CoV-2. Biochemical Society Transactions, 48(5), 2307-2316. [CrossRef]
  • 5. Hasöksüz, M., Kilic, S., Sarac, F. (2020). Coronaviruses and Sars-CoV-2. Turkish Journal of Medical Sciences, 50(9), 549-556. [CrossRef]
  • 6. Çelik, İ., Erol, M., Uzunhisarcikli, E., Ufuk, İ. (2022). Virtual screening and molecular docking analysis on three sars-cov-2 drug targets by multiple computational approach. Journal of Faculty of Pharmacy of Ankara University, 46(2), 376-392. [CrossRef]
  • 7. Klemm, T., Ebert, G., Calleja, D.J., Allison, C.C., Richardson, L.W., Bernardini, J.P., Lu, B.G., Kuchel, N.W., Grohmann, C., Shibata, Y. (2020). Mechanism and inhibition of the papain‐like protease, PLpro, of SARS‐CoV‐2. The EMBO Journal, 39(18), 1-17. [CrossRef]
  • 8. Alamri, M.A., ul Qamar, M.T., Mirza, M.U., Alqahtani, S.M., Froeyen, M., Chen, L.L. (2020). Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches. Journal of Pharmaceutical Analysis, 10(6), 546-559. [CrossRef]
  • 9. Ullrich, S., Nitsche, C. (2020). The SARS-CoV-2 main protease as drug target. Bioorganic and Medicinal Chemistry Letters, 30(17), 127377. [CrossRef]
  • 10. Gao, X., Qin, B., Chen, P., Zhu, K., Hou, P., Wojdyla, J.A., Wang, M., Cui, S. (2021). Crystal structure of SARS-CoV-2 papain-like protease. Acta Pharmaceutica Sinica B, 11(1), 237-245. [CrossRef]
  • 11. Bosken, Y.K., Cholko, T., Lou, Y.C., Wu, K.P., Chang, C.A. (2020). Insights into dynamics of inhibitor and ubiquitin-like protein binding in SARS-CoV-2 papain-like protease. Frontiers in Molecular Biosciences, 7, 174. [CrossRef]
  • 12. Friesner, R.A., Banks, J.L., Murphy, R.B., Halgren, T.A., Klicic, J.J., Mainz, D.T., Repasky, M.P., Knoll, E.H., Shelley, M., Perry, J.K. (2004). Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of Medicinal Chemistry, 47(7), 1739-1749. [CrossRef]
  • 13. Friesner, R.A., Murphy, R.B., Repasky, M.P., Frye, L.L., Greenwood, J.R., Halgren, T.A., Sanschagrin, P.C., Mainz, D.T. (2006). Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. Journal of Medicinal Chemistry, 49(21), 6177-6196. [CrossRef]
  • 14. Trott, O., Olson, A.J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455-461. [CrossRef]
  • 15. Jain, A.N. (2007). Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. Journal of Computer-aided Molecular Design, 21, 281-306. [CrossRef]
  • 16. Osipiuk, J., Azizi, S.A., Dvorkin, S., Endres, M., Jedrzejczak, R., Jones, K.A., Kang, S., Kathayat, R.S., Kim, Y., Lisnyak, V.G. (2021). Structure of papain-like protease from SARS-CoV-2 and its complexes with non-covalent inhibitors. Nature Communications, 12, 1-9. [CrossRef]
  • 17. Irwin, J.J. (2008). Using ZINC to acquire a virtual screening library. Current Protocols in Bioinformatics, 22(1), 14.6.1.-14.6.23. [CrossRef]
  • 18. Irwin, J.J., Shoichet, B.K. (2005). ZINC− a free database of commercially available compounds for virtual screening. Journal of Chemical Information and Modeling, 45(1), 177-182. [CrossRef]
  • 19. Abraham, M.J., Murtola, T., Schulz, R., Páll, S., Smith, J.C., Hess, B., Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1, 19-25. [CrossRef]
  • 20. Erol, M., Celik, I., Kuyucuklu, G. (2021). Synthesis, molecular docking, molecular dynamics, DFT and antimicrobial activity studies of 5-substituted-2-(p-methylphenyl)benzoxazole derivatives. Journal of Molecular Structure, 1234, 130151. [CrossRef]
  • 21. Erol, M., Celik, I., Ince, U., Fatullayev, H., Uzunhisarcikli, E., Puskullu, M.O. (2022). Quantum mechanical, virtual screening, molecular docking, molecular dynamics, ADME and antimicrobial activity studies of some new indole-hydrazone derivatives as potent agents against E. faecalis. Journal of Biomolecular Structure and Dynamics, 40(17), 8112-8126. [CrossRef]
  • 22. Erol, M., Celik, I., Sağlık, B.N., Karayel, A., Mellado, M., Mella, J. (2022). Synthesis, molecular modeling, 3D-QSAR and biological evaluation studies of new benzimidazole derivatives as potential MAO-A and MAO-B inhibitors. Journal of Molecular Structure, 1265, 133444. [CrossRef]
  • 23. Fan, J., Fu A., Zhang, L. (2019). Progress in molecular docking. Quantitative Biology, 7, 83-89. [CrossRef]
  • 24. Stanzione, F., Giangreco, I., Cole, J.C. (2021). Use of molecular docking computational tools in drug discovery. Progress in Medicinal Chemistry, 60, 273-343. [CrossRef]
  • 25. Santos, L.H., Ferreira, R.S..Caffarena, E.R. (2019). Integrating molecular docking and molecular dynamics simulations. Docking Screens for Drug Discovery, Methods in Molecular Biology, 13-34. [CrossRef]
  • 26. Eren, D., Yalçın, İ. (2020). Rasyonel ilaç tasarımında moleküler mekanik ve moleküler dinamik yöntemlerin kullanılma amacı. Journal of Faculty of Pharmacy of Ankara University. 44(2), 334-355. [CrossRef]
  • 27. Salo-Ahen, O.M., Alanko, I., Bhadane, R., Bonvin, A.M., Honorato, R.V., Hossain, S., Juffer, A.H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A.S. (2020). Molecular dynamics simulations in drug discovery and pharmaceutical development. Processes, 9(1), 71. [CrossRef]
  • 28. Durrant, J.D., McCammon, J.A. (2011). Molecular dynamics simulations and drug discovery. BMC Biology, 9(1), 1-9. [CrossRef]
  • 29. Kirchmair, J., Markt, P., Distinto, S., Wolber, G., Langer, T. (2008). Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—what can we learn from earlier mistakes? Journal of Computer-aided Molecular Design, 22, 213-228. [CrossRef]
  • 30. Martínez, L. (2015). Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis. PloS one, 10(3), e0119264. [CrossRef]
  • 31. Ghahremanian, S., Rashidi, M.M., Raeisi, K., Toghraie, D. (2022). Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review. Journal of Molecular Liquids, 354, 118901. [CrossRef]
  • 32. Boroujeni, M.B., Dastjerdeh, M.S., Shokrgozar, M., Rahimi, H., Omidinia, E. (2021). Computational driven molecular dynamics simulation of keratinocyte growth factor behavior at different pH conditions. Informatics in Medicine Unlocked, 23, 100514. [CrossRef]
  • 33. da Fonseca, A.M., Caluaco, B.J., Madureira, J.M.C., Cabongo, S.Q., Gaieta, E.M., Djata, F., Colares, R.P., Neto, M.M., Fernandes, C.F.C., Marinho, G.S. (2023). Screening of potential inhibitors targeting the main protease structure of SARS-CoV-2 via molecular docking, and approach with molecular dynamics, RMSD, RMSF, H-bond, SASA and MMGBSA. Molecular Biotechnology, 1-15 (in press). [CrossRef]

IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS

Yıl 2023, , 978 - 986, 20.09.2023
https://doi.org/10.33483/jfpau.1311496

Öz

Objective: In this study, it was aimed to perform in silico studies on the papain-like protease structure of SARS-CoV-2 (PDB: 7JIT) of 1300 FDA-approved drugs downloaded from the ZINC database.
Material and Method: A molecular docking study was performed with PLpro (PDB ID: 7JIT) using four different molecular docking programs for a total of 1300 FDA-approved drugs obtained from the ZINC database. Conivaptan and amphotericin B were obtained in docking analysis with AutoDock Vina and Sybyl-X, respectively. Docking analysis with Glide SP and Glide XP resulted in fludarabine and panobinostat, respectively. Molecular dynamics simulations were performed for a period of 120 ns to check the stability of these four drugs.
Result and Discussion: The reliability of the results obtained using four different molecular docking programs on the SARS-CoV-2 papain-like protease of 1300 drug molecules was checked by reinserting the co-crystal ligand. Protein-ligand interactions between fludarabine, conivaptan, amphotericin-B, panobinostat, and PLpro were given. In the molecular dynamics study, RMSD, RMSF, Rg, and SASA analyses were performed for four systems. It was observed that RMSD remained constant for all 120 ns for all four systems except for amphotericin B, which deviated slightly towards the end of 120 ns. No significant fluctuation was noticed in the RMSF graphics for all four systems.

