Article Versions Notes

Ghufran M, Ullah M, Khan HA, Ghufran S, Ayaz M, Siddiq M, Abbas SQ, Hassan SSu, Bungau S. In-Silico Lead Druggable Compounds Identification against SARS COVID-19 Main Protease Target from In-House, Chembridge and Zinc Databases by Structure-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations. Bioengineering. 2023; 10(1):100. https://doi.org/10.3390/bioengineering10010100

Ghufran, Mehreen, Mehran Ullah, Haider Ali Khan, Sabreen Ghufran, Muhammad Ayaz, Muhammad Siddiq, Syed Qamar Abbas, Syed Shams ul Hassan, and Simona Bungau. 2023. "In-Silico Lead Druggable Compounds Identification against SARS COVID-19 Main Protease Target from In-House, Chembridge and Zinc Databases by Structure-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations" Bioengineering 10, no. 1: 100. https://doi.org/10.3390/bioengineering10010100

Ghufran, M., Ullah, M., Khan, H. A., Ghufran, S., Ayaz, M., Siddiq, M., Abbas, S. Q., Hassan, S. S. u., & Bungau, S. (2023). In-Silico Lead Druggable Compounds Identification against SARS COVID-19 Main Protease Target from In-House, Chembridge and Zinc Databases by Structure-Based Virtual Screening, Molecular Docking and Molecular Dynamics Simulations. Bioengineering, 10(1), 100. https://doi.org/10.3390/bioengineering10010100