Ajmal, A.; Danial, M.; Zulfat, M.; Numan, M.; Zakir, S.; Hayat, C.; Alabbosh, K.F.; Zaki, M.E.A.; Ali, A.; Wei, D.
In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches. Pharmaceuticals 2024, 17, 551.
https://doi.org/10.3390/ph17050551
AMA Style
Ajmal A, Danial M, Zulfat M, Numan M, Zakir S, Hayat C, Alabbosh KF, Zaki MEA, Ali A, Wei D.
In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches. Pharmaceuticals. 2024; 17(5):551.
https://doi.org/10.3390/ph17050551
Chicago/Turabian Style
Ajmal, Amar, Muhammad Danial, Maryam Zulfat, Muhammad Numan, Sidra Zakir, Chandni Hayat, Khulood Fahad Alabbosh, Magdi E. A. Zaki, Arif Ali, and Dongqing Wei.
2024. "In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches" Pharmaceuticals 17, no. 5: 551.
https://doi.org/10.3390/ph17050551
APA Style
Ajmal, A., Danial, M., Zulfat, M., Numan, M., Zakir, S., Hayat, C., Alabbosh, K. F., Zaki, M. E. A., Ali, A., & Wei, D.
(2024). In Silico Prediction of New Inhibitors for Kirsten Rat Sarcoma G12D Cancer Drug Target Using Machine Learning-Based Virtual Screening, Molecular Docking, and Molecular Dynamic Simulation Approaches. Pharmaceuticals, 17(5), 551.
https://doi.org/10.3390/ph17050551