Teşekkür

All molecular dynamics simulations reported were performed utilizing TÜBİTAK (The Scientific and Technological Research Council of Turkey) ULAKBİM (Turkish Academic Network and Information Centre), High Performance and Grid Computing Centre (TRUBA resources).

Kaynakça

  • 1. Celik, I., Erol, M., Duzgun, Z. (2021). In silico evaluation of potential inhibitory activity of remdesivir, favipiravir, ribavirin and galidesivir active forms on SARS-CoV-2 RNA polymerase. Molecular Diversity, 26(1), 279-292. [CrossRef]
  • 2. Rastogi, M., Pandey, N., Shukla, A., Singh, S.K. (2020). SARS coronavirus 2: from genome to infectome. Respiratory Research, 21, 1-15. [CrossRef]
  • 3. Patel, K.P., Vunnam, S.R., Patel, P.A., Krill, K.L., Korbitz, P.M., Gallagher, J.P., Suh, J.E., Vunnam, R.R. (2020). Transmission of SARS-CoV-2: An update of current literature. European Journal of Clinical Microbiology and Infectious Diseases, 39, 2005-2011. [CrossRef]
  • 4. Wang, Z., Fu, Y., Guo, Z., Li, J., Li, J., Cheng, H., Lu, B., Sun, Q. (2020). Transmission and prevention of SARS-CoV-2. Biochemical Society Transactions, 48(5), 2307-2316. [CrossRef]
  • 5. Hasöksüz, M., Kilic, S., Sarac, F. (2020). Coronaviruses and Sars-CoV-2. Turkish Journal of Medical Sciences, 50(9), 549-556. [CrossRef]
  • 6. Çelik, İ., Erol, M., Uzunhisarcikli, E., Ufuk, İ. (2022). Virtual screening and molecular docking analysis on three sars-cov-2 drug targets by multiple computational approach. Journal of Faculty of Pharmacy of Ankara University, 46(2), 376-392. [CrossRef]
  • 7. Klemm, T., Ebert, G., Calleja, D.J., Allison, C.C., Richardson, L.W., Bernardini, J.P., Lu, B.G., Kuchel, N.W., Grohmann, C., Shibata, Y. (2020). Mechanism and inhibition of the papain‐like protease, PLpro, of SARS‐CoV‐2. The EMBO Journal, 39(18), 1-17. [CrossRef]
  • 8. Alamri, M.A., ul Qamar, M.T., Mirza, M.U., Alqahtani, S.M., Froeyen, M., Chen, L.L. (2020). Discovery of human coronaviruses pan-papain-like protease inhibitors using computational approaches. Journal of Pharmaceutical Analysis, 10(6), 546-559. [CrossRef]
  • 9. Ullrich, S., Nitsche, C. (2020). The SARS-CoV-2 main protease as drug target. Bioorganic and Medicinal Chemistry Letters, 30(17), 127377. [CrossRef]
  • 10. Gao, X., Qin, B., Chen, P., Zhu, K., Hou, P., Wojdyla, J.A., Wang, M., Cui, S. (2021). Crystal structure of SARS-CoV-2 papain-like protease. Acta Pharmaceutica Sinica B, 11(1), 237-245. [CrossRef]
  • 11. Bosken, Y.K., Cholko, T., Lou, Y.C., Wu, K.P., Chang, C.A. (2020). Insights into dynamics of inhibitor and ubiquitin-like protein binding in SARS-CoV-2 papain-like protease. Frontiers in Molecular Biosciences, 7, 174. [CrossRef]
  • 12. Friesner, R.A., Banks, J.L., Murphy, R.B., Halgren, T.A., Klicic, J.J., Mainz, D.T., Repasky, M.P., Knoll, E.H., Shelley, M., Perry, J.K. (2004). Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of Medicinal Chemistry, 47(7), 1739-1749. [CrossRef]
  • 13. Friesner, R.A., Murphy, R.B., Repasky, M.P., Frye, L.L., Greenwood, J.R., Halgren, T.A., Sanschagrin, P.C., Mainz, D.T. (2006). Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. Journal of Medicinal Chemistry, 49(21), 6177-6196. [CrossRef]
  • 14. Trott, O., Olson, A.J. (2010). AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455-461. [CrossRef]
  • 15. Jain, A.N. (2007). Surflex-Dock 2.1: robust performance from ligand energetic modeling, ring flexibility, and knowledge-based search. Journal of Computer-aided Molecular Design, 21, 281-306. [CrossRef]
  • 16. Osipiuk, J., Azizi, S.A., Dvorkin, S., Endres, M., Jedrzejczak, R., Jones, K.A., Kang, S., Kathayat, R.S., Kim, Y., Lisnyak, V.G. (2021). Structure of papain-like protease from SARS-CoV-2 and its complexes with non-covalent inhibitors. Nature Communications, 12, 1-9. [CrossRef]
  • 17. Irwin, J.J. (2008). Using ZINC to acquire a virtual screening library. Current Protocols in Bioinformatics, 22(1), 14.6.1.-14.6.23. [CrossRef]
