tetano
Editor, Senior Moderator
Sci Rep
. 2024 Jun 20;14(1):14255.
doi: 10.1038/s41598-024-65228-5. Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme
Hamlet Khachatryan[SUP] 1 2 [/SUP], Mher Matevosyan[SUP] 3 [/SUP], Vardan Harutyunyan[SUP] 3 [/SUP], Smbat Gevorgyan[SUP] 4 3 [/SUP], Anastasiya Shavina[SUP] 4 3 [/SUP], Irina Tirosyan[SUP] 3 [/SUP], Yeva Gabrielyan[SUP] 3 [/SUP], Marusya Ayvazyan[SUP] 3 [/SUP], Marine Bozdaganyan[SUP] 4 [/SUP], Zeynab Fakhar[SUP] 5 [/SUP], Sajjad Gharaghani[SUP] 5 [/SUP], Hovakim Zakaryan[SUP] 6 7 [/SUP]
Affiliations
The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.
Keywords: COVID-19; Conformational analysis; Coronavirus; Mpro; Structural clustering; Virtual screening.
. 2024 Jun 20;14(1):14255.
doi: 10.1038/s41598-024-65228-5. Computational evaluation and benchmark study of 342 crystallographic holo-structures of SARS-CoV-2 Mpro enzyme
Hamlet Khachatryan[SUP] 1 2 [/SUP], Mher Matevosyan[SUP] 3 [/SUP], Vardan Harutyunyan[SUP] 3 [/SUP], Smbat Gevorgyan[SUP] 4 3 [/SUP], Anastasiya Shavina[SUP] 4 3 [/SUP], Irina Tirosyan[SUP] 3 [/SUP], Yeva Gabrielyan[SUP] 3 [/SUP], Marusya Ayvazyan[SUP] 3 [/SUP], Marine Bozdaganyan[SUP] 4 [/SUP], Zeynab Fakhar[SUP] 5 [/SUP], Sajjad Gharaghani[SUP] 5 [/SUP], Hovakim Zakaryan[SUP] 6 7 [/SUP]
Affiliations
- PMID: 38902397
- DOI: 10.1038/s41598-024-65228-5
The coronavirus disease 19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to a global health crisis with millions of confirmed cases and related deaths. The main protease (Mpro) of SARS-CoV-2 is crucial for viral replication and presents an attractive target for drug development. Despite the approval of some drugs, the search for effective treatments continues. In this study, we systematically evaluated 342 holo-crystal structures of Mpro to identify optimal conformations for structure-based virtual screening (SBVS). Our analysis revealed limited structural flexibility among the structures. Three docking programs, AutoDock Vina, rDock, and Glide were employed to assess the efficiency of virtual screening, revealing diverse performances across selected Mpro structures. We found that the structures 5RHE, 7DDC, and 7DPU (PDB Ids) consistently displayed the lowest EF, AUC, and BEDROCK scores. Furthermore, these structures demonstrated the worst pose prediction results in all docking programs. Two structural differences contribute to variations in docking performance: the absence of the S1 subsite in 7DDC and 7DPU, and the presence of a subpocket in the S2 subsite of 7DDC, 7DPU, and 5RHE. These findings underscore the importance of selecting appropriate Mpro conformations for SBVS, providing valuable insights for advancing drug discovery efforts.
Keywords: COVID-19; Conformational analysis; Coronavirus; Mpro; Structural clustering; Virtual screening.