  • 18. Irwin, J.J., Shoichet, B.K. (2005). ZINC− a free database of commercially available compounds for virtual screening. Journal of Chemical Information and Modeling, 45(1), 177-182. [CrossRef]
  • 19. Abraham, M.J., Murtola, T., Schulz, R., Páll, S., Smith, J.C., Hess, B., Lindahl, E. (2015). GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 1, 19-25. [CrossRef]
  • 20. Erol, M., Celik, I., Kuyucuklu, G. (2021). Synthesis, molecular docking, molecular dynamics, DFT and antimicrobial activity studies of 5-substituted-2-(p-methylphenyl)benzoxazole derivatives. Journal of Molecular Structure, 1234, 130151. [CrossRef]
  • 21. Erol, M., Celik, I., Ince, U., Fatullayev, H., Uzunhisarcikli, E., Puskullu, M.O. (2022). Quantum mechanical, virtual screening, molecular docking, molecular dynamics, ADME and antimicrobial activity studies of some new indole-hydrazone derivatives as potent agents against E. faecalis. Journal of Biomolecular Structure and Dynamics, 40(17), 8112-8126. [CrossRef]
  • 22. Erol, M., Celik, I., Sağlık, B.N., Karayel, A., Mellado, M., Mella, J. (2022). Synthesis, molecular modeling, 3D-QSAR and biological evaluation studies of new benzimidazole derivatives as potential MAO-A and MAO-B inhibitors. Journal of Molecular Structure, 1265, 133444. [CrossRef]
  • 23. Fan, J., Fu A., Zhang, L. (2019). Progress in molecular docking. Quantitative Biology, 7, 83-89. [CrossRef]
  • 24. Stanzione, F., Giangreco, I., Cole, J.C. (2021). Use of molecular docking computational tools in drug discovery. Progress in Medicinal Chemistry, 60, 273-343. [CrossRef]
  • 25. Santos, L.H., Ferreira, R.S..Caffarena, E.R. (2019). Integrating molecular docking and molecular dynamics simulations. Docking Screens for Drug Discovery, Methods in Molecular Biology, 13-34. [CrossRef]
  • 26. Eren, D., Yalçın, İ. (2020). Rasyonel ilaç tasarımında moleküler mekanik ve moleküler dinamik yöntemlerin kullanılma amacı. Journal of Faculty of Pharmacy of Ankara University. 44(2), 334-355. [CrossRef]
  • 27. Salo-Ahen, O.M., Alanko, I., Bhadane, R., Bonvin, A.M., Honorato, R.V., Hossain, S., Juffer, A.H., Kabedev, A., Lahtela-Kakkonen, M., Larsen, A.S. (2020). Molecular dynamics simulations in drug discovery and pharmaceutical development. Processes, 9(1), 71. [CrossRef]
  • 28. Durrant, J.D., McCammon, J.A. (2011). Molecular dynamics simulations and drug discovery. BMC Biology, 9(1), 1-9. [CrossRef]
  • 29. Kirchmair, J., Markt, P., Distinto, S., Wolber, G., Langer, T. (2008). Evaluation of the performance of 3D virtual screening protocols: RMSD comparisons, enrichment assessments, and decoy selection—what can we learn from earlier mistakes? Journal of Computer-aided Molecular Design, 22, 213-228. [CrossRef]
  • 30. Martínez, L. (2015). Automatic identification of mobile and rigid substructures in molecular dynamics simulations and fractional structural fluctuation analysis. PloS one, 10(3), e0119264. [CrossRef]
  • 31. Ghahremanian, S., Rashidi, M.M., Raeisi, K., Toghraie, D. (2022). Molecular dynamics simulation approach for discovering potential inhibitors against SARS-CoV-2: A structural review. Journal of Molecular Liquids, 354, 118901. [CrossRef]
  • 32. Boroujeni, M.B., Dastjerdeh, M.S., Shokrgozar, M., Rahimi, H., Omidinia, E. (2021). Computational driven molecular dynamics simulation of keratinocyte growth factor behavior at different pH conditions. Informatics in Medicine Unlocked, 23, 100514. [CrossRef]
  • 33. da Fonseca, A.M., Caluaco, B.J., Madureira, J.M.C., Cabongo, S.Q., Gaieta, E.M., Djata, F., Colares, R.P., Neto, M.M., Fernandes, C.F.C., Marinho, G.S. (2023). Screening of potential inhibitors targeting the main protease structure of SARS-CoV-2 via molecular docking, and approach with molecular dynamics, RMSD, RMSF, H-bond, SASA and MMGBSA. Molecular Biotechnology, 1-15 (in press). [CrossRef]
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Farmasotik Kimya
Bölüm Araştırma Makalesi
Yazarlar

Meryem Erol 0000-0001-5676-098X

Erken Görünüm Tarihi 1 Eylül 2023
Yayımlanma Tarihi 20 Eylül 2023
Gönderilme Tarihi 8 Haziran 2023
Kabul Tarihi 21 Ağustos 2023
Yayımlandığı Sayı Yıl 2023

Kaynak Göster

APA Erol, M. (2023). IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS. Journal of Faculty of Pharmacy of Ankara University, 47(3), 978-986. https://doi.org/10.33483/jfpau.1311496
AMA Erol M. IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS. Ankara Ecz. Fak. Derg. Eylül 2023;47(3):978-986. doi:10.33483/jfpau.1311496
Chicago Erol, Meryem. “IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS”. Journal of Faculty of Pharmacy of Ankara University 47, sy. 3 (Eylül 2023): 978-86. https://doi.org/10.33483/jfpau.1311496.
EndNote Erol M (01 Eylül 2023) IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS. Journal of Faculty of Pharmacy of Ankara University 47 3 978–986.
IEEE M. Erol, “IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS”, Ankara Ecz. Fak. Derg., c. 47, sy. 3, ss. 978–986, 2023, doi: 10.33483/jfpau.1311496.
ISNAD Erol, Meryem. “IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS”. Journal of Faculty of Pharmacy of Ankara University 47/3 (Eylül 2023), 978-986. https://doi.org/10.33483/jfpau.1311496.
JAMA Erol M. IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS. Ankara Ecz. Fak. Derg. 2023;47:978–986.
MLA Erol, Meryem. “IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS”. Journal of Faculty of Pharmacy of Ankara University, c. 47, sy. 3, 2023, ss. 978-86, doi:10.33483/jfpau.1311496.
Vancouver Erol M. IN SILICO EVALUATION OF SARS-COV-2 PAPAIN-LIKE PROTEASE INHIBITORY ACTIVITY OF SOME FDA-APPROVED DRUGS. Ankara Ecz. Fak. Derg. 2023;47(3):978-86.

Kapsam ve Amaç

Ankara Üniversitesi Eczacılık Fakültesi Dergisi, açık erişim, hakemli bir dergi olup Türkçe veya İngilizce olarak farmasötik bilimler alanındaki önemli gelişmeleri içeren orijinal araştırmalar, derlemeler ve kısa bildiriler için uluslararası bir yayım ortamıdır. Bilimsel toplantılarda sunulan bildiriler supleman özel sayısı olarak dergide yayımlanabilir. Ayrıca, tüm farmasötik alandaki gelecek ve önceki ulusal ve uluslararası bilimsel toplantılar ile sosyal aktiviteleri içerir